SMJ

‌E-ISSN 2228-8082

Volume 77, Number 1, January 2025

Geriatric Medicine and Gerontology

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THAILAND SECTION 1954

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MONTHLY

Siriraj Medical Journal

The world-leading biomedical science of Thailand

ORIGINAL ARTICLE REVIEW ARTICLE

‌ORIGINAL ARTICLE‌

1

Clinical Effectiveness Evaluation and

Cost-effectiveness Analysis of Comprehensive Geriatric Assessment and Multidisciplinary Team for Ambulatory Older Patients: A Cohort Study

Prakasit Virulhakul, Somboon Intalapaporn, Sichon Luerithipong, Narisa Tantai, Satanan, Weerasak Muangpaisan

SMJ

Siriraj Medical Journal

The world-leading biomedical science of Thailand

Volume 77 Number 1

January 2025

12

Reliability and Validity of the Thai Version of the PAINAD Scale: An Extended Application of Pain Assessment in the Moderately Severe Stage of Dementia

Natthapapath Boonsawat, Patumporn Suraarunsumrit, Sutisa Pitiyarn,

Napaporn Pengsorn, Varalak Srinonprasert, Sahatsa Mandee, Titima Wongviriyawong

22

Outcomes of Robot-assisted Radical Prostatectomy in Men Aged 75 Years Old or Older: A Single-center Study in Thailand

Attapol Mahalelakul, Pubordee Assavavirojekul, Sunai Leewansangtong, Varat Woranisarakul,Thitipat Hansomwong, Sittiporn Srinualnad

29

Validation of Self-application-based Malnutrition and Limited Mobility Screening Tools Compared with Standard Diagnostic Tools in Older Adults

Panvadee Tanaviboon, Weerasak Muangpaisan, Angkana Jongsawadipatana, Pitiporn Siritipakorn, Somboon Intalapaporn

39

A Survey of Home-Based Cognitive Stimulation Activities in Thai Patients with Mild Cognitive Impairment and Mild Dementia

Wirarat Jinatongthai, Kitikan Thana-udom, Vorapun Senanarong, Chatchawan Rattanabannakit

51

Prevalence of Geriatric Syndromes and Satisfaction of Service in Older People Receiving Annual Health Screening at the Check-up Clinic, Siriraj Hospital

Harisd Phannarus, Supakorn Chansaengpetch, Tirathat Virojskulchai, Napaporn Pengsorn, Pensri Chaopanitwet, Usa Vannachavee, Jirawit Wong-ekkabut, Ananya Treewisoot, Sunun Thanasamut, Angkana Jongsawadipatana, Weerasak Muangpaisan

64

Effectiveness of Personalized Multifactorial Fall Risk Assessment and Intervention in Reducing Fall Rates Among Older Adults: A Retrospective Study

Piyapat Dajpratham, Poungkaew Thitisakulchai, Rinlada Pongratanakul, Rachaporn Prapavanond, Sirapat Haridravedh, Weerasak Muangpaisan

73

Depressive Symptoms and Poor Functional Status are Factors Associated with Frailty and Decreased Quality of Life in Thai Older Breast Cancer Survivors

Arpa Satayasanskul, Prasert Assantachai, Suebwong Chuthapisith, Monthira Thammasalee, Thapanee Chimchanwet, Suthipol Udompunturak

83

Impact of Frailty on Healthcare Utilization in Older Patients Admitted to Medical Wards: A Study from a Large Medical School in a Middle-income Setting

93

Outcomes in Critically Ill Patients Aged 90 Years and Older: A Scoping Review

Nuanprae Kitisin, Nuttapol Pattamin, Nirinrada Thongpibul, Nattaya Raykateeraroj

REVIEW ARTICLE

Patumporn Suraarunsumrit, Pacha Sinthornkasem, Ponnapa Petchthai, Supawadee Sainimnuan, Rinrada Preechitkul, Varalak Srinonprasert

‌Executive Editor:

SIRIRAJ MEDICAL JOURNAL

SMJ

https://he02.tci-thaijo.org/index.php/sirirajmedj/index

Professor Apichat Asavamongkolkul, Mahidol University, Thailand

Editorial Director:

Professor Aasis Unnanuntana, Mahidol University, Thailand

Associate Editors

Assistant Professor Adisorn Ratanayotha, Mahidol University, Thailand Pieter Dijkstra, University of Groningen, Netherlands

Professor Phunchai Charatcharoenwitthaya, Mahidol University, Thailand Professor Varut Lohsiriwat, Mahidol University, Thailand

International Editorial Board Members

Editor-in-Chief:

Professor Thawatchai Akaraviputh, Mahidol University, Thailand

Allen Finley, Delhousie University, Canada

Christopher Khor, Singapore General Hospital, Singapore Ciro Isidoro, University of Novara, Italy

David S. Sheps, University of Florida, USA

David Wayne Ussery, University of Arkansas for Medical Sciences, USA Dennis J. Janisse, Medical College of Wisconsin, USA

Dong-Wan Seo, University of Ulsan College of Medicine, Republic of Korea Folker Meyer, Argonne National Laboratory, USA

Frans Laurens Moll, University Medical Center Ultrecht, Netherlands George S. Baillie, University of Glasgow, United Kingdom

Gustavo Saposnik, Unity Health Toronto, St. Micheal Hospital, Canada Harland Winter, Harvard Medical School, USA

Hidemi Goto, Nagoya University Graduate School of Medicine, Japan Ichizo Nishino, National Institute of Neuroscience NCNP, Japan Intawat Nookaew, University of Arkansas for Medical Sciences, USA James P. Doland, Oregon Health & Science University, USA

John Hunter, Oregon Health & Science University, USA

Karl Thomas Moritz, Swedish University of Agricultural Sciences, Sweden Kazuo Hara, Aichi Cancer Center Hospital, Japan

Keiichi Akita, Institute of Science Toko, Japan Kyoichi Takaori, Kyoto University Hospital, Japan Marcela Hermoso Ramello, University of Chile, Chile Marianne Hokland, University of Aarhus, Denmark

Matthew S. Dunne, Institute of Food, Nutrition, and Health, Switzerland Mazakayu Yamamoto, Tokyo Women’s Medical University, Japan Mitsuhiro Kida, Kitasato University & Hospital, Japan

Moses Rodriguez, Mayo Clinic, USA

Nam H. CHO, Ajou University School of Medicine and Hospital, Republic of Korea Nima Rezaei, Tehran University of Medical Sciences, Iran

Noritaka Isogai, Kinki University, Japan

Philip A. Brunell, State University of New York At Buffalo, USA Philip Board, Australian National University, Australia Ramanuj Dasgupta, Genome Institution of Singapore

Richard J. Deckelbaum, Columbia University, USA Robert W. Mann, University of Hawaii, USA

Robin CN Williamson, Royal Postgraduate Medical School, United Kingdom Sara Schwanke Khilji, Oregon Health & Science University, USA

Seigo Kitano, Oita University, Japan Seiji Okada, Kumamoto University

Shomei Ryozawa, Saitama Medical University, Japan Shuji Shimizu, Kyushu University Hospital, Japan

Stanlay James Rogers, University of California, San Francisco, USA Stephen Dalton, Chinese University of HK & Kyoto University

Tai-Soon Yong, Yonsei University, Republic of Korea Tomohisa Uchida, Oita University, Japan

Victor Manuel Charoenrook de la Fuente, Centro de Oftalmologia Barraquer, Spain Wikrom Karnsakul, Johns Hopkins Children’s Center, USA

Yasushi Sano, Director of Gastrointestinal Center, Japan Yik Ying Teo, National University of Singapore, Singapore Yoshiki Hirooka, Nagoya University Hospital, Japan

Yozo Miyake, Aichi Medical University, Japan Yuji Murata, Aizenbashi Hospital, Japan

Editorial Board Members

Vitoon Chinswangwatanakul, Mahidol University, Thailand Jarupim Soongswang, Mahidol University, Thailand

Jaturat Kanpittaya, Khon Kaen University, Thailand Nopphol Pausawasdi, Mahidol University, Thailand Nopporn Sittisombut, Chiang Mai University, Thailand Pa-thai Yenchitsomanus, Mahidol University, Thailand Pornprom Muangman, Mahidol University, Thailand Prasit Wattanapa, Mahidol University, Thailand

Prasert Auewarakul, Mahidol University, Thailand Somboon Kunathikom, Mahidol University, Thailand Supakorn Rojananin, Mahidol University, Thailand

Suttipong Wacharasindhu, Chulalongkorn University, Thailand Vasant Sumethkul, Mahidol University, Thailand

Watchara Kasinrerk, Chiang Mai University, Thailand Wiroon Laupattrakasem, Khon Kaen University, Thailand Yuen Tanniradorn, Chulalongkorn University, Thailand

Editorial Assistant: Nuchpraweepawn Saleeon, Mahidol University, Thailand

Proofreader: Amornrat Sangkaew, Mahidol University, Thailand, Nuchpraweepawn Saleeon, Mahidol University, Thailand

‌Clinical Effectiveness Evaluation and Cost-effectiveness Analysis of Comprehensive Geriatric Assessment and Multidisciplinary Team for Ambulatory Older Patients: A Cohort Study

Prakasit Virulhakul, M.D.1, Somboon Intalapaporn, M.D.2, Sichon Luerithipong, M.D.2, Narisa Tantai 3, Satanan Maneeon3, Weerasak Muangpaisan, M.D.2,*

1Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 2Department of Preventive and Social Medicine,

Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 3Pharmacy Department, Siriraj Hospital, Mahidol University, Bangkok, Thailand.

*Corresponding author: Weerasak Muangpaisan E-mail: drweerasak@gmail.com

Received 13 October 2024 Revised 7 November 2024 Accepted 16 November 2024 ORCID ID:http://orcid.org/0000-0001-5863-3597 https://doi.org/10.33192/smj.v77i1.271623

All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.

ABSTRACT

Objective: The comprehensive geriatric assessment (CGA) and multidisciplinary team (MDT) services are essential components of clinics that promote holistic care for older patients. However, their clinical and cost-effectiveness have not been fully established.

Materials and Methods: This study was a 1-year cohort, two-arm observational study conducted in ambulatory older patients at the Geriatric and Internal Medicine OPD. The primary endpoint was clinical effectiveness: activity of daily living (ADL), Thai mental status examination (TMSE), Mini-nutritional assessment (MNA), extra-visit, hospitalization, length of stay, fall rate, and death rate. The secondary endpoint was a cost-utility analysis using a decision-tree and Markov model. Outcomes included the incremental cost-effectiveness ratio (ICER), and quality of life, assessed by the European Quality of Life Five Dimensions Five Levels (EQ-5D-5L). Sensitivity analysis was conducted through probabilistic methods.

Results: Older adults who received the CGA and MDT service in the geriatric OPD showed improved nutritional status, with the MNA-SF score increasing from 9.3 (± 3.3) to 10.9 (± 2.9) (p=0.01). There were no significant differences between groups in terms of extra-visits, hospitalizations, length of stay, fall rate, or death rate. After one year, the ICER for the CGA and MDT group was US$-3,073 per quality-adjusted life year (QALY) gained to usual care, indicating cost savings at a threshold of $4, 564.9 US dollar per QALY gained.

Conclusion: The CGA and MDT service in a geriatric clinic is clinically effective compared to usual care over a one-year follow-up, as demonstrated by the improvement in nutritional status. Additionally, the CGA and MDT is a cost-saving intervention.

Keywords: Clinical effectiveness evaluation; cost-effectiveness; incremental cost-effectiveness; comprehensive geriatric assessment; multidisciplinary team, geriatric clinic (Siriraj Med J 2025; 77: 1-11)

INTRODUCTION

Currently, the number of older adults is increasing significantly.1 Older adults with comorbidity are considered a national healthcare challenge.2,3 Evidence shows that patients who receive comprehensive geriatric assessment (CGA) and multidisciplinary team (MDT) services tend to live at home longer, have a reduced rate of institutionalization, receive more palliative care, and are prescribed safer, low-risk medications.4-8 Studies in Europe and the US have found that CGA & MDT services improve clinical outcomes in over usual care in inpatient department (IPD) settings. However, these services in Western countries often incur high costs due to the extensive use of comprehensive service.4,9-13 One study in Southeast Asia demonstrated that CGA and MDT services in an IPD setting can be both clinically effective and cost-saving for older adults.14 It is necessary to evaluate clinical and cost-effectiveness15 of CGA and MDT services in the Out-patient department (OPD) settings for older adults, as this has not yet been studied in Thailand or in tertiary hospitals worldwide.

MATERIALS AND METHODS

Study design

This study was a prospective cohort, 52-week trial

with two parallel arms, conducted in the Geriatric OPD and Internal Medicine OPD at a tertiary hospital in Bangkok, Thailand. The study included both clinical and cost-effective analyses.

Cost-utility analysis was performed using a model- based approach (Decision Tree and Markov Model). The comparators were CGA and MDT versus usual care. The effectiveness was measured in life years (LY) and quality-adjusted life year (QALY). The study adopted a societal perspective, with a time horizon extending over length of life. Probabilistic sensitivity analysis was used as the analytic method.

Intervention and control

In the intervention group (CGA and MDT), older adults were patients who had previously received services in the Geriatric OPD. They underwent medical examinations and received treatment from a team of geriatricians and MDT, including a pharmacist, psychologist, geriatric nurse, dietitian, and rehabilitation team.

In the usual care group, older adults were patients who had previously received services in the Internal Medicine OPD. They received medical examinations and standard care from their doctors, who were either internists or specialist medicine physicians.

Participants and recruitment

The participants were older adults who met the following criteria: 1) aged 60 years or older with at least two comorbidities, 2) able to follow up at the hospital, and 3) had no communicable diseases. If participants were unable to provide personal history, a proxy or caregiver willing to participate in the study was asked to provide information instead. The exclusion criteria included older adults who: 1) had an unstable medical condition (ie sepsis, shock), 2) were expected to undergo surgery within 1 month, 3) had an accident which required immediate treatment within 24 hours, 4) were predicted to have a life expectancy < 6 months and 5) were not willing to participate in the research. All eligible older adults and their legal representatives were invited to participate in the study without undue influence and provided written informed consent.

Older adults visiting the Geriatric OPD and Internal Medicine OPD were randomly selected based on their OPD registration times: 8.00 AM, 9.00 AM, 10.00 AM, 11.00 AM, 1.00 PM, 2.00 PM, 3.00 PM. If a selected older adult did not meet the inclusion criteria, the next individual registered at that time was chose. The recruitment process was stratified by age and level of ADL. ADL evaluation included the Barthel Index, Lawton Scale, and ADL state.16

Procedures

The researcher conducted interviews with older adults. After obtaining informed consent, the researcher began by assessing their cognitive function using the Thai mental status examination (TMSE) test. The total score is 30 and the cut-off value for possible cognitive impairment is 23

or less. It includes assessment in orientation, memory, attention, calculation, language ability, picture copying, and abstract thinking. If the patients were diagnosed or showed symptoms of dementia and had a TMSE score ≤ 23 points, baseline characteristics, including age, gender, education level, Barthel ADL score, Lawton IADL score, Charlson comorbidity index, Utility (EQ5D5L), MNA short form, number of falls within 3 months, underlying diseases, and history of recent hip fracture were gathered from their caregiver or proxy.

The second and third interviews were conducted at the 6th month and 12th months, respectively. Phone interviews were used to collect cost-related information at the 3rd and 9th months. Onsite interviews at the 6th and 12th months were carried out to collect both clinical and cost data. Permission was requested from the hospital database department to access medical staff salaries for both the CGA and MDT and usual care groups to calculate direct medical costs.

At the beginning (day 0), and again at the 6th and 12th months, the researcher collected utility data by explaining the EQ-5D-5L scoring process to older adults or their caregivers before conducting the interview.

The analysis was performed at the 12-month mark to compare the clinical effectiveness and cost effectiveness between the two groups.

Outcomes

From the total of 138 older adults at the beginning of the study, the 55 older adults in CGA&MDT and 52 in usual care who remained at the one-year follow-up were analyzed (Fig 1).

Fig 1. Study flowchart.

Abbreviations: CGA= comprehensive geriatric assessment, MDT=multidisciplinary team

Primary outcome

The primary outcome was the clinical effectiveness assessed across five aspects; 1. ADL consisting of the Barthel Index, Lawton Scale and ADL state16, 2. Quality of life (QOL) and patient satisfaction, 3. Cognitive function assessed using TMSE, 4. Nutritional status evaluated using the MNA-SF, and 5. Unplanned hospitalizations, OPD visits, emergency department visits, length of hospital stays, fall events, and death rate.

The ADL was classified into five groups17 as follows.

1. ADL 0: No ADL limitation

2. ADL 1: Mild ADL limitation

3. ADL 2: Moderate ADL limitation

4. ADL 3: Moderate ADL limitation

5. ADL 4: Complete ADL limitation

Given the study’s one-year duration, the expected number of participant deaths was small. Therefore, the ADL state was used to predict the chance of death based on the study by Stineman MG.15 The classification of ADL groups allowed for a one-year follow-up to match the ADL predictor with the possibility of death.15 This information was then used to calculate, QALY, and incremental cost effectiveness ratio (ICER) in a decision tree diagram18 and Markov model.19

Secondary outcomes

The secondary outcomes included cost effectiveness in terms of the ICER. The intervention (CGA and MDT) cost and control (usual) cost were compared to assess both cost and QOL. ICER was evaluated to determine if adopting the new intervention is an efficient use of resources.

Costs were considered from a societal perspective, with a discount rate of 3%. Data were collected prospectively over a one-year period. The costs included direct medical costs, direct non-medical costs and indirect costs. Direct medical costs borne by patients were obtained from the hospital database, including medical services and personnel costs. The personnel cost was calculated by multiplying their hourly salary by the duration of service provided to each older adult. Direct non-medical costs included living expenses during the study, such as transportation, food and accommodation for healthcare visits. Costs covering expenses for drugs, transportation, food, accommodation, and medical devices for each older adult were collected and recorded in a logbook. Total costs for each older adult were computed by adding all medical costs listed in the parameter and utility table. The transitional ADL states and utility were obtained from evaluations at the 0th and 12th month evaluation for both groups. At the 0th month, ADLs were classified into states 0 to IV; at the

12th month, they were classified into states 0 to IV and death (within 12 months) (Supplementary Fig 1). The utility scores derived from the health-related quality of life measure (EQ-5D-5L) questionnaire were converted to a scale ranging from 0 to 1 (with lower scores indicating lower quality of life and higher scores indicating better quality of life). Though there are many QOL measures, we chose the EQ-5D-5L which is the generic, preference- based measure to generate QALYs for the cost-effective analysis. This questionnaire is completed with low burden to patients and readily applied in a various health setting. It covered five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. The EQ-5D-5L questionnaire has an associated utility which is derived from its preference-based score in the Thai population.20

Statistical analysis

Sample size calculation

The effect of the CGA and MDT intervention on ADL outcomes from a previous study showed that older adults who received CGA and MDT intervention in an IPD setting and were followed up for 3 months had a higher mean Barthel ADL score than those in the usual care group (17.15 vs 14.35).14 To achieve a power of 90% and a two-sided significance level of 0.05, 126 older adults were required to detect a difference. Considering a potential loss to follow up rate of 10%, the total sample size needed was 138 older adults.

Data analysis

A per-protocol analysis was used for the clinical outcomes. A linear model was performed to analyze the change in clinical effectiveness (mean ADL scores using the (Barthel and Lawton indexes over 12 months. In the regression analysis, potential risk factors for the clinical outcomes with a P value of <0.2 from the univariate analysis were included. The categorical data, including extra visits, hospitalization, fall rate, death rate, and patient satisfaction, were compared between the 0th month and 12th months to assess the effects of the CGA and MDT intervention versus usual care. For the proportional effectiveness analysis of categorical outcomes, a chi- square test was used. For continuous variables, a Student’s t-test was applied to normally distributed data, while the Mann-Whitney U test was used for non-normally distributed data. The estimated effect size was reported as a mean or median difference for relevant data, along with 95% confidence intervals. Statistical analyses were conducted using PASW Statistics 18 (SPSS Inc., Chicago, IL, USA). All tests were two-tailed, and a p-value of less

than 0.05 was considered statistically significant. The outcome of the economic analysis was based on the intention-to-treat analysis.

To estimate the costs and QALY, and assess the cost- effectiveness of the CGA and MDT service, a decision tree was applied to model the transitional states of older adults’ ADL from the 0th to the 12th month, dividing participants into the intervention arm (CGA and MDT) and the control arm (usual care). Following this, a simple two-state Markov model (“Alive” and “Dead”) was employed.21,22 In the Markov model, all participants interviewed after the 1-year follow-up started in the “Alive” state. During each annual Markov cycle, they faced a risk dying and could transition to the absorbing “Dead” state5 (Supplementary Fig 2). The annual risk of dying was based on the all-cause 1-, 5-, and 10-year mortality rates in older adults, as described in the study of activities of daily living stages by Stineman MG.17 The model ran for 30 cycles to ensure that, by the end of the analysis, all participants had transitioned to the “Dead” state. For each Markov cycle in which participants remained in the “Alive” state, they incurred an annual cost and QALY estimate. No costs or QALY were associated with the “Dead” state. At the end of the analysis, the discounted costs and QALY were summed over all cycles to estimate the per-participant mean costs and QALY for both CGA and usual care, respectively. The model was implemented in Microsoft Excel, with the outcome presented as total cost and total QALY.

The ICER was used to measure cost-effectiveness by dividing the difference in costs between the intervention and control groups by the difference in QALY gained. This helped determine if the CGA and MDT services provided more benefit per cost compared to usual care. A probabilistic sensitivity analysis was conducted to account for uncertainty. Cost-effectiveness acceptability curves and cost-effectiveness plane were used to explore uncertainties in costs and outcomes. A Monte Carlo stimulation23 was employed, generating 1,000 rounds of simulation using a gamma distribution for cost uncertainties and a beta distribution for utility and probability of death in each ADL state parameter. The costs of CGA and MDT and usual care, as well as QALY data, were collected over one year from the hospital database and

patient interviews.

RESULTS

Patient characteristics

At baseline, each group consisted of 69 older adults. The older adults in CGA and MDT and usual care groups were comparable in many aspects. For example, the mean

age was 81.5 (± 8.6) years in the CGA and MDT group and 77.6 (± 8.3) years in usual care group, respectively (Table 1). However, the CGA and MDT group had lower TMSE scores compared to the usual care group. There was also a higher proportion of older adults with dementia, OA knee and recent hip fracture within 3 months in the CGA and MDT group. Cancer patients were present in both groups (Table 1).

Outcomes

Clinical effectiveness analysis

After one year of follow-up, the clinical outcomes were summarized in supplementary table 1. Older adults in the CGA and MDT group showed greater improvement in nutritional status compared to those in the usual care group. Specifically, the MNA-SF score for older adults who received CGA and MDT services from a Geriatric OPD improved significantly, increasing from 9.3 (± 3.3) to 10.9 (± 2.9), p=0.01 (Table 2). In contrast, the usual care group showed a non-significant change in their MNA-SF score over the same period (10.1 (± 2.8) vs

10.2 (± 2.6), p=0.69) (Table 2). Other clinical outcomes were similar between the two groups.

The CGA and MDT services in the OPD setting did not demonstrate a reduction in unplanned OPD visits, hospitalizations, ER visits, or occurrences of serious and non-serious falls. Additionally, there was no significant decrease in mortality rates after one year of r follow-up, with 12 deaths in the CGA and MDT group and 13 in the usual care group (21.8% vs 25.0% p=0.76) (Supplementary Table 2).

Quality-adjusted life year

At the one-year follow-up, the number of older adults in the CGA and MDT group was 55, while the usual care group had 52 participants. At baseline, the CGA and MDT group had a non-significant utility difference compared to the usual care group (0.68 (± 0.23) vs 0.60 (± 0.24)) (Supplementary Table 2). After one year, the CGA and MDT group showed an increase in utility, rising from 0.68 (± 0.23) at baseline to 0.76 (± 0.21) (p=0.01) (Table 3). Similarly, the usual care also experienced an increase in utility from 0.60 (± 0.24) at baseline to 0.72 (± 0.22) after one-year (p=0.01) as shown in Table 2. Both groups demonstrated significant improvement in utility.

Economic evaluation: cost-effectiveness analysis

The relevant costs for CGA and MDT and usual care were US$8,309 and $9,039, respectively. The QALYs for the CGA and MDT and usual care groups were

TABLE 1. Baseline characteristics and underlying diseases.

Abbreviations: CGA = comprehensive geriatric assessment, MDT = multidisciplinary team, TMSE = Thai mental state examination, MNA SF = mini-nutritional assessment short form, EQ5D5L = European quality of life five dimensions five levels, UC = universal coverage, SD

= standard of deviation, HT = hypertension, DM = diabetic mellitus, DLP = dyslipidemia, CKD = chronic kidney disease, NPH = normal pressure hydrocephalus, CA = cancer, OA = osteoarthritis, COPD = chronic obstructive pulmonary disease

TABLE 2. Comparison of baseline and 1-year outcomes of the CGA and MDT group and usual care group.

Abbreviations: TMSE = Thai mental state examination, MNA= mini-nutritional assessment, EQ5D5L= Euro quality of life group 5 dimensions 5 levels, MNA-SF= mini-nutritional assessment short form, SD= standard deviation

TABLE 3. Costs, health outcomes, and ICER of the CGA and MDT group compared to the usual care group.

Abbreviations: CGA&MDT= comprehensive geriatric assessment and Multidisciplinary team, Lys = life years, QALY = quality adjusted life year (currency rate in January 2022: 35.05 Baht = 1 US dollar)

2.321 and 2.084, respectively. The incremental cost was

$-730, and the incremental QALYs were 0.237. The incremental life year gain at one year was 0.18 years. Based on probabilistic analysis, the incremental cost- effectiveness was cost-saving at $3,073 per QALY (Table 3).

Uncertainty analysis

The cost-effectiveness acceptability curve, based on the net benefit approach, was used to illustrate the relationship between the ceiling ratio (willingness to pay for a unit of QALY gained) and the probability of favoring each group. From a societal perspective, the

results indicated that the CGA and MDT service, at a cost of $4,564 per QALY gained, had a 90% probability of being cost-effective, while the usual care service had only a 10% probability (Fig 2). Therefore, the CGA and MDT service was the preferred choice.

The results of the probabilistic analysis are shown on the cost-effectiveness plane (Supplementary Fig 3). The joint distribution of incremental costs and QALYs reveals that the CGA and MDT service is associated with a slightly decrease in cost in 99% of the simulations (at a cost-effectiveness threshold of $4,564) and a gain in QALYs in 92 % of the simulations.

Fig 2. Cost-effectiveness acceptability curves for quality-adjusted life-year gained

Abbreviation: CGA= comprehensive geriatric assessment and multidisciplinary team

DISCUSSION

This was the first prospective study to assess the clinical effectiveness and cost-effectiveness of a geriatric service at a Geriatric OPD in a tertiary hospital within a medical school in Thailand. Previous studies on the cost- effectiveness and clinical effectiveness of OPD services were conducted in municipal ambulatory OPD settings in Sweden5 and community clinics in England.25 While these European studies demonstrated clinical effectiveness benefits, the cost analysis did not show cost-effectiveness due to the high intervention costs. In contrast, this study found that CGA and MDT was a cost-saving intervention in the OPD setting in Thailand.

Following these initial findings on cost-effectiveness, a closer look at baseline characteristics reveals further insights into the unique benefits observed in the CGA and MDT group. The baseline characteristics between two groups were similar, although the CGA and MDT group had a lower TMSE score compared to the usual care group at baseline. Despite this, the outcomes showed that MNA-SF score in the CGA and MDT improved more than in the usual care group, while both groups experienced an increase in quality of life along over the one-year study period. The improvement in nutritional status among older adults could be attributed to the CGA and MDT service, which maintained the physical, mental and functional health of patients with poor nutritional status. This was achieved by providing appropriate nutritional education and nutritional supplements to effectively enhance their nutritional health.

In addition to nutritional improvements, the study also considered the broader context of quality of life,

especially considering pandemic-related challenges. The evaluation of quality of life (EQ-5D-5L score) appeared to be lower than the mean score for the Thai population.20 Several factors may explain this finding. First, this study was conducted during the COVID-19 pandemic, which directly affected older adults’ quality of life, particularly in terms of depressed mood and anxiety, as well as the well-being of caregivers.26-28 Secondly, most older adults in this study were female, had multiple comorbidities, and experienced financial problems due to the lockdown, all of which are associated with lower quality of life scores.29 While these factors impacted quality of life,

the study also assessed how CGA and MDT services affected healthcare utilization and mortality, providing a comprehensive view of their impact on older adults. The CGA and MDT services in the OPD setting did not demonstrate a benefit in reducing unplanned OPD visits, hospitalizations, ER visits, or the incidence of serious and non-serious falls. Additionally, the CGA and MDT services did not decrease the number of deaths during the one-year follow-up period. This may be because the CGA and MDT service did not directly address the primary causes of mortality in older adults, particularly those due to infectious diseases. Neither the death rate nor the occurrence of undesirable events (unplanned OPD visits, hospitalizations, ER visits, serious and non-serious falls) was found to be directly preventable through this intervention.

Although certain healthcare utilizations were not significantly reduced, comparing these findings with studies from different regions emphasizes the cost-effectiveness of CGA and MDT services in specific contexts. The

findings indicated that while CGA and MDT services were a more expensive option in terms of direct medical costs, they were likely to provide better outcomes in nutritional status and quality of life compared to usual care. Although the cost of medical personnel in the CGA and MDT group was three times higher than that of the usual care group, other societal costs associated with CGA and MDT were lower. This demonstrates both clinical and cost effectiveness, similar to the study by Soejono CH14 in Southeast Asia. However, that study was non- randomized control trial and was conducted in an IPD setting. It showed that the CGA provided clinical and cost benefits over usual care in the 30 days follow-up after hospitalization. In our study, the cost savings in the CGA and MDT group were mainly due to a trend of fewer extra OPD visits and unplanned admissions. While these numbers were not statistically lower than those in in the usual care group, the total cost savings still suggested cost-effectiveness. Interestingly, the CGA and MDT service did not significantly reduce unexpected events but did contribute to overall cost-saving results. The number of extra OPD visits in the GCA and MDT group was not lower than in the usual care group, a finding that contrasts with the study by Wei et al.30 The study by Wei et al reported reduced number of drugs prescribed, fewer healthcare utilization in terms of OPD visits, emergency department visit, and hospitalizations among older adults in the Geriatric OPD which provided the CGA and MDT services as compared to non-geriatric OPD clinic. The reduction in medical costs was shown in patients with more comorbidities and an older age (≥ 80 years).

Our study cannot be directly compared with others conducted in different countries due to variations in the cost of living.31 In Europe and the US, the cost of living is 3-4 times higher than ASEAN countries, which corresponds to the higher costs of medical care, including medical personnel, as shown in many studies.10,32 The CGA and MDT service improved the quality of care for older adults by detecting undiagnosed problems, such as cognitive impairment, depression, fall risk, inappropriate medication use and urinary incontinence.33 This highlights the potential benefit of CGA and MDT services in low to middle-income countries, where lower medical care costs can significantly enhance the quality of clinical practice for older adults.

A probabilistic sensitivity analysis was conducted to assess uncertainty, confirming that the CGA and MDT service was more cost-effective than usual care in terms of QALY gained. The acceptability curves indicated that the cost per QALY, from a societal perspective was

approximately $3,052 per QALY, which is lower than the national threshold of $4,564 per QALY.24 Therefore, the CGA and MDT service not only results in societal cost savings but also improves the quality of life for older adults.

The study’s strengths in design contribute to the reliability of these findings, despite certain limitations. The study lies in its prospective design with a follow-up period of up to one year, demonstrating significant clinical and cost outcomes in the Geriatric OPD. Other studies on cost-effectiveness analysis have been retrospective, which can introduce limitations such as recall bias and difficulties in accurately collecting cost data.34 Moreover, previous studies did not find that CGA and MDT services in an OPD setting were cost-saving; they primarily demonstrated clinical effectiveness in providing more palliative care services.5,35

Nevertheless, acknowledging study limitations helps in understanding the scope and generalizability of these results, especially considering pandemic-era data and the unique baseline differences observed between groups. First, the COVID-19 pandemic during the study period affected the number of older adults receiving the MDT service. This could affect the service provision from the non-COVID period. Second, we did not identify the specific causes leading to extra admissions, ER visit and falls. Some causes might not be avoidable even with the CGA and MDT. Third, there were slight difference in baseline characteristics between the 2 groups which might affect the outcomes. The potential confounding variables such as age, income, ADL, illness severity (determined by Charlson Comorbidity Index: CCI) were not significantly different between group. However, some of the illness conditions were different such as dementia, OA knee and recent hip fracture within 3 months. Dementia and OA knee were more prevalent in the CGA & MDT group, while recent hip fracture was more prevalent in the usual care group. These could affect the service need and clinical outcomes. Lastly, as the study was conducted in a single medical school, which is a tertiary hospital in Bangkok Metropolitan with a large number of older adults and MDT experts, generalizing the results nationwide requires caution due to the lack of such expertise in other healthcare settings and different living expenses.

CONCLUSION

This study demonstrates the clinical and economic effectiveness of CGA and MDT services in an outpatient setting, affirming their role as essential components of elderly care for enhancing quality of life and managing

health-related costs. The broader implications of these findings suggest that CGA and MDT services could be beneficial beyond Thailand, serving as a model for aging populations worldwide. By focusing on cost- effectiveness and holistic care, these interventions can help healthcare systems meet the complex needs of older adults, providing sustainable and high-quality care on a global scale. Further research in diverse healthcare settings is needed to refine this model, ensuring that CGA and MDT remain adaptable to the unique challenges of different regions and healthcare infrastructures.

ACKNOWLEDGMENTS

The authors thank facilitators, nurses, computer programmers, research assistants, and all older adults who participated in the present study.

DECLARATION

Grants and Funding Information

This project is not funded by any external source.

Conflict of Interest Statement

The authors have no conflicts of interest to declare.

Author Contributions

Conceptualization and methodology, P.V., S.I., N.T.,

S.M. and W.M. ; Investigation, P.V.; Formal analysis, P.V., N.T., S.M. and W.M. ;Visualization and writing – original draft, P.V., N.T. and S.M.; Writing – review and editing, W.M., N.T. and S.M; Supervision, W.M. All authors have read and agreed to the final version of the manuscript.

Use of artificial intelligence

The manuscript is not produced using artificial intelligence.

Human ethics approval declaration

This study was approved by the Institutional Review Board, Bangkok, Thailand (IRB No. 1057/2563). Written informed consent was obtained from each older adult or their legal representative.

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12. Morley JE, Arai H, Cao L, Dong B, Merchant RA, Vellas B, et al. Integrated care: enhancing the role of the primary health care professional in preventing functional decline: a systematic review. J Am Med Dir Assoc. 2017;18(6):489-94.

13. Ellis G, Whitehead MA, Robinson D, O’Neill D, Langhorne PJB. Comprehensive geriatric assessment for older adults admitted to hospital: meta-analysis of randomised controlled trials. BMJ. 2011;343:d6553.

14. Soejono CH. The impact of’comprehensive geriatric assessment (CGA)’implementation on the effectiveness and cost (CEA) of healthcare in an acute geriatric ward. Acta Med Indones. 2008; 40(1):3-10.

15. Sumonthip P, Boonkerd J, Phrayai N, Permkrietkajorn R. Program evaluation Comprehensive geriatric assessment clinic Satisfaction Older patients. Ramathibodi Nursing Journal. 2013;16(3): 443-55.

16. Stineman MG, Xie D, Pan Q, Kurichi JE, Zhang Z, Saliba D, et al. All‐cause 1‐, 5‐, and 10‐year mortality in elderly people according to activities of daily living stage. J Am Geriatr Soc. 2012;60(3): 485-92.

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‌Reliability and Validity of the Thai Version of the PAINAD Scale: An Extended Application of Pain Assessment in the Moderately Severe Stage of Dementia

Natthapapath Boonsawat, M.D.1,2, Patumporn Suraarunsumrit, M.D.2, Sutisa Pitiyarn, R.N., A.P.N.2, Napaporn Pengsorn, R.N.4, Varalak Srinonprasert, M.D.2, Sahatsa Mandee, M.D.3, Titima Wongviriyawong, M.D.2,*

1Division of Geriatric Medicine, Department of Medicine, Khon Kaen Hospital, Khon Kaen, Thailand, 2Division of Geriatric Medicine, Department of

Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 3Department of Anesthesiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 4Department of Preventive and Social Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

*Corresponding author: Titima Wongviriyawong E-mail: titima.won@mahidol.ac.th

Received 14 October 2024 Revised 1 November 2024 Accepted 14 November 2024 ORCID ID:http://orcid.org/0000-0003-0121-4003 https://doi.org/10.33192/smj.v77i1.271644

All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.

INTRODUCTION

Dementia is a complex syndrome characterised by impairment across multiple cognitive domains, resulting in a progressive decline in daily functioning.1 In addition to cognitive decline, dementia affects behaviour, mood, mental state, and interpersonal relationships.2 In the early stage, people with dementia (PwD) may not need assistance in basic daily activities and can communicate their needs well, but as the disease advances to the severe stage, they usually have limited expression of their needs and are unable to perform daily activities without assistance.3

Pain detection is one of the challenging problems in PwD. Despite the high prevalence of pain up to 50% of people with dementia in hospital settings,4 it is often inadequately identified and managed due to the difficulties in expressing pain,5 resulting in depression, further cognitive and physical decline, increased risk of falls, poor sleep quality, and a reduction in the quality of life of affected individuals.6,7

Pain self-reporting is considered the gold standard for evaluating pain in patients who can express the characteristics and severity of their pain. In people with mild to moderate cognitive impairment, it is suggested that pain can be evaluated by querying their pain using the Numerical Rating Scale or verbal expression.8,9 However, pain assessment in people with severe cognitive impairment using self-report is challenging because of their decreased communication ability. Notwithstanding the difficulty in verbally expressing pain, PwD possibly manifest their pain in non-specific manifestations such as

confusion, agitation, restlessness, irritability, or changes in appetite.10-12

This adversity has led to the development of various pain assessment tools in PwD, based on behavioural observation, including the “Discomfort Scale-Dementia of the Alzheimer’s Type” (DS-DAT), “Checklist of Nonverbal Pain Indicators” (CNPI), “the ABBEY Pain Scale”, “Mobilization-Observation-Behavior-Intensity- Dementia Pain Scale” (MOBID), “Pain Assessment Checklist for Seniors with Limited Ability to Communicate” (PACSLAC), “Pain Assessment in Advanced Dementia” (PAINAD) scale, and Doloplus-2 scale. Among the tools mentioned, the UK National guidelines recommend using the PAINAD and Doloplus-2 scales to assess pain in PwD.9

The PAINAD scale was developed by Warden, et al. to assess pain in PwD. It includes observing individuals in five features: breathing, negative vocalisation, facial expression, body language, and consolability. Each feature is scored on a scale ranging from 0 to 2 based on specifically described characteristics. The scale exhibited good construct validity, strong interrater reliability, and a good correlation with the DS-DAT scale and the Visual Analogue Scale (VAS).13 The PAINAD has shown strong concurrent validity in clinical research, regardless of cognitive status in older adults undergoing hip fracture surgery.14 Additionally, it has demonstrated a high sensitivity of 92% in identifying and detecting pain in older people with severe dementia.15

The PAINAD scale has been translated into multiple languages, including Italian, German, Portuguese, Dutch, Chinese, and Korean.16-22 However, it has not been translated into Thai. Given the absence of an optimal pain assessment tool for individuals with moderate to severe dementia in Thailand, despite the increasing prevalence of dementia among older adults as a result of a rapid transition of the Thai population into a super-aged society within a decade,23 this study aims to assess the reliability and validity of a Thai version of PAINAD (PAINAD-Th) for measuring pain in PwD. Moreover, this study aimed to explore the validity of the PAINAD-Th in delirium superimposed on dementia patients, given the high prevalence of delirium varying between 38–72% in a tertiary hospital setting.24-26

MATERIALS AND METHODS

This study comprised three phases of validity processes carried out at Siriraj Hospital, a large university hospital in Bangkok, Thailand. The study protocol was approved by the Siriraj Institutional Review Board before commencing (Si 560/2019). The process of cross-cultural translation and the evaluation of the validity and reliability of PAINAD- Th involved three distinct phases, as outlined below.27,28 Video recordings were used for training and interrater reliability processes to minimise the disturbance of vulnerable subjects and ascertain that the assessments were based on the exact circumstances.

Phase 1: Translation of PAINAD to a Thai version

In the initial forward-translation step, the original English version of the PAINAD scale was translated into Thai after receiving permission from one of the PAINAD developers, Prof. Ladislav Volicer, by two bilingual geriatricians with Thai mother tongues. Subsequently, a complete translated version was created through consensus between the two translators. A back-translation was then independently undertaken by another translator, who is bilingual in traditional Thai and English and has a master’s degree in linguistics. Subsequently, a team of three subject-matter experts (two geriatricians and one anesthesiologist) reviewed the back-translation and rated each feature from 1–4. Higher scores (3 or 4) indicated closer equivalence to the original version. The content validity index for semantic equivalence to the original version of the PAINAD was then assessed.29 Any uncertainties about the translation were discussed with the back-translator. All features underwent a thorough review to ensure accuracy and grammatical correctness. Subsequently, the final version of the PAINAD-Th scale was attained.

Phase 2: Training process

The two nurses underwent a two-step training process facilitated by a geriatric fellow. Initially, they participated in a one-hour instructional session where they received detailed explanations of each component of the PAINAD-Th scale and were assessed to confirm their comprehension of the tool. Subsequently, each nurse independently practised using the scale while observing the same set of 10 videos. The objective was to sufficiently acquaint the nurses with the patient- observation procedures, enabling them to independently and consistently utilise the PAINAD-Th scale in the later evaluation.

Phase 3: The test of reliability and validity of PAINAD-Th The reliability and validity of the PAINAD-Th scale were assessed through inter-rater reliability, test-retest

reliability, and concurrent validity analyses.

Study design

From September 2019–March 2020, patients aged over 60 who had been admitted to Siriraj Hospital were enrolled in the study if any one of the following conditions were met:

1. they had a prior diagnosis of dementia in their medical records;

2. they had been diagnosed with dementia by a geriatrician on admission or

3. they had an abnormal cognitive assessment30 (namely, a modified Informant Questionnaire on Cognitive Decline in the Elderly score (modified IQCODE)31 ≥ 3.42, a Thai Mental State Examination score (TMSE)32 < 24, or a Montreal Cognitive Assessment score(MoCA)33 < 25).

After the dementia patients were identified, the geriatric fellow assessed the severity of dementia using the Functional Assessment Staging Test (FAST)34 in order to enrol patients with a moderately severe or severe stage of dementia (FAST stage 6 and 7). The family members or guardians of patients were informed about the research aims and procedures, including video recordings, and then informed consent was obtained. Patients were excluded if they were comatose or quadriplegic, had severe sepsis or septic shock,35 or had been admitted to an intensive care unit.

On the initial assessment, baseline characteristics were collected and assessed by the geriatric fellow. These included age, sex, comorbidities, the Barthel Index,36 for assessing basic activities of daily living, FAST stage for dementia, and the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) classification for

delirium.1 The delirium diagnosis made by the geriatric fellow had previously demonstrated a substantial agreement with an experienced geriatrician with Cohen’s kappa coefficient of 0.783.

Pain diagnosis reference standard

A researcher recorded videos of each participant for two episodes, each for a 5-minute duration. The first record, labelled as “activity”, was captured during an activity that could provoke pain, such as wound dressing, bed-bathing, or physical therapy session, while the second one, labelled as “rest”, was recorded while the patient was at rest. Two geriatricians who were unaware of the scoring of the PAINAD-Th established a comprehensive pain assessment as a reference standard by reviewing the participants’ medical histories from electronic medical records and inpatient documents, including potential sources of pain, and then used a Visual Analogue Scale (VAS)37 to assess the participants’ pain levels based on their behaviour in the activity and rest videos, given the participants were unable to communicate their pain accurately.

Determination of PAINAD-Th reliability

The primary outcomes included assessing the reliability and validity of PAINAD-Th for measuring pain in PwD in moderately severe to severe stages. To test inter-rater reliability, two trained nurses independently evaluated the participants’ pain using PAINAD-Th by observing the same sets of video records. One week later, the rating process was reproduced to investigate the test-retest reliability of PAINAD-Th. Concurrent validity was investigated by evaluating it against the VAS assessment by the geriatricians.

Statistical analysis

Thesamplesizecalculationforexploringtheconcurrent validity of PAINAD-Th was based on the previous study reporting a moderate correlation (correlation coefficient; r=0.65) of translated PAINAD (Italian version) with the Visual Rating scale.16 Our study expected the lowest value that still represents a moderate correlation (r=0.4–0.69),38 thus, the correlation coefficient of 0.4 was used to estimate the sample size, given an acceptable significant level of 5% (p=0.05) with a power of 80% and a 20% dropout rate; the calculated sample size was 57.

Demographic data for categorical variables were reported as percentages. For continuous variables, data were presented as means with standard deviations for parametric data, and medians with interquartile ranges for non-parametric data. The content validity index

was used to determine the semantic equivalence to the original PAINAD scale by summing the percentages of agreement of all items given a rating of 3 or 4 by the expert committee. Intraclass correlation coefficients (ICCs) were analyzed for inter-rater reliability using a two-way mixed-effects model with absolute agreement type and for test-retest reliability using a two-way mixed-effects model with consistency type.39,40 The concurrent validity of PAINAD-Th compared to the reference standard was analyzed using Spearman’s rank correlation coefficient, due to the non-parametric nature of the data. Analyses were conducted using PASW Statistics for Windows (version 18.0; SPSS Inc., Chicago, Ill., USA).

RESULTS

Baseline characteristics

A total of 60 participants were enrolled in the study, with a mean age of 84.7 ± 7.1 years. In total, 120 video recordings were obtained. Women comprised 66.7% of the sample, with the majority (60%) diagnosed with Alzheimer’s disease. Approximately two-thirds of the participants were in the moderately severe stage of dementia. The most common diagnosis associated with painful conditions was fractures, accounting for 38.3% of cases. Delirium was present in 23.3% of participants, with hypoactive delirium being the most prevalent subtype. Characteristics of the included participants are outlined in Table 1.

Content validity index

The content validity indices for the semantic equivalence were 1.00 for the forward translation and

0.93 for the back translations.

Concurrent validity

The concurrent validity of the PAINAD-Th at rest demonstrated strong correlation coefficients (rs), ranging from 0.854 to 0.943, with a p-value <0.001. During activity, the correlation coefficients (rs) ranged from 0.897 to 0.904, also with a p-value <0.001 (Table 2). Subgroup analyses were conducted to assess concurrent validity across different dementia stages and based on the presence of delirium. The results indicated a slightly stronger correlation with the reference standard in the severe stage compared to the moderately severe stage. In participants without delirium, the PAINAD-Th exhibited a very strong correlation with the reference standard (Table 2).

Inter-rater reliability and test-retest reliability

Concerning inter-rater reliability, the ICCs for the

FAST stage, n (%)

Stage 6, moderately severe

TABLE 1. Baseline characteristics. (continue)

B

Delirium, n (%)

Note: a Age-unadjusted Charlson comorbidity index

TABLE 2. Concurrent validity: the correlation between the VAS (reference standard) and the PAINAD-Th.

Abbreviation: VAS, Visual Analogue Scale Note: all p-value <0.001

total PAINAD-Th scores were 0.937 (activity stage) and 0.955 (rest stage). At rest, each item showed a moderate- to-good ICC, ranging between 0.691 and 0.818. The ICCs for the activity stage also showed moderate-to- good ICCs of 0.671 to 0.861 (Table 3). The test-retest reliabilities for the total scores were good to excellent

(ICCs of 0.880 to 0.964). When examining each feature, the ICCs generally showed good reliabilities, except for a few features that displayed moderate reliabilities. These include the breathing feature assessed during the activity stage, and the body language feature assessed both in the rest stage and during the activity stage (Table 4).

TABLE 3. Inter-rater reliability for each feature and total score.

TABLE 4. Test-retest reliability for each feature and total score.

DISCUSSION

This study demonstrated good validity and reliability of the PAINAD-Th scale for pain assessments among patients with moderately severe or severe dementia. The result was consistent with previous studies.13,16-21 The content validity indices of the PAINAD-Th, as evaluated by experts, demonstrated high scores, signifying semantic equivalence to the original version and suitability for implementation in a Thai context. The concurrent validity of the PAINAD-Th, evaluated by comparing the results against the VAS determined by the two geriatricians, showed an excellent correlation. This result was similar to a study by Warden, et al.,13 which was tested against the VAS and was slightly higher than that of D. Costardi, et al.16 The strong correlation may be influenced by the comprehensive pain assessments by an expert committee across multiple domains. This includes observing the participant’s body language, facial expressions, and pain-indicating vocalizations, all of which may partly resemble those of the PAINAD-Th features. Regarding pain-indicating vocalizations assessed by the expert committee, some of the PwD may be able to accurately report their pain verbally, even in moderate to severe stages,41,42 which could correspond to an observational comprehensive assessment of pain recommended for individuals with severe dementia.43

In this study, the use of PAINAD-Th also effectively measured pain in patients with dementia in their moderately severe and severe stages, addressing the gap left by previous studies that focused only on patients in the severe stage.13,16-21 Additionally, the PAINAD-Th scale accurately identified pain in both resting and active stages.

We also observed that the assessment of the breathing feature during activity demonstrated lower inter-rater reliability and test-retest reliability compared to other features, which is consistent with the previous study.13 The findings may be attributed to the difficulty of accurately assessing breathing patterns through video recordings when PwD could have altered respiratory pathology, leading to apnea or breathing dysrhythmias.44,45 Besides, Cheyne-Stokes respiration may not be a specific indicator of pain, as this pattern is commonly seen in patients with unstable central respiratory control, such as those with stroke and heart failure.46 As a result, the variation of breathing patterns in PwD could perplex the rating of the breathing feature.

Despite the discrepancy in each feature score between the two raters, the decision to proceed with further management was based on the total score rather than each feature. It is important to note that the lower

agreement on each feature may not diminish the overall rating result.

Our study demonstrated that the PAINAD-Th effectively evaluated pain in PwD who also experienced delirium. The data revealed a strong correlation between the PAINAD-Th scores and the established reference standards, suggesting that this tool is reliable in complex clinical situations, such as acute care settings where delirium is frequently encountered.24,25 Although the correlation was slightly reduced in PwD with delirium compared to those without, this discrepancy likely stems from the inherent challenges of assessing pain in delirious patients. Delirium often manifests with various symptoms, such as disorganized thinking, perceptual disturbances, and inattention, that can obscure the accurate interpretation of pain-related behaviours. For example, negative vocalizations may not necessarily indicate pain but could reflect other unmet needs, making it difficult to differentiate. However, considering that pain is a well-documented precipitating factor for delirium47, the availability of a tool like the PAINAD-Th, which can capture pain signals even in these complex cases, is crucial for ensuring timely and effective clinical interventions. The test’s ability to operate reliably in such challenging contexts underscores its value in managing pain in PwD, particularly in settings where delirium is a common complicating factor.

This study presents both strengths and limitations that should be recognized. A key strength was the methodology employed to assess test-retest reliability, inter-rater reliability, and concurrent validity. Geriatricians and nurses observed the same set of video recordings, enabling direct comparison of the pain ratings provided by nurses against the reference standard values determined by geriatricians, without any interval between assessments. This approach ensured consistency and robustness in evaluating the tool’s validity. Additionally, the study demonstrated that pain assessment using the PAINAD-Th could be effectively conducted after a one-hour training session. It is plausible that further competency could be achieved through more extensive training or supplementary self- learning resources, which may enhance understanding of the tool. This could serve as a framework for the tool’s integration into daily clinical practice and support its feasibility for use by non-specialist personnel.

However, several limitations must be acknowledged. A primary limitation is that patient assessments were conducted via video recordings, while in clinical settings, pain assessments are typically performed in person, allowing for a more comprehensive and time-sensitive evaluation. Furthermore, the validity of the reference

standard could be strengthened by confirming the resolution of symptoms following pain relief, thereby providing additional verification of the tool’s accuracy in identifying pain.

Another limitation is that we did not account for behavioural and psychological symptoms of dementia (BPSD) diagnoses prior to the reference-standard pain assessment. BPSD is highly prevalent, affecting up to 90% of PwD,48,49 and includes a variety of manifestations, such as agitation, anxiety, irritability, and abnormal vocalization. These symptoms may contribute to the overdiagnosis of pain by the reference standard, as certain behavioural cues assessed by the PAINAD-Th scale can overlap with features of BPSD. This overlap could lead to a high correlation between the reference standard and the PAINAD-Th scale.

However, it is important to note that BPSD is often triggered by unmet needs such as pain, hunger, toileting, or communication difficulties. Thus, diagnosing and addressing potential pain may be more beneficial than overlooking it, given the significant impact untreated pain can have on the quality of life in PwD.

CONCLUSION

The PAINAD-Th is an effective tool for assessing pain in people with dementia, regardless of the presence of delirium. Compared to the standard reference, it has demonstrated good-to-excellent content validity, concurrent validity, inter-rater reliability, and test-retest reliability. Furthermore, its utility extends not only to severe dementia cases but also to moderately severe stages.

ACKNOWLEDGEMENTS

We extend our gratitude to Mrs. Nipaporn Sangarunakul for her invaluable administrative support.

DECLARATION

Grants and Funding Information

This research was supported by the Siriraj Research Fund (R 016231064), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

Conflict of Interest

The authors declare no conflict of interest.

Author Contributions

Conceptualisation and methodology, T.W., N.B., P.S., and V.S.; Investigation, N.B., S.P., N.P., S.M., P.S.,

T.W.; Formal analysis, N.B., T.W.; Visualization and writing – original draft, N.B.; Writing – review and

editing, T.W., V.S.; Funding acquisition, N.B., T.W.; Supervision, T.W. All authors have read and agreed to the final version of the manuscript.

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‌Outcomes of Robot-assisted Radical Prostatectomy in Men Aged 75 Years Old or Older: A Single-center Study in Thailand

Attapol Mahalelakul, M.D., Pubordee Assavavirojekul, M.D., Sunai Leewansangtong, M.D., Varat Woranisarakul, M.D., Thitipat Hansomwong, M.D., Sittiporn Srinualnad, M.D.*

Division of Urology, Department of Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

*Corresponding author: Sittiporn Srinualnad E-mail: sitsrinualnad@gmail.com

Received 28 September 2024 Revised 24 October 2024 Accepted 1 November 2024 ORCID ID:http://orcid.org/0000-0002-5118-7675 https://doi.org/10.33192/smj.v77i1.271301

All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.

INTRODUCTION

Prostate cancer (PCa) is the second most frequent cancer and the fifth leading cause of cancer-related death among men in 2022.1 In Thailand, it is the fourth most common cancer in men.2 According to WHO data from 2020, the life expectancy of Thai males at birth is 74.4 years, with a life expectancy of 22.8 years at age 603, and these figures are increasing annually. For urologists, this growing trend of reduced mortality in the elderly population presents challenges in choosing appropriate treatment options, such as radical prostatectomy (RP), radiation, or androgen deprivation therapy (ADT).

Previous studies have shown that elderly patients with PCa often present with more aggressive and locally advanced tumors.4 Therefore, it is crucial for urologists to offer active treatment to selected elderly patients, as some may experience local tumor invasion or systemic metastasis. Robot-assisted radical prostatectomy (RARP), first performed in 2000, has demonstrated better outcomes and safety profiles compared to open RP5,6, especially when combined with some surgical techniques and preoperative MRI.7,8 Additionally, this approach spares patients from the systemic effects associated with ADT, which is commonly administered alongside radiation therapy in patients with unfavorable or high-risk PCa. However, the upper age limit for RP as a curative treatment for localized PCa remains a topic of debate.

The aim of this study was to evaluate the surgical and oncological outcomes, as well as complications, in men aged 75 years old or older who have undergone RARP.

MATERIALS AND METHODS

This retrospective cohort study was conducted at the Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok. The study proposal was approved by the Siriraj Institutional Review Board of the Faculty of Medicine Siriraj Hospital, Mahidol University (272/2565(IRB4)). From July 2018 to December 2020, the records of

557 patients with PCa who had underwent RARP were reviewed. Patients were divided into two groups: those younger than 75 years old and those aged 75 years or older. Both groups were analyzed for assessing their preoperative characteristics, which included body mass index (BMI), American Society of Anesthesiologists classification (ASA), prior prostatic surgery, BPH medication use, prostate specific antigen (PSA), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR). Perioperative characteristics included operative time, neurovascular bundle (NVB) sparing, blood loss, and prostatic weight. Postoperative characteristics included Gleason score, pathological stage, surgical margin status, complications (classified by Clavien–Dindo), length of postoperative hospital stay, and postoperative PSA level. All the patients were followed up with serum PSA measurements every 3 months after the surgery. Biochemical recurrence (BCR) within one year was defined as a PSA

level of 0.2 ng/ml or higher.

Sample size was calculated based on the research by Burkhard Ubrig (2018), we estimated that in the group of prostate cancer patients who underwent RARP at Siriraj Hospital, those aged 75 years and older, as well as those younger than 75 years, will have a biochemical recurrence

rate after one year of follow-up of approximately 25.0% and 10.0%, respectively. We established the ratio (n2/ n1) of prostate cancer patients aged 75 years and older (n1) to those younger than 75 years (n2) as 7/1, or a ratio of 7. Given a two-sided Type I error (α) of 0.05 and a power of the test of 80%, the required sample size for prostate cancer patients aged 75 years and older (n1) is at least 57 cases, while for those younger than 75 years (n2) it is at least 398 cases, totaling 455 cases overall.

Statistical analysis was performed using SPSS statistics version 23 (IBM Corp, Armonk, NY, USA). Demographic data were presented according to the distribution of quantitative variables: the mean ± standard deviation for normally distributed variables and median with interquartile range for non-normally distributed variables. T-tests were used to compare continuous values between two groups. For binary variables, the chi-square test was used. Multivariate analyses were conducted to identify significant predictors of BCR. A p-value < 0.05 was considered statistically significant.

RESULTS

Patients were divided into two groups: those younger than 75 years old (n=398) and those aged 75 years or older (n=57) (Fig 1). RARP was performed using the Da Vinci Robotic 4-Arm system with a transperitoneal approach. Pelvic lymph node dissection was performed in the majority of cases, with the extent of dissection determined at the surgeon’s discretion.

Preoperative characteristics of the two groups are shown in Table 1. The mean age in the group aged <75 was

67 years old (63–70), compared to 77 years old (75–79) in the group aged ≥75 years. The percentage of patients with ASA class 3 was higher in the older group (35% vs. 23.4%). BPH medication use was also significantly higher in the elderly group (63.2% vs. 39.4%). Both the neutrophil-to-lymphocyte ratio (NLR) and platelet-to- lymphocyte ratio (PLR) were significantly lower in the older group. The median PSA levels were not significantly different between the two groups.

The perioperative and postoperative characteristics are displayed in Table 2. The non-NVB sparing technique was more commonly performed in the older group, with a significantly higher rate compared to the younger group (89.5% vs. 51.5%, p < 0.05). Prostate size was significantly larger in the older group. Similarly, pathological T-staging was more advanced in the older group, with 64.9% classified as pT3 compared to 48.7% in the younger group. The proportion of patients with a high Gleason grade group (4 and 5) was also higher in the older group (41.3% vs. 25.1%). The operative time was not significantly different between the two groups (160 min vs. 165 min, p = 0.82), nor was blood loss (250 ml vs. 200 ml, p

= 0.38). Despite the higher prevalence of aggressive pathological features in the older group, there were no significant differences in surgical margin, pelvic node involvement, or postoperative complications between the two groups. The majority of patients in both groups did not experience postoperative complications. However, 8 patients (2%) in the younger group and 3 patients (5.3%) in the older group experienced Clavien–Dindo grade 3 complications.

Fig 1. Patient selection.

Abbreviations: NLR = Neutrophil-Lymphocyte ratio, PLR = Platelet-Lymphocyte ratio

The duration of hospitalization was not significantly different between the two groups. BCR at one year was higher in the older group (10.3% vs. 17.5%), but this difference was not statistically significant (p = 0.1).

Multivariate analysis revealed that preoperative PSA of 15 or higher, higher Gleason grade group, and positive surgical margin were significantly associated with BCR (Table 3).

DISCUSSION

As life expectancy for men continues to increase, a larger proportion of elderly patients are being diagnosed with clinically significant PCa, with many potentially having a life expectancy extending beyond 10 years. Careful selection of candidates for surgical intervention for PCa among the elderly is therefore crucial. While a minimum life expectancy of 10 years is typically deemed necessary when considering potentially curative therapy, many urologists refrain from pursuing definitive treatment for localized PCa in elderly patients based solely on age, without considering their overall life expectancy. There is extensive literature on the oncological outcomes of RP in patients aged 65 years old or older, or 70 years old and older.9,10 However, only a limited number of studies have specifically examined oncological outcomes for men aged 75 years old and above.11,12

Previous studies have shown that older patients undergoing RARP often present with higher pathological stages, Gleason scores, and PSM rates. Similarly, the older group in our study exhibited higher histological and staging characteristics compared to the younger cohort, with 64% of older patients having pT3 disease. Interestingly, while the PSM rate was lower in the older group, the difference was not statistically significant. Previous research has highlighted a strong correlation between PSM and recurrence of PCa. Yang et al.13 identified an association of PSM, GG 4 to 5, pT3, and PSA levels greater than 10 ng/ml, reporting a 5-year BCR rate of 66.7%. Consistent with their findings, our multivariate analysis emphasized the importance of PSM in predicting BCR, while age did not predict BCR. This suggests that RARP is a viable option for selected older patients, offering comparable short-term oncological outcomes to younger adults, even when presenting with slightly more advanced disease.

Physical status and cognitive function are crucial predictors of postoperative outcomes. The Mini-Cog and G-8 screening tools14 are recommended for comprehensive preoperative assessment in urological cancers, including RARP. In our study, the majority of older patients were classified as ASA class 2. Complications rates, as classified by the CDC, did not differ significantly between the groups,

TABLE 2. Perioperative and Postoperative outcomes.

*Clavien-Dindo classification

TABLE 3. Multivariate analysis showing predictors of post-operative BCR in both groups.

with 21% of older patients experiencing postoperative complications (5.3% with grade 3 complications versus 2% in the younger group). These results align with a study by Ubrig et al.15, which reported minor complications in 26.3% of patients over 75 years undergoing RARP, with major complications occurring in only 1.3% of cases. These findings underscore the importance of comprehensive preoperative evaluation and the integration of validated tools for patients undergoing RARP.

Frailty, a condition marked by reduced physiological reserves and impaired function across multiple systems, leads to a diminished capacity for the body to respond to stress. Systemic inflammation is a key contributor to physical decline and frailty in older adults. Meta-analyses have shown that frailty and pre-frailty are associated with elevated levels of serum inflammatory markers. The NLR and PLR are emerging biomarkers of inflammation. Previous studies have found that declines in physical function and frailty are associated with higher NLR and PLR in elderly patients.16-19 Moreover, several studies have confirmed that these novel markers are linked to cancer progression and prognosis. In our study, both NLR and PLR were significantly lower in the older group, although their relevance to the 1-year BCR was not established. Additionally, a large population-based study in China by Meng et al.20 reported variations in inflammatory biomarkers, including NLR and PLR, across different age groups, with higher values observed in men older than 65 years (NLR: 1.71 vs. 1.85, PLR: 106 vs.139). This suggests a potential selection bias, as healthier older adults may be more likely to undergo RARP. Research into the impact of NLR and PLR in the Thai population remains limited. However, a study by Veerakulwatana et al.21 found no association between NLR or PLR levels and 30-day major complications following radical cystectomy, a more aggressive procedure than RARP.

PSA has been used for detection of recurrent disease. The American Urological Association (AUA) and the European Association of Urology (EAU) have recommended defining BCR as a serum PSA ≥0.2ng/mL followed by a second confirmatory level.22,23 Approximately 20-40% of patients with clinically localized PCa will present BCR after RP.24,25 Short time from RP to BCR has also been associated with poor clinical prognosis. Ten-year rate of systemic progression for PCa was 10% for patients who experienced BCR more than six years after RP, compared to 19% for those with BCR occurring less than

1.2 years after RP.26 Therefore, we have chosen to conduct follow-up on BCR for one year and from our study BCR at one year was higher in the older group (10.3% vs. 17.5%), but this difference was not statistically significant (p = 0.1).

Recent studies have shown that elderly patients often exhibit more aggressive pathological findings, which align with the results of our own research. As such, there are potential benefits to performing RARP in selected patients aged 75 years and older, as they may achieve surgical and oncological outcomes comparable to those of younger patients. Therefore, age should not be considered a contraindication for surgical intervention.

However, there are several limitations of our study to note. First, this study involved a retrospective analysis, therefore it was restricted by the available evidence level. Second, our results might not be representative for all men over 75 years old because our cohort involved a highly selected group of patients. Third, our follow-up duration was too short to show biochemical, cancer-specific, and overall survival. Finally, there may be potential bias from the surgeons’ experience.

ACKNOWLEDGEMENTS

The authors would like to thank Ms. Jitsiri Chaiyatho and all coordinators of the Siriraj Hospital for their important contributions to this study.

DECLARATION

Grants and Funding Information

There are no sources of funding to disclose.

Conflict of Interest

The authors declare that they have no conflicts of interest.

Author Contributions

Conceptualization and methodology, S.S, A.M. and T.H. ; Investigation, S.S., T.H., V.W., S.L. and P.A. ; Formal analysis, S.S. and A.M. ; Visualization and writing – original draft, A.M. ; Writing – review and editing, S.S., A.M. and T.H. ; Supervision, S.S. All authors have read and agreed to the final version of the manuscript.

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26. Boorjian SA, Thompson RH, Tollefson MK, Rangel LJ, Bergstralh EJ, Blute ML, et al. Long-term risk of clinical progression after biochemical recurrence following radical prostatectomy: the impact of time from surgery to recurrence. Eur Urol. 2011; 59(6):893-9.

‌Validation of Self-application-based Malnutrition and Limited Mobility Screening Tools Compared with Standard Diagnostic Tools in Older Adults

Panvadee Tanaviboon, M.D.1, Weerasak Muangpaisan, M.D. 2,3, Angkana Jongsawadipatana, M.Sc.2, Pitiporn Siritipakorn, M.N.S .2, Somboon Intalapaporn, M.D.2,*

1Division of Geriatric Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 2Division

of Geriatrics, Department of Preventive and Social Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 3Siriraj Academic Center of Geriatric Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand

*Corresponding author: Somboon Intalapaporn E-mail: sintalapaporn@gmail.com

Received 21 October 2024 Revised 23 November 2024 Accepted 23 November 2024 ORCID ID:http://orcid.org/0009-0005-3714-0562 https://doi.org/10.33192/smj.v77i1.271719

All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.

INTRODUCTION

Populations worldwide are transitioning toward an aging society, and the trend is rapidly increasing. In October 2017, the World Health Organization (WHO) released “Integrated care for older people: Guidelines on community-level interventions to manage declines in intrinsic capacity”.1 The guidelines include care for various aspects of intrinsic capacity, including vitality, locomotor, psychological, visual, hearing, and cognitive capacity.1

“Vitality” refers to the physiological factors related to locomotor capacity, encompassing balance and energy expenditure within the body. One significant factor contributing to reduced vitality among older adults is malnutrition,1,3 a problem affecting up to 10% of the population aged 65 and above;2 its impact on quality of life is substantial and affects disability rates, hospitalization duration, mortality rates, and healthcare costs.3-4

Locomotor capacity refers to an individual’s physical ability to move from one place to another. Mobility is a crucial factor in healthy aging, developing disability, and preventing dependence on others.1 Limited mobility is common among older adults, leading to difficulties in movement, cognitive decline, and social issues. Additionally, limited mobility can result in dependency, disabilities, physical injuries, hospitalization, and an increased length of stay.11,12 Screening for limited mobility and providing care to improve flexibility are essential for achieving a good quality of life.1

As mentioned, assessing nutritional status and locomotor capacity is crucial. Early screening for malnutrition and limited mobility, followed by prompt assessment and treatment, can lead to positive outcomes.1 Screening tools should be rapid, user-friendly, cost-effective, standardized, and valid.5 Various types of screening tools have been developed to assess intrinsic capacity; however, they have limitations such as the need for face-to-face assessments, time-consuming procedures, and difficulty reaching individuals who are far away and cannot easily access healthcare facilities. Furthermore, many tests require long evaluation times. For example, the SPPB assessment takes an average of approximately 10–15 minutes.11 In the present era of advanced medical technology, electronic applications are being increasingly used for screening to assess nutritional status more effectively. The benefits include remote access without the need to visit a hospital, which is particularly advantageous during the COVID-19 pandemic, as it helps reduce face-to-face contact. Researchers have aimed to develop electronic applications to screen for malnutrition and limited mobility among Thai older adults, thus increasing the chance of accessing diagnostic tests and interventions to improve their physical capabilities. Moreover, if malnutrition or decreased mobility is detected, basic self-care instructions and guidance on seeking medical attention at hospitals, especially for high-risk individuals, are provided. However, tool development requires validity evaluation and possibility of self-screening.

MATERIALS AND METHODS

This research was approved by the Ethics Committee for Research in Human Subjects, Faculty of Medicine, Siriraj Hospital, Mahidol University, Thailand. The approval number is 344/2566 (IRB3). The certificate of approval is Si 463/2023. This study was subsequently conducted from 2023–2024 and is classified as observational clinical research (diagnostic research). The older adults who came to Siriraj Hospital, the quaternary care medical center in Thailand, were randomly selected using the consecutive sampling method. Researchers conducted patient screening using the Eligibility Criteria Checklist before obtaining consent from participants or their relatives.

The inclusion criteria included outpatients aged 60 and older who could communicate, read Thai and answer questions on mobile or tablet applications. Exclusion criteria included those with visual or hearing impairments that impeded the application or standard tests, disabilities affecting the use of the application or SPPB, and dyspnea (functional classes III–IV). Individuals who requested not to be contacted or do not wish to disclose their medical records were excluded, as were those with prior evidence of severe neuropsychiatric diseases affecting communication, such as severe dementia with behavioral and psychological symptoms of dementia (BPSD) or schizophrenia. Inpatient older adults were also excluded. Participants or their legal representatives had the right to withdraw from the research at any time without consequences; this ensured that participation was voluntary and that participants could drop out at their discretion. Additionally, participants who did not cooperate in completing the questionnaire or testing via electronic tools or the standard test were excluded from the study.

All participants were provided with detailed explanations and asked for consent before they participated in the study. General patient information, including sex, age, occupation, level of education, primary caregiver, preexisting conditions, current medications, history of alcohol consumption, history of surgery, history of hearing and vision impairment, oral health status and denture usage, functional status, physical activity, history of falling, gait aid usage, and oral nutritional supplementation, was also collected from the electronic medical record system and self-reporting. Participants underwent screening for malnutrition and mobility impairment via application screening tools, with participants using the tools themselves; afterward, trained medical personnel evaluated them for the MNA and SPPB. The user satisfaction and experience were also investigated. Statistical analysis was conducted

on all collected data. Appendix: Figure 1 illustrates the flow chart of the validation process.

Malnutrition

Standard tool: The current gold standard for diagnosing malnutrition is the GLIM criteria, which comprises screening and assessment of nutritional status.9 According to the MaNuEL study, the MNA can be used as a standard reference tool for evaluating the validity of nutritional screening instruments;6,8 these are considered ‘semigold’ reference standards and can be used as substitutes for the gold standard in certain cases, such as for measuring changes in body composition.6 The full form of the Mini Nutritional Assessment (MNA)10,19 comprises both screening and assessment components for nutritional status, including measurements via anthropometry;5 notably, it bears similarities to the GLIM criteria used for diagnosing malnutrition.10 Additionally, various studies have shown that the MNA performs well in community-dwelling older adults.5,8,10 Consequently, researchers have chosen to utilize the MNA to assess the validity of electronic screening programs for at-risk malnutrition in elderly individuals. The cutoff point is below 24 points.

Screening tool: We use a tool that is simple and concise, making it easy for older adults to use. To screen for at-risk malnutrition, we used the WHO-ICOPE 2 questions (unintentional weight loss >3 kg over the last 3 months, OR appetite loss).1 Appendix: Figure 2 illustrates the self-application-based malnutrition screening tool. In previous trials when we developed this tool, there were limited data of its validity, but now there is a study published. However, the study was not in application- based self-assessment and has never been conducted in Thailand. In a cross-sectional study of the ICOPE screening tool in China, the sensitivity was 51.3%. However, the specificity was 94.7%, which indicates a high validity. When included a BMI below 20 kg/m2 provided better sensitivity.6 Thus, we included BMI in the application and separated the calculation of the statistic of whether or not to include BMI. The screening was considered positive when the participant answered yes to one of the two questions.

Locomotor capacity impairment (Limited mobility) Standard tool: Several tools have been used to evaluate senior people’s mobility and balance.11,20-22 However, there is currently no clear consensus on which tool should be the primary assessment method, depending on the aspect that we want to evaluate.11 The SPPB is a tool used to assess gait, balance, and endurance in older adults,

both in research and clinical settings.26 The SPPB can predict disability, falls, activities of daily living (ADL), limited mobility, and hospitalization rates.10,25 Studies have consistently reported that the SPPB is accurate and reliable for assessing mobility capacity in older adults across various environments, with minimal environmental impact on measurement reliability.13-14 Researchers use the SPPB as a standard assessment tool for evaluating the validity of electronic screening programs for limited mobility. A cutoff of less than 10 points is used to detect locomotor capacity impairment or limited mobility.

Screening tool: To screen for limited mobility or locomotor capacity impairment that causes an increase in fall risk, we used the first-step 3-key questions of the STEADI algorithm (feel unsteady when standing or walking, worry about falling, or have fallen in the past year).35,36 In the prospective cohort study of older adults living in Nakhon Ratchasima, Thailand, the sensitivity of the first step 3-key questions by clinicians was 93.9%, and the specificity was 88%.37 The screening was considered positive when the participant answered yes to one of the three questions. Appendix: Figure 3 illustrates the self-application-based limited mobility screening tool (limited mobility).

User acceptance testing

We conducted interviews with participants to rate the application in terms of two aspects: ease of understanding and confidence in the use of the application. For ease of understanding, the participants rated the application on a scale of 1- to 5, with 1 being poor, 2 being fair, 3 being average, 4 being good, and 5 being excellent. Similarly, for their confidence in using the application by themselves, the participants provided ratings on the same 1- to 5 scale, indicating their level of confidence from poor to excellent. These ratings provided valuable insights into the user experience and overall satisfaction with the application.

Sample size calculation

Tool: Self-application-based malnutrition screening

tool.

The sample size for this study was calculated based on the sensitivity and specificity values obtained from previous studies. Screening for malnutrition has demonstrated a sensitivity of 73% and a specificity of 84%.23 The pooled prevalence of at-risk malnutrition is reported to be 42.6%.24 To estimate the required sample size for each group, the principle of estimating a single proportion with a margin of error (d=0.10) is applied. This method ensures that the sample size is sufficient

to accurately reflect the sensitivity and specificity of the malnutrition screening tool within an acceptable margin of error. Therefore, the estimated total sample size required for at-risk malnutrition in this study was 178 participants.

Tool: Self-application-based limited mobility screening tool.

The sample size for locomotor capacity impairment was calculated based on the sensitivity and specificity of the ICOPE tool from previous studies. For individuals with limited mobility, the ICOPE tool has shown a sensitivity of 85% and a specificity of 92.8%, with a prevalence of limited mobility of 35%.25 To calculate the required sample size for each group, the principle of estimating a single proportion with a margin of error (d=0.10) was applied. The estimated total sample size required for the study was 140 participants.

Thus, the total sample size was initially calculated as 178 participants. A possible 5% data loss rate must be taken into consideration when adjusting the sample size. Consequently, an adjusted total sample size of 187 participants was needed for the investigation.

Statistical analysis

We analyzed the outcome measurements for this study to confirm the validity of the application screening tools in detecting malnutrition and locomotor capacity impairment, comparing them with the standard tools MNA and SPPB. We present descriptive data in terms of percentages, means, and standard deviations to provide participant demographic data. The validity of the self- application-based malnutrition and limited mobility screening tools was evaluated by sensitivity, specificity, positive and negative predictive values, and likelihood ratios. The accuracy was also investigated. User satisfaction and experience were assessed by analyzing participants’ ratings of easy understanding of and confidence in their use of the application. We reported these ratings as percentages. The data were analyzed using SPSS version

18.0 (SPSS Inc., PASW Statistics for Windows, Chicago, IL, USA).

RESULTS

A total of 187 people participated in the study (mean age, 69.8±7 years). Appendix: Figure 4 illustrates the age distribution of the participants. Thirty (16%) patients were diagnosed with at-risk malnutrition by the MNA, and 35 (18.7%) were diagnosed with limited mobility by the SPPB. The baseline characteristics are described in the Table 1 & 2. The validity of the application for

TABLE 1. Demographic data: Nutritional status.

detecting malnutrition and limited mobility is shown in the Table 3. Validation of the application of Malnutrition compared with that of the MNA. If a BMI < 20, which is used for diagnosing malnutrition in older adults, was included in the application, the sensitivity and specificity increased to 100% and 81.5%, respectively. When the ROC curve was used to find the best cutoff point, a BMI of 19.38 provided the best results. For limited mobility applications that use the first-step 3-key questions of the STEADI algorithm, the sensitivity and specificity were 94.2% and 76.3%, respectively. For each question, “feeling unsteady when standing or walking” yields the best result. Table 4 shows the validation of the limited mobility application compared with SPPB.

In terms of user satisfaction and experience, the participants rated the application for easy understanding

as “excellent” 65%, “good” 32.5%, or “average” 2.5%. They rated their confidence in their ability to use the application by themselves as “excellent” 70%, “good” 25%, or “average” 5%. The time to complete the application averaged less than 2 minutes. Appendix: Figure 5 illustrates user satisfaction with the application (easily understanding point, %), Appendix: Figure 6 illustrates user satisfaction with the application (confidence in their ability to use the application by themselves, %).

DISCUSSION

To date, few studies have included mobile or tablet applications in the process of screening for malnutrition or limited mobility in Thai older adults. To the best of our knowledge, this is the first study using the 2-questions of the WHO-ICOPE and the first step 3-key questions

TABLE 2. Demographic data: Locomotor capacity.

TABLE 3. Validation of the malnutrition application compared with the MNA.

Abbreviations: Malnutrition App. = Malnutrition application, MNA = Mini Nutritional Assessment, PPV = Positive predictive value, NPV

= Negative predictive value, LR+ = Positive likelihood ratio, LR- = Negative likelihood ratio

TABLE 4. Validation of the limited mobility application compared with the SPPB.

Abbreviations: Locomotor App. = Limited mobility application, SPPB = Short Physical Performance Battery Test, Q1 = Has fallen in the past year?, Q2 = Feels unsteady when standing or walking?, Q3 = Worries about falling?, PPV = Positive predictive values, NPV = Negative predictive values, LR+ = Positive likelihood ratios, LR- = Negative likelihood ratios

of the STEADI algorithm for screening for malnutrition and locomotor capacity impairment via application by self-screening, respectively. The questions are simple and short; thus, they are appropriate for older adults. The majority of the participants reported their high satisfaction with the application rated their excellent confidence in their ability to use the application by themselves.

In terms of baseline characteristics, there were more females than males, with a ratio of 2:1. This proportion may be higher than that of the general older adult population.33 Approximately 16% of participants were diagnosed with at-risk malnutrition according to the MNA, which is lower than the pooled prevalence of at-risk malnutrition in Thai older adults as assessed by the MNA.24 Similarly, when compared with the health survey of monks in the Bangkok Noi area of Bangkok, the monks exhibited a higher prevalence of elevated BMI and a lower prevalence of at-risk malnutrition compared to our participants.34 They were diagnosed with limited mobility by

the SPPB at a rate of 18.7%, which is lower than that reported in a previous study;26 this may be because, in this trial, the exclusion criterion excluded individuals with disabilities and severe dementia; those are the majority of malnutrition and mobility impairment patients. The group with locomotor dysfunction was older and had fewer years of education; more financial problems; cognitive impairment; hearing and visual impairment; a history of falls; polypharmacy; greater use of gait aids; and more cases of malnutrition. Thus, there are more comorbidities and fragilities.

The specificity of the malnutrition application tool, which involves two screening questions concerning weight loss and poor appetite, is excellent, but the sensitivity is fair. These results are similar to those of previous ICOPE face-to-face screening trials, but this trial was more sensitive and accurate. In the previous ICOPE face-to-face screening trial, researchers included BMI in screening for malnutrition. Thus, the sensitivity increased; this may be because BMI has high sensitivity by itself. We therefore added BMI to the application. The results show that the sensitivity increased, which is consistent with the previous face-to-face trial.5,7-8,10,28-32

In this study, the three questions in the application to screen for locomotor capacity impairment had high sensitivity, specificity, and good diagnostic value. This result resembles that of previous face-to-face studies; the sensitivity of the STEADI’s three key questions ranged from 78.9 to 100%.37-41 Therefore, this application may be used to screen for at-risk malnutrition and limited mobility by online self-screening in Thai older adults, except in an inpatient setting.

The strength of this study is its ability to screen older adults quickly. Compared with previous studies, screening by the MNA takes approximately 7–30 minutes42, and the SPPB takes approximately 10–15 minutes.11 However, this application takes almost 1–2 minutes to complete. Therefore, this application is a timesaving and age- friendly tool. Furthermore, the only additional equipment required is the individual’s mobile phone or tablet. Moreover, individuals can use it independently, making

it suitable for situations where face-to-face screening is challenging. This tool lowers the barriers to accessing the screening process. However, few studies have validated the screening performance of the first-step ICOPE tool and the first-step STEADI algorithm, especially in mobile or tablet applications.27-31 This application is available for validation.

The limitations of this study are that the mean age of the participants was 69 years, which favors younger older adults, and the mean number of years of education favors higher education, which introduces selection bias but may be considered usual in a study that focuses on digital technology. Next, they were diagnosed with limited mobility by the SPPB fewer times than in the previous study;25 this may be because, in this trial, the exclusion criterion excluded individuals with disabilities. Moreover, the use of the MNA as a standard diagnostic tool may be inconsistent because the gold standard for the diagnosis of malnutrition is the GLIM criteria. However, according to the MaNuEL study, the MNA can be used as a standard reference tool for evaluating the validity of nutritional screening instruments; these are considered ‘semigold’ reference standards and can substitute for the gold standard.5-6,8,19 In this application, some words of the question can have an ambiguous meaning: “feel unsteady when standing or walking”. We evaluated the validity of the test, which provided good sensitivity, and afterward, the question could be used. The BMI is one part of the MNA that is used as a standard reference, which may lead to an increase in its validity. In the MNA, the BMI’s point is 2 out of a total score of 30, which is a minimal count and may not produce much change. However, the interpretation should be carefully considered. Next, this research did not test test-retest and interrater reliability because the participants lived in a distant area. As a result, the test’s reliability may decrease. Furthermore, the use of electronic devices among Thai older adults is limited. However, the current trend is to increase the use of electronic devices. In the future, if this application is validated for use by caregivers, it can be used by both older adults and caregivers.

For implementation, this application can be used by Thai older adults in noninpatient settings to screen for at- risk for malnutrition and limited mobility. Furthermore, this application can provide self-care information or suggestions for further evaluation when there are at- risk conditions that can be put in the application for immediate feedback. We should assess the test-retest and interrater reliability of the research to reduce the limitations in future research.

CONCLUSIONS

Combining BMI with the 2 questions of the WHO- ICOPE screening for malnutrition provides better sensitivity. However, BMI should be used with caution because it is a body composition metric that is included in the standard reference, the MNA. The first step, the 3-key question of the STEADI algorithm, which is applied to screen for limited mobility and fall risk, has high sensitivity and is appropriate for use as a screening tool in older adults. The majority of the participants reported their high satisfaction with the application rated their excellent confidence in their ability to use the application by themselves. Thus, this application is an age-friendly, time-saving tool that can be used when face-to-face screening is difficult.

ACKNOWLEDGEMENTS

The authors would like to thank all Siriraj Hospital personnel who assisted with data collection and investigation. We acknowledge all participants who enthusiastically participated in this trial.

DECLARATION

Grants and Funding Information

The Siriraj Foundation, Siriraj Hospital, Thailand, who provided funding for this trial, have no influence in the study’s design, method, data analysis, or interpretation.

Conflict of Interest

The authors declare that they have no competing interests.

Author Contributions

P.T., W.M., S.I.- conceptualization, methodology, software, validation, resource. P.T., A.J., P.S.- investigation. P.T.- writing original draft. P.T., W.M.- visualization. W.M.-Project administration, funding acquisition. S.I.-supervision. P.T., W.M., S.I.- writing review and editing. All co-authors- final approval of the submitted manuscript.

Use of Artificial Intelligence

No artificial intelligence tools or technologies were used in the writing, analysis, or development of this research.

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‌A Survey of Home-Based Cognitive Stimulation Activities in Thai Patients with Mild Cognitive Impairment and Mild Dementia

Wirarat Jinatongthai, M.D.1, Kitikan Thana-udom, M.D.2, Vorapun Senanarong, M.D.1, Chatchawan Rattanabannakit, M.D.1,*

1Division of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 2Department of

Psychiatry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

*Corresponding author: Chatchawan Rattanabannakit E-mail: chatchawan.rat@mahidol.ac.th

Received 27 September 2024 Revised 4 November 2024 Accepted 4 November 2024 ORCID ID:http://orcid.org/0000-0001-9769-9556 https://doi.org/10.33192/smj.v77i1.271344

All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.

ABSTRACT

Objective: This study investigated the characteristics of home-based activities in individuals with mild cognitive impairment (MCI) and mild dementia, as well as factors related with those activities.

Materials and Methods: A cross-sectional, questionnaire-based study was conducted on patients with MCI and mild dementia at Siriraj Hospital. Data on patient and caregiver characteristics, home cognitive activities, and proficiency in using information technology (IT) devices and telecommunications applications were collected. Home activities were categorized into cognitive, physical, and religion-related activities based on their type and frequency.

Results: Of 157 enrolled patients with a mean age of 76.2±7.9 years, 46.5% were diagnosed with MCI and 53.5% with mild dementia. The MCI group exhibited significantly higher frequencies of activities such as reading, writing, playing mobile games, texting, calculating, music listening, meditation, praying, almsgiving, doing chores, cooking, and gardening (all p<0.05). Approximately 51% of patients were able to use IT devices. MCI patients demonstrated greater proficiency in using smart IT devices and teleconferencing applications than those with mild dementia (79.5% vs. 26.2%, and 49.3% vs. 11.9%, both p<0.001). Cognitive activity scores were associated with age (r=-0.34, p<0.001), body mass index (r=0.16, p=0.04), educational attainment (r=0.38, p<0.001), IT device literacy (r=0.41, p<0.001), and proficiency in using telecommunications applications (r=0.55, p<0.001).

Conclusion: Thai patients with MCI and mild dementia engaged in limited home activities, particularly those with dementia. IT device literacy was surprisingly prevalent and contributed to higher cognitive activity scores. Developing home-based cognitive stimulation programs for Thai patients facing cognitive challenges utilizing telecommunication may be feasible.

Keywords: Home-based activity; cognitive activity; mild cognitive impairment; mild dementia; Thai (Siriraj Med J 2025; 77: 39-50)

INTRODUCTION

Leisure activities impact cognitive decline in geriatric adults. Engaging in activities such as board games, reading, musical instruments, crossword puzzles, dancing, household chores, walking, swimming, and caregiving significantly reduces the risk of cognitive decline.1

A survey conducted in 2020 on Thai individuals aged over 60 during the COVID-19 pandemic revealed difficulties in activities such as leaving the house for errands, shopping, medical appointments, religious ceremonies, social activities, and visiting relatives or friends.2 The pandemic has also notably affected the decline in Mini- Mental State Examination scores in dementia patients, with a more significant decline during the lockdown.3,4 A systematic review suggests that cognitive training can improve cognitive function in patients with mild to moderate dementia.5 However, caregiver-led cognitive stimulation therapy at home did not significantly improve cognitive function in dementia patients, likely due to inconsistent engagement in cognitively stimulating activities within the study samples.6,7

There is evidence showing that factors such as low education attainment, depression, physical inactivity, obesity, or social isolation can contributed to modifiable risk factors for dementia.8 In the Thai population, previous

studies have identified several factors associated with dementia in the elderly. These factors include male gender, advanced age, low education levels, diabetes, depression, lack of mobile phone use, limited skills in computer and internet use, infrequent social participation, and minimal engagement in religious activities.9,10 Moreover, advanced ageing people are likely to experience home- activities limitation due to many possible factors, such as health status, depression, psychosocial factors, body mass index (BMI), or education level.11 Previous research suggests that engaging in activities such as computer use and arts or crafts may lower the risk of mild cognitive impairment (MCI).12 These activities may also promote cognitive reserve, neuronal function, neural growth, and alternative neural pathways, thereby facilitating the maintenance of cognitive function.13

Other studies have shown associations between leisure activities and dementia risk, indicating potential protective effects against dementia.14-18 However, a large longitudinal study suggested that reduced activity participation may indicate prodromal dementia, despite an unclear association with dementia incidence.19 Nonetheless, a systematic review in 2016 confirmed the positive association between mentally stimulating leisure activities and cognitive function, as well as decreased cognitive decline.20

Clinical guidelines recommend cognitive training for patients with cognitive impairment to slow disease progression. However, previous studies on home-based, caregiver-led cognitive stimulation therapy showed limited effectiveness in improving cognitive function for dementia patients, possibly due to difficulties in consistently engaging participants in cognitively stimulating activities.6,7 Limited information exists on home-based cognitive training for dementia patients in Thailand. This study aimed to investigate the characteristics of home activities that contribute to cognitive function in individuals with MCI and mild dementia, as well as factors influencing these activities. The findings may facilitate the development of home-based tools or activities to stimulate cognitive function at home.

MATERIALS AND METHODS

Patient population and data collection

This cross-sectional study was conducted at a single center university hospital between September and December 2022 and was approved by the Siriraj Institutional Review Board (COA no. Si 448/2022). Eligible participants were (1) individuals aged 60 years old or older who visited the memory clinic or related clinics at Siriraj Hospital, (2) diagnosed with MCI or mild dementia, and (3) had at least one caregiver. MCI was defined as having a measurable objective cognitive impairment such as a Montreal Cognitive Assessment21 (MoCA) score below 25, while having the Thai Mental State Examination22 (TMSE) score of 24 to 30. The TMSE is an adaptation of the Mini-Mental State Examination (MMSE). Patients with MCI were also characterized by having normal activities of daily living, as indicated by a Functional Assessment Staging23 (FAST) scale score of 3 or a Global Deterioration Scale24 (GDS) score of 3. Mild dementia was defined as having a TMSE score of 18 to 23, a FAST score of 4, or a GDS score of 4. The diagnosis of MCI or mild dementia was then re-validated by at least two experienced neurologists. The exclusion criteria were (1) severe visual, auditory, or mobility impairments that hindered daily activities and cognitive tests, and (2) cognitive decline caused by reversible processes such as vitamin B12 deficiency or thyroid disorders.

The sample size was calculated using the formula for infinite population proportion and drew upon information from a previous study.1 The proportion of individuals regularly engaging in leisure and physical activities was set at 0.25, with an acceptable margin of error of 0.07 and a type 1 error of 0.05. The calculated sample size was 147 individuals. After adding 10 percent to account for incomplete data, the adjusted sample size was 162

individuals. However, five participants were excluded after recruitment because they were initially classified as having mild dementia but were later found to have moderate dementia upon further review.

During routine outpatient visits, patients and their caregivers were apprised of the study and subsequently invited to engage in the research. Caregivers who agreed to participate provided written informed consent. The caregivers then completed a comprehensive questionnaire on (1) the patient and caregiver characteristics, (2) patient and caregiver proficiency with information technology (IT) devices and aptitude in utilizing telecommunications applications, and (3) patient engagement in cognitive stimulation activities at home.

Home-based cognitive stimulation activities and activity scores

Twenty-five home-based cognitive stimulation activities were categorized into three groups. The first group consisted of 14 cognitive-related activities: reading; writing; playing cards; board games; crossword puzzles; mobile games; texting; computer use; calculations; drawing/ painting; playing musical instruments; listening to music; singing; and socializing with friends/relatives. The second group included four religion-related activities: meditation; praying; almsgiving; and temple visits. The third group encompassed seven physical activities: dancing; chores; cooking; babysitting; pet care; gardening, and exercise. Each activity was rated based on frequency: never; occasionally; 1–2 days/week; 3–5 days/week; and daily. According to a previous study by Verghese J et al1, activity scores were calculated as follows: 0 point for never and occasionally; 1 point for 1–2 days/week; 4 points for 3–5 days/week; and 7 points for daily participation received. Thus, the maximum scores in our study for cognitive- related, religion-related, and physical activities were 98, 28, and 49, respectively. Furthermore, Participation was classified as “frequent” for 3–7 days/week engagement

and “rare” for 0–2 days/week engagement.

IT device literacy and ability to use telecommunications applications

IT device literacy data from the questionnaires were divided into two categories: simple devices (CD players, radios, and mobile phones for basic calls) and smart devices (smartphones, tablets, and computers). The ability to use telecommunications applications was also classified into two categories: simple applications (such as LINE for texting, Facebook, and YouTube) and smart applications (for example, LINE for video calls, Facetime, or Zoom).

Statistical analysis

Statistical analyses were conducted using PASW Statistics, version 26 (SPSS Inc, Chicago, IL, USA). Age, BMI, TMSE, MoCA, and Thai Geriatric Depression Scale-1525 are reported as the mean and standard deviation. Nonparametric continuous data are presented as a median with an interquartile range, and categorical data are shown as percentages. Statistical comparisons for categorical data were performed using Pearson’s chi-square test, while the Mann–Whitney U test was used for continuous variables. The independent samples Kruskal–Wallis test was employed to compare three or more categorical variables with nonparametric data. Spearman’s rank correlation coefficient was used to assess variable correlations. Statistical significance was defined as a p-value < 0.05.

RESULTS

The study included 157 patients with a mean age of

76.2 ± 7.9 years, 65.6% of whom were female. Of these, 73

(46.5%) were diagnosed with MCI, whereas 84 (53.5%) were identified with mild dementia. Statistically significant differences were observed in the mean age, generation, BMI, education level, TMSE scores, and MoCA scores of the MCI and mild dementia patient groups (Table 1). The caregivers of the patients in the two groups had no significant differences in their characteristics (Table 2). While the level of confidence and anxiety in caregiving in the two groups did not significantly differ, the caregivers of patients with mild dementia experienced a significantly greater burden of care (p < 0.001).

Table 3 showed significant differences in the IT device literacy and ability to use telecommunications applications of the two groups. A majority (79.5%) of MCI patients were proficient in using smart devices, compared to only 26.2% of mild dementia patients (p < 0.001). Similarly, 49.3% of MCI patients could use video- call or conference applications, while only 11.9% of mild dementia patients possessed this capability (p < 0.001). Conversely, there were no significant differences in IT device literacy and the ability to use telecommunications applications among the caregivers in the two groups. Regarding the activity scores, the patients in the two groups exhibited significant differences in their cognitive (p < 0.001), physical (p < 0.001), and religion-related activity scores (p = 0.004).

Patients with MCI engaged in reading, writing, playing mobile games, texting, calculating, and listening to music more frequently than those with mild dementia. Patients with MCI also had higher frequencies of home physical activities (chores, cooking, gardening) and religion-

related activities (meditation, praying, almsgiving). Most patients did not report that COVID-19 had negatively impacted their activities; however, meeting with friends or relatives, visiting temples, and almsgiving were affected, with 47.1%, 28.7%, and 19.1% of patients, respectively, reporting an adverse impact (Table 4).

The results revealed significant associations between cognitive-related activity scores and physical activity scores, religion-related activity scores and BMI (Fig 1). A significant inverse association was found between cognitive activity scores and the Geriatric Depression Scale-15 as well as patient age. Furthermore, patients’ cognitive-related, religion-related, and physical activity scores significantly differed based on their IT device literacy and ability to use telecommunications applications (Fig 2). Patients who could use smart devices or video call/conference applications had higher scores for all three cognitive-stimulation activity groups. When comparing the impact of different levels of education and family income on each home-based activities, only a significant difference in level of education was found in the scores of cognitive-related activities.

DISCUSSION

This study is the first to investigate home-based activities in Thai patients with MCI and mild dementia. The findings suggest that home activities, including reading, writing, playing mobile games, texting, calculating, listening to music, meditating, praying, giving alms, doing chores, cooking, and gardening, showed significant differences in frequency between individuals with MCI and those with mild dementia. A previous study compared home activities in elderly individuals who developed dementia with those who did not, indicating that certain activities, such as reading, playing board games, playing musical instruments, and dancing were found to be less common among patients who would go on to develop dementia.1 Despite cultural differences, we also observed that activities like reading were less frequent among patients with dementia in our study. However, our study compared individuals with dementia to those with MCI, rather than assessing the risk of developing dementia as was done in the previous study.

The study found significant associations between older age, lower BMI, lower education level, IT device literacy, and ability to use telecommunications applications with poorer cognitive function. Our study results align with previous research, which consistently identifies age and education level as significant risk factors for cognitive impairment.26,27 While research on the influence of information and communication technology (ICT)

TABLE 1. Baseline characteristics of patients and comparison between MCI and mild dementia groups.

Abbreviations: BMI, body mass index; CKD, chronic kidney disease; MCI, mild cognitive impairment; MoCA, Montreal Cognitive Assessment; TGDS-15, Thai Geriatric Depression Scale; TMSE, Thai Mental State Examination

use on cognition is relatively limited, previous studies have also demonstrated that ICT usage is associated with cognitive benefits, including enhancements in memory and executive function in older adults over time.28,29

Surprisingly, 51.0% of patients in our study were able to use IT devices. Patients with MCI showed a high level of proficiency in using smart IT devices and teleconferencing applications than those with dementia. This finding was consistent with a study involving 2,172 people with dementia and MCI in Spain and Sweden, which reported that approximately 54.14% of participants used a smartphone almost every day, while only 9.76% utilized specific application or software to support their memory.30 In our study, 44.9% of participants were able to use any application; however, we did not collect data on the specific applications they used.

The study also examined the impact of religion- related activities on cognitive status. Previous research has shown a positive association between religious or spiritual involvement and cognitive function.31-33 However, limited information exists regarding younger individuals and non-Christian groups. Given that nearly all participants in the present study were Buddhist (99%), it appears that common practices in Thai culture, such as meditation, almsgiving, and praying, are significantly associated with cognitive function.

The study has its limitations. this study relied on a questionnaire asking caregivers about the past activities of patients. As such, it may be subject to recall bias, as the accuracy of the responses depends on the caregivers’ memory and perception. Moreover, there is a possibility that the accompanying caregiver during the outpatient

TABLE 2. Baseline characteristics of caregivers and group comparison.

Caregiver’s availability for home cognitive training (%)

Available hours in a day, median (IQR)

Available days in a week, median (IQR)

Abbreviation: MCI, mild cognitive impairment

visit may not be the primary one. Hence, the information accuracy might have been affected. Lastly, our study did not collect data on underlying factors that might influence impaired mobility, which could potentially contribute to a lower activity frequency.

In future research, the cross-sectional design of this study limits the ability to establish clear causality or identify which specific activities may contribute more significantly to a decline in cognitive function in patients with MCI and mild dementia. A longitudinal study will be needed to determine which activities that should be targeted for future intervention. The high prevalence of IT device use among patients with MCI and their caregivers in our study highlights the potential for future

interventions using mobile or telecommunication devices in Thai patients with MCI. In dementia patients, IT literacy is lower, so developing interventions through their caregivers may be a more feasible approach.

CONCLUSION

The current investigation provides valuable insights for home-based activities of Thai patients with MCI and mild dementia. Approximately half of them were able to use IT devices, a factor that may be associated with higher cognitive activity scores. Developing home-based cognitive stimulation programs for Thai patients with cognitive issues using telecommunication technology is potentially feasible.

TABLE 3. IT device literacy and telecommunications application proficiency of patients and caregivers, with patients’ activity scores.

* Simple devices: CD players, radios, or phones for simple calls

† Smart devices: smartphones, tablets, or computers

‡ Simple applications: Line application for texting, Facebook, or YouTube

§ VDO call applications: Line application for video calls, Facetime, or Zoom

Abbreviations: app, application; MCI, mild cognitive impairment

TABLE 4. Frequency of home activities (cognitive, physical, and religion-related) and group comparison.

Reading

Rare Frequent

61.8

38.2

53.4

46.6

69.0

31.0

0.045

Dancing

Rare Frequent

97.5

2.5

97.3

2.7

97.6

2.4

0.887

Home All

activities and patients frequency (%) n=157

Mild

MCI dementia p

n=73 n=84

Home All

activities and patients frequency (%) n=157

Mild

MCI dementia p

n=73 n=84

Cognitive activities Physical activities

Writing

Rare 84.7 75.3 92.9 0.002

Playing cards

Rare 99.4

Frequent 0.6

100.0

0.0

98.8

1.2

0.350

Frequent 15.3 24.7 7.1

Doing chores

Rare 36.9 21.9 50.0 <0.001

Cooking

Rare Frequent

66.9

33.1

56.2

43.8

76.2

23.8

0.008

Frequent 63.1 78.1 50.0

Playing board games

Rare 99.4 100.0 98.8 0.350

Doing crossword puzzles

Rare 99.4 98.6

Frequent 0.6 1.4

100.0

0.0

0.282

Frequent 0.6 0.0 1.2

Babysitting

Rare 89.8 91.8 88.1 0.446

Caring for pets

Rare 73.2

Frequent 26.8

75.3

24.7

71.4

28.6

0.581

Frequent 10.2 8.2 11.9

Playing mobile games

Rare 93.6 87.7 98.8 0.004

Texting on a mobile phone

Rare 68.2 43.8

Frequent 31.8 56.2

89.3

10.7

<0.001

Frequent 6.4 12.3 1.2

Gardening

Rare 72.6 58.9 84.5 <0.001

Working out

Rare Frequent

49.0

51.0

45.2

54.8

52.4

47.6

0.370

Frequent 27.4 41.1 15.5

Using a computer

Rare 96.2 94.5 97.6 0.312

Frequent 3.8 5.5 2.4

Religion-related activities

Drawing or painting

Rare 99.4 98.6 100.0 0.282

Frequent 0.6 1.4 0.0

Meditation

Rare Frequent

86.6

13.4

79.5

20.5

92.9

7.1

0.014

Praying

Calculating

Rare Frequent

82.2

17.8

67.1

32.9

95.2

4.8

<0.001

Rare 56.7 47.9 64.3 0.039

Almsgiving

Rare Frequent

80.9

19.1

74.0

26.0

86.9

13.1

0.040

Frequent 43.3 52.1 35.7

Listening to music

Rare 49.7 39.7 58.3 0.020

Frequent 50.3 60.3 41.7

Visiting temples

Playing a musical instrument

Rare 97.5 95.9

Frequent 2.5 4.1

98.8

1.2

0.247

Rare 96.2 94.5 97.6 0.312

Frequent 3.8 5.5 2.4

Singing

Fare Frequent

87.9

12.1

83.6

16.4

91.7

8.3

0.120

Abbreviation: MCI, mild cognitive impairment

Meeting with friends or relatives

r = 0.436; p<0.001 r = 0.276; p<0.001

r = -0.171; p=0.043 r = -0.340; p<0.001

r = 0.163; p=0.043

Fig 1. Correlations between scores for cognitive-related, religion- related, and physical activity scores, TGDS-15 scores, age, and BMI of patients.

Abbreviation: TGDS, Thai Geriatric Depression Scale; BMI, body mass index

P<0.001 P=0.390 P=0.054

P=0.054 P=0.653 P=0.250

P<0.001 P<0.001 P=0.006

P<0.001 P<0.001 P=0.001

Fig 2. Activity scores stratified by education level, family income, IT device literacy, and telecommunications application proficiency.

ACKNOWLEDGEMENTS

The authors acknowledge Dr. Saowalak Hunnangkul for facilitating the statistical analysis.

DECLARATION

Grants and Funding Information

This research project was supported by the Siriraj Research Development Fund, Faculty of Medicine, Siriraj Hospital, Mahidol University (grant number [IO] R016531077).

Conflict of Interests

The authors declare no conflict of interest.

Author Contributions

Conceptualization and methodology, W.J., K.T.,

V.S. and C.R. ; Investigation, W.J. and C.R. ; Formal analysis, W.J. and C.R. ; Visualization and writing – original draft, W.J. and C.R. ; Writing – review and editing, K.T., V.S. and C.R. ; Funding acquisition, W.J. and C.R. ; All authors have read and agreed to the final version of the manuscript.

Use of artificial intelligence

The authors declare no use of artificial intelligence.

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    ‌Prevalence of Geriatric Syndromes and Satisfaction of Service in Older People Receiving Annual Health Screening at the Check-up Clinic, Siriraj Hospital

    
    

    Harisd Phannarus, M.D.1, Supakorn Chansaengpetch, M.D.1, Tirathat Virojskulchai, M.D.1, Napaporn Pengsorn, B.N.S.2, Pensri Chaopanitwet, B.N.S.2, Usa Vannachavee, M.N.S.2, Jirawit Wong-ekkabut, M.Sc.1, Ananya Treewisoot, B.Sc.1, Sunun Thanasamut, B.N.S.2, Angkana Jongsawadipatana, M.Sc.3, Weerasak Muangpaisan, M.D.1,4,*

    1Department of Preventive and Social Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 2Department of Nursing,

    Siriraj Hospital, Mahidol University, Bangkok, Thailand, 3Department of Research, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 4Siriraj Academic Center of Geriatric Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

    
    

    
    

    *Corresponding author: Weerasak Muangpaisan E-mail: drweerasak@gmail.com

    Received 18 October 2024 Revised 5 November 2024 Accepted 15 November 2024 ORCID ID:http://orcid.org/0000-0001-5863-3597 https://doi.org/10.33192/smj.v77i1.271734

    
    

    All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.

    
    

    ABSTRACT

    Objective: To assess the prevalence of geriatric syndromes (GSs) and evaluate service satisfaction among older patients attending a comprehensive geriatric check-up clinic (CGCC) at Siriraj Hospital.

    Materials and Methods: A cross-sectional study was conducted at the CGCC from December 2021 to November 2022. Participants aged 60 years and older were screened using a two-step approach; short screening by a standard questionnaire followed by an in-depth assessment. GSs were identified through standardized tools, and patient satisfaction was assessed using a structured questionnaire.

    Results: Of 159 participants, 67.9% were women, with a mean age of 66.6 ± 6 years. In step 1, 43.7% showed cognitive impairment, 29.1% had a risk of falls, and 76% reported oral health issues. Step 2 confirmed cognitive impairment in 40.6%, malnutrition risk in 93.3%, and sarcopenia in 78%. The mean satisfaction score was 33.3 ± 2.5 out of 35 points. Total service time averaged 104.2 ± 36.9 minutes.

    Conclusion: In a health check-up clinic where GSs are often under-recognized, GSs, particularly cognitive impairment, fall risk, and oral health issues, are prevalent. Despite extended service times, patient satisfaction remained high, highlighting the importance of comprehensive screening in geriatric care.

    Keywords: Geriatric syndromes; cognitive impairment; comprehensive geriatric assessment; patient satisfaction; health screening (Siriraj Med J 2025; 77: 51-63)

INTRODUCTION

Geriatric syndromes (GSs) comprise a well-defined cluster of conditions that have a significant impact on the health of older individuals. These conditions are influenced by age-related physiological changes, functional stressors, and identifiable chronic diseases, resulting in a multifaceted process of organ system impairment.1,2 Owing to their substantial impact on the older population, GSs have emerged as a pivotal concern within the field of geriatric care. This burden includes a variety of challenges, including increased disability rates, elevated hospitalization rates, and prolonged lengths of stay in health care facilities.3-5 GSs are defined and captured under the mnemonic “7Is”: inappetence, instability, intellectual impairment, incontinence, immobility, insomnia, and iatrogenesis. In the outpatient setting, a range of screening tools tailored to these specific conditions are employed, contingent upon the nuances of the health care system and the preparedness of health care personnel.1 The prevalence of GSs reported in previous studies ranged from 36% to 75.3%.4-6 These results demonstrate the necessity of addressing GSs as a crucial aspect of geriatric health care management.

Thailand, classified as an upper middle-income country, has a life expectancy of approximately 84 and 79 years for females and males, respectively.7 The demographic landscape reveals a significant shift, with the proportion of individuals aged 60 years and older in Thailand reaching a considerable 20% of the population by 2023.8,9 However, clinical practices focused on GSs are

relatively rare.5 In addition, the number of GS diagnoses remains inconclusive, with considerable variability observed across different health care providers and regions. This variability highlights the absence of standardized approaches for addressing GSs. While the Thai Ministry of Public Health has introduced screening guidelines for various geriatric issues in the older population10, implementation difficulties persist. Inadequate infrastructure and a lack of specialists in certain regions make it difficult for health care professionals to comply with these guidelines. This highlights the disparities and complexities surrounding the integration of geriatric care protocols, leading to efforts to bridge the gap between policy and practical execution.

In the context of geriatric care at Siriraj Hospital, notable advancements were realized with the establishment of the comprehensive geriatric check-up clinic (CGCC) in 2021. This initiative was undertaken with the primary purpose of enhancing the quality of care and facilitating the early detection of GSs in a general health check-up clinic. The clinic provides a platform for comprehensive geriatric assessment (CGA) for individuals aged 60 years and older. This assessment protocol is intended to incorporate a holistic evaluation of physical, mental, social, and functional aspects. The outcome of this thorough assessment subsequently guides the diagnostic process, allowing the identification of health-related conditions requiring specialized care.

Despite the substantial range of studies, to our knowledge, investigations into the prevalence of GSs

and the consequential health care utilization resulting from GS screening in a check-up clinic within a tertiary care facility in Thailand are lacking. The present study assumes significance by focusing on the demographics of older outpatients who have undergone geriatric screening. The objectives of this study were to determine the prevalence of GSs, examine the practical implications of screening outcomes by assessing their influence on medical consultations, and assess the level of satisfaction among older outpatients attending Siriraj Hospital’s comprehensive check-up clinic.

MATERIALS AND METHODS

Study design and participants

This was a cross-sectional study in which participants were recruited from the CGCC specified for older people at Siriraj Hospital, which was developed in 2020. The study cohort comprised individuals aged 60 years and older who were undergoing a new protocol of comprehensive geriatric screening and assessment within the check- up clinic of the Department of Preventive and Social Medicine, Faculty of Medicine, Siriraj Hospital, Mahidol University, Thailand. The recruitment phase spanned from December 2021 to November 2022. The eligibility criteria for enrollment were as follows: 1) subjects who were 60 years of age or older; 2) subjects who received comprehensive geriatric screening services at the CGCC at Siriraj Hospital; and 3) subjects who did not have communication problems. The exclusion criteria were as follows: 1) older individuals who had not undergone a full battery of comprehensive geriatric screening; and

2) older individuals or representatives who declined to participate in the study. All participants provided written informed consent.

The sample size for this study was determined via Cochran’s formula11 with a 95% confidence level. Previous studies reported that the prevalence of undetected GSs was 6.7% in geriatric clinics and 2.5% in community-dwelling populations. However, as no data were available for the check-up clinic population, we estimated a prevalence of 5% for the calculation. The allowable margin of error was set at 4%, with a corresponding z score of 1.96 at the 95% confidence level. The minimum sample size was 115 participants. To account for an estimated 20% rate of missing data, the final targeted sample size was adjusted to 138 participants. The study protocol was approved by the Siriraj Research Ethics Committee (COA No. Si 218/2565).

CGCC services and measurements

The CGCC was established in 2020 with the primary

objective of conducting a comprehensive evaluation of GSs and aging-associated problems in the older population. This specialized facility provides a comprehensive array of services designed to identify and address a spectrum of concerns through systematically organized flow management (Fig 1). The scope of evaluation included malnutrition, cognitive impairment, depression, fall and fracture risks, sarcopenia, frailty, oral health problems, frailty, hearing and visual problems, and a general health assessment stratified by distinct age groups. The assessment embraced a multifaceted approach, integrating thorough patient history-taking, a physical examination, and multiple questionnaire-based assessments focusing on each age- related concern. The majority of questionnaires employed in this service were derived from standardized instruments or were based on screening guidelines from the Ministry of Public Health, Thailand.10 Some of these were subsequently tailored to specific contexts and constraints of health care services, particularly limitations inherent to the service duration allocated for each patient. The selection of questions ensured practicality and administrative efficiency.

In accordance with the CGCC framework, the screening process was conducted in two steps (Fig 1). During the whole process, the service team administered a comprehensive evaluation focusing on general physical, mental, and social conditions through a structured set of screening questionnaires. These questionnaires encompassed the following key domains:

1. Malnutrition risk assessment: The first step of the malnutrition risk assessment involved the application of an adapted version of the SPENT Nutrition Screening tool.12 This tool was modified by a panel of experts to enhance its applicability in identifying individuals at high risk for malnutrition. It comprises three questions targeting key indicators of nutritional risk: recent appetite loss, unintentional weight loss of 3 kg or more within the past three months, and body mass index (BMI) values either below 18.5 kg/m2 or equal to or greater than 30 kg/m2. A positive response to any of these questions triggered a more comprehensive evaluation in the second stage of screening. In step 2, the Mini-Nutritional Assessment short-form (MNA-SF)13,14 was employed. The MNA-SF, a widely validated tool, provides a total score of up to 30 points, categorizing individuals into three nutritional statuses: normal nutritional status (24–30 points), at risk of malnutrition (17–23.5 points), and malnourished (<17 points).13

2. Cognitive function evaluation: The assessment of cognitive function incorporated both self-reported cognitive-related questions and an adapted version of the

   
   

   
   

   Fig 1. Flow chart of the comprehensive geriatric screening of participants.

   Abbreviations: BIA, bioelectrical impedance analysis; BMD, bone mineral density; CGCC, Comprehensive geriatric check-up clinic; ENT, ear nose throat; FRAX, Fracture risk assessment tool; ICOPE, Integrated care for older people; MDT, Multidisciplinary team; MNA-SF, mini-nutritional assessment short-form; MoCA, Montreal cognitive assessment; MSRA, Mini sarcopenia risk assessment; PHQ, patient health questionnaire; TMSE Thai mental stale examination; TUGT, timed up and go test; 5TSTS, five-times-sit-to-stand test

   
   

   Integrated Care for Older People (ICOPE) framework.15 The self-reported cognitive assessment encompassed key indicators, including any recent memory loss, functional deficits, and changes in behavior or emotional state. In the adapted version of the ICOPE cognitive screening, the assessment focused on two specific cognitive domains: word recall (three common words) and orientation (date, month, year and place). The positive indicators of the respondents were subsequently assessed using the Thai Mental State Examination (TMSE)16 and the Montreal Cognitive Assessment (MoCA)17 in the second step, which were tailored to their educational background. Both the TMSE and MoCA are standardized cognitive assessments, with a total possible score of 30 points. For the TMSE, a

   cutoff score of 23/24 was employed to identify cognitive impairment16, whereas for the MoCA, a cutoff score of 24/25 was used to determine mild cognitive impairment (MCI).17

3. Depression screening: The depression screening instrument, which was originally validated for the Thai population18, consists of two questions suggesting depressive symptoms in the past 2 weeks and was designed to identify individuals at high risk for depression. Respondents who provided affirmative responses to at least one of these questions were flagged for further evaluation. High-risk individuals were subsequently assessed via the Patient Health Questionnaire (PHQ-9), a widely recognized instrument for determining the severity of depression.19

   
   

   In cases where the PHQ-9 score exceeded 7 points, the PHQ-8 was employed to evaluate the risk of suicidal ideation, offering an additional layer of insight.20

4. Fall risk screening: The fall risk screening tool employed is a tool developed by the Centers of Disease Control and Prevention (CDC) and Stopping Elderly Accidents, Deaths & Injuries (STEADI).21 This screening tool consists of three essential questions aimed at identifying individuals at high risk for falls. The questions focused on key risk factors, including a history of falls within the past year, a subjective feeling of instability, and a fear of falling. An affirmative response to any of these screening questions triggered a comprehensive fall risk evaluation. The subsequent assessments included the timed up and go test (TUG)22 and the five-times-sit-to-stand test (5TSTS)23 in step 2. These objective measures are well-established methods in clinical practice for evaluating mobility and lower limb strength, both of which are indicators of fall risk. Participants identified as high risk on the basis of these tests were initially checked for any reversible conditions and provided fall prevention. For those at high risk, further evaluation was carried out by referral to a specialist, enabling in-depth investigation of the underlying causes and the development of individualized, targeted preventive interventions.

5. Fracture risk assessment: The Fracture Risk Assessment Tool (FRAX)24 was employed to estimate the risk of major osteoporotic and hip fractures. This tool provides a quantitative measure of fracture risk, with the outcomes indicating the likelihood of fractures at critical sites such as the hip and other major osteoporotic regions. In cases where the calculated fracture risk exceeded thresholds of ≥3% for hip fractures and ≥20% for major osteoporotic fractures, participants were advised to schedule appointments for bone mineral density (BMD) testing to obtain a definite diagnosis.25

6. Sarcopenia screening: The modified version of the Mini-Sarcopenia Risk Assessment (MSRA-5)26, a five-question screening tool, was employed to assess the risk of sarcopenia. A cumulative score of 30 or below signifies a positive result for sarcopenia.26 Individuals with a positive screening result underwent further evaluations, including the 5TSTS, handgrip strength, and bioelectrical impedance analysis (BIA), to classify them as having normal, sarcopenia, or severe sarcopenia.27

7. Frailty identification: The FRAIL scale28, consisting of five questions, was used to identify frail individuals. Those with three or more affirmative responses were categorized as frail and underwent additional assessments to determine the underlying causes of frailty.

8. Oral health assessment: A battery of five questions

   aimed at detecting oral health issues, including 1) the presence of pain, 2) pus or bleeding when brushing the teeth, 3) the use of dentures, 4) the presence of cavitated dental lesions or food impaction, and 5) a lack of scaling within 12 months. If a respondent answered yes to Question 1) or 2) or had malnutrition and answer yes to Question 3), 4), or 5), they were referred to a dental clinic for further evaluation. If the responses were yes to 3), 4), or 5) with no malnutrition, they received an appointment to see a dentist.

9. Ear, nose, and throat (ENT) assessment: This screening included questions related to dizziness, hearing difficulties, and swallowing problems. A positive response in any of these areas indicated a high risk for ENT issues, and the respondent was referred to a specialist.

10. Ocular health screening: Participants were asked about their ophthalmologist visits within the past year. Individuals who had not seen an ophthalmologist were referred for further evaluation.

11. Traditional Thai medicine (TTM) services: Respondents were screened for symptoms that aligned with the treatments available through TTM services. Those who met the criteria were referred for TTM services.

    Each of these domains provides a targeted approach to screening, enabling early identification of potential health issues and facilitating timely referrals for appropriate interventions.

    Data collection

    A research assistant approached each participant enrolled in the CGCC to obtain informed consent prior to data collection. The data collection was conducted by members of the clinic, particularly nurses or other health care personnel, and was seamlessly embedded into the CGCC’s routine services. A comprehensive dataset was constructed, which included various demographic and health-related details recorded in case record forms. Initially, demographic information such as age, sex, level of education, income, smoking status, and physical activity level was collected. Basic health information, including weight, height, blood pressure, and the presence of underlying diseases, was subsequently recorded. The participants then completed the first step of the screening process via the CGCC’s screening instrument. For those who tested positive in the first step of the screening process, a second step of more in-depth assessment followed. Upon completion of the entire check-up process, patient satisfaction with the services provided was assessed via a structured satisfaction questionnaire. Additionally, the time spent on each service was recorded to facilitate a comprehensive evaluation of the quality of care delivered

    
    

    at the CGCC. The satisfaction survey consisted of seven questions, with a total score of 35 points. Each question was rated on a five-point Likert scale ranging from 5 (very satisfied) to 1 (very dissatisfied).

    Statistical analyses

    SPSS version 18.0 (SPSS Inc., PASW Statistics for Windows, Chicago, IL, USA) was used for the statistical analysis. Continuous variables are presented as the means, medians, and standard deviations (SDs). Independent t tests, Pearson correlations, Mann‒Whitney U tests, and Wilcoxon signed-rank tests were used to analyze continuous data on the basis of the data distribution. Moreover, categorical outcomes are presented as frequencies and percentages. The chi-square test, or Fisher’s exact test, was used to compare categorical data. Univariate and multivariate linear regression analyses were used to evaluate the associations between variables. The odds ratios and adjusted odds ratios with 95% confidence intervals are reported. A p value less than 0.05 indicated statistical significance.

    
    

    RESULTS

    Demographic characteristics

    The baseline characteristics of the participants are presented in Table 1. A total of 159 participants were included in the study, with a mean age of 66.6±6 years. Women represented 67.9% of the participants. The mean body mass index (BMI) was 22.7±3.4 kg/m2, and the mean waist circumference was 88.7±7.1 cm for males and 84±9 cm for females. More than half of the participants (56%) had attained at least a bachelor’s degree. In terms of health status, 56% had at least one underlying condition, including hyperlipidemia (11.3%) and insomnia (9.4%). Additionally, 39% of the participants reported taking at least one medication regularly. Over half of the participants (52.2%) exercised at least five times per month, and 79.3% had received the COVID-19 vaccine, with 54.1% receiving the influenza vaccine.

    Outcomes of the comprehensive screening (step 1)

    In the first step of the screening process, oral health problems were the most commonly identified issue, affecting 76% of the participants, followed by ocular problems at 53.8%. Cognitive impairment was detected in 43.7% of the participants, while 29.1% were identified as being at risk of falls. Future fracture risk, as assessed via the FRAX score, was observed in 29.1% of the participants, with an average risk of 3.1±3.9% for hip fractures and

    8.6±5.7% for major osteoporotic fractures. Depression

    and malnutrition were less prevalent, affecting 10.8% and 9.5% of the participants, respectively. Frailty was reported in 1.9% of participants on the basis of the FRAIL scale. ENT problems and sarcopenia were identified in 38% and 31.4% of the participants, respectively. These findings are detailed in Table 2.

    Outcomes of the comprehensive screening (step 2)

    The participants who tested positive in step 1 underwent further assessment in step 2, and the results are summarized in Table 3. Cognitive impairment, categorized as mild cognitive impairment (MCI) or more significant impairment, was confirmed in 40.6% and 36.2% of those tested, respectively. The average scores for the TMSE, MoCA, and MoCA-B were 22.5±5.8, 20.9±4.3, and 17.1±4.9, respectively. With respect to fall risk, 56.5% of the participants in step 2 tested positive, with an average time of 10.8±2.8 seconds for the TUG test and 15.2±4.7 seconds for the 5TSTS test. Depression was confirmed in 41.2% of the participants, with an average PHQ-9 score of 5.8±3.5. Among those screened for malnutrition, 93.3% were confirmed to be at risk of malnutrition, with an average MNA-SF score of 22±4. Sarcopenia was confirmed in 78% of the participants, with an average 5TSTS time of 15.2±7.6 seconds. Handgrip strength for the dominant hand averaged 30±6.4 kg for males and 19.6±3.4 kg for females.

    Service quality and satisfaction

    The participants reported a high level of satisfaction with the CGCC services, with an average satisfaction score of 33.3±2.5 out of a possible 35 points. The average time required to complete the baseline characteristics was 8.1±3.8 minutes, while the comprehensive screening process took an average of 34.6±19.9 minutes. The total service time, including waiting time and physical examination by a physician, averaged 104.2±36.9 minutes. These results are presented in Table 4.

    Relationship between satisfaction and service time

    Fig 2 illustrates the relationships between the total satisfaction score and various service-related times during the CGCC service, including the total screening time, waiting time and total service time. No significant relationships were found between these time metrics and the satisfaction scores. The graphs presented nonlinear relationships, indicating that extended screening and waiting times were associated with a decline in patient satisfaction. The fitted values and 95% confidence intervals (CIs) for these relationships are depicted in the figures.

    
    

    TABLE 1. Demographic characteristics of CGCC participants (n = 159).

    
    

    Characteristics	Values
    Age, years±SD	66.6±6
    Women, n (%)	108 (67.9)
    BMI, kg/m2±SD	22.7±3.4
    Waist circumference, cm±SD Male	88.7±7.1
    Female	84±9
    MAP, mmHg±SD	90.7±11.6
    Education attainment, n (%) <Bachelor’s degree	70 (44)
    ≥Bachelor’s degree	89 (56)
    Having carers, n (%)	68 (42.8)
    Having ≥ 1 underlying disease, n (%)	89 (56)
    Hyperlipidemia	18 (11.3)
    Insomnia	15 (9.4)
    Cataract/Glaucoma	15 (9.4)
    Hypertension	11 (6.9)
    Having ≥ 1 medication, n (%)	62 (39)
    Current smoker, n (%)	3 (1.9)
    Current drinker, n (%)	8 (5)
    Exercise status, n (%) 1-4 times/month	42 (26.4)
    ≥5 time/month	83 (52.2)
    Received ≥ 1 vaccination, n (%)	157 (98.7)
    COVID-19 vaccine	126 (79.3)
    Influenza	86 (54.1)

    Abbreviations: BMI, body mass index; CGCC, comprehensive geriatric check-up clinic; cm, centimetre; MAP, mean arterial pressure; mmHG, millimetres of mercury; SD, standard deviation

    
    

    DISCUSSION

    This study provides new evidence on the effectiveness of a two-step comprehensive screening process for older populations, presenting the prevalence of GSs identified in step 1, followed by more detailed assessments in step 2 at a health check-up clinic in a tertiary care unit. This study also highlights the satisfaction scores, time spent on services, and relationships among these variables, offering insights into the operational efficiency of the check-up clinic.

    The application of standardized screening tools constitutes a fundamental component of the CGCC service. The tools applied throughout the two-step screening process exhibit varying levels of sensitivity and specificity, reflecting their applicability across different GSs. In the initial step of the screening process (step 1), depression was assessed via the Thai version of the two-question screening questionnaire, which has been shown to have high sensitivity (96.5%) and specificity (85.1%) in detecting depressive symptoms.18

    
    

    TABLE 2. Participant outcomes from the comprehensive screening (step 1).

    
    

    Positive screening in Step 1	Values
    At risk of malnutrition, n (%)	15 (9.4)
    Cognitive impairment, n (%)	69 (43.4)
    Depression, n (%)	17 (10.7)
    Falling, n (%)	51 (32.1)
    Fracture risk

    FRAX results, n (%)

    Positive 46 (28.9)

    FRAX score, %±SD

    
    

    Hip site	3.1±3.9
    Major site	8.6±5.7
    Sarcopenia, n (%)	50 (31.4)
    Frailty, n (%)	3 (1.9)
    Oral problem, n (%)	120 (75.5)
    ENT problem, n (%)	60 (37.7)
    Ocular problem, n (%)	85 (53.5)
    Having any symptoms required TTM, n (%)	46 (28.9)

    Abbreviations: ENT, ear nose throat; FRAX, Fracture risk assessment tool; SD, standard deviation; TTM, Thai traditional medicine

    
    

    Additionally, fall risk was evaluated via a three-question screening tool, which has been previously validated among community-dwelling older adults in Thailand and has high sensitivity (93.9%) and specificity (75%).29,30 Fracture risk was assessed via the FRAX score, a globally recognized, web-based algorithm recommended by the World Health Organization and other organizations, including the National Osteoporosis Foundation, to predict future fracture risk.24 The modified version of the MRSA-5 tool used for sarcopenia screening in step 1 is another well-validated tool for the Thai population, offering a sensitivity of 82.6% and a moderate specificity of 43.4%.26 This tool’s effectiveness in identifying individuals at risk for sarcopenia has contributed to its widespread use in geriatric screenings. Similarly, frailty was assessed using the FRAIL scale, which has been validated in the Thai population and has high sensitivity (85.8%) and specificity (80.6%).28 The high sensitivity of these tests is particularly appropriate for the two-step screening process, as they allow for the inclusion of a broad range of at-risk individuals in step 1, who are then further evaluated in step 2 to identify those in need of targeted

    interventions or treatments.31 This approach ensures that the screening process is both comprehensive and efficient, allowing for early identification and timely management of GSs.

    Some of the adapted questionnaires used in the first step of the screening process may exhibit limited efficacy owing to their development by experts on the basis of previously established standard instruments. The malnutrition screening questionnaire in step 1 could lower the sensitivity of the screening process. Adapted from the SPENT Nutrition Screening tool12, the questions focus on more severe symptoms and advanced-stage signs of malnutrition, including a BMI of <18.5 and >30 kg/ m2 and significant weight loss over the preceding three months. Moreover, participants attending the check-up clinic predominantly came from higher socioeconomic backgrounds, where malnutrition is less prevalent.32 As a result, only 9.3% of the participants tested positive for malnutrition during the first step. This finding contrasts with that of a previous study, which reported a 37.8% prevalence of malnutrition risk among older adults in Thailand.33 However, after further assessment in step 2,

    
    

    TABLE 3. Participant outcomes from the comprehensive screening (step 2).

    
    

    Positive screening in Step 2 Values

Cognitive impairment (n =69) Assessment results, n (%)

MCI 28 (40.6)

Significant impairment 25 (36.2)

Test results, point (mean±SD)

Abbreviations: 5TSTS, five times sit-to-stand; BIA, bioelectrical impedance analysis; kg, kilogramme; MCI, mild cognitive impairment; MNA-SF, mini nutritional assessment short-form; MoCA, Montreal cognitive assessment; PHQ, patient health questionnaire; TMSE, Thai mental state examination; TTM, Thai traditional medicine; TUG, timed up and go test; SD, standard deviation

TABLE 4. Participant outcomes from the comprehensive screening (step 2).

Abbreviations: CGCC, comprehensive geriatric check-up clinic; SD, standard deviation

Fig 2. Relationship curve between total satisfaction score and time of service.

98.3% of the participants were confirmed to be at risk of malnutrition or malnourished, demonstrating the high positive predictive value of the step 1 questions. These findings suggest that while the step-one malnutrition screening tool is practical for high-volume clinical settings, its lower sensitivity may necessitate revisions of the incorporation of more sensitive questions to enhance the early detection of at-risk individuals.

The screening for oral health issues, ENT problems, and ocular conditions in step 1 involved the use of expert- designed questionnaires aimed at detecting clinical or urgent symptoms that need further evaluation by specialist clinics. These tools identified oral health problems, ENT issues, and ocular problems in 75%, 37.8%, and 50.6% of the participants, respectively. These results are consistent with those of previous studies. For example, 64% of older adults in the United States were reported to have periodontitis34, whereas ocular issues, particularly visual impairment, affected 20–33% of older adults.35,36 Similarly, ENT problems have been reported to affect 25–50% of this population.37 The results from the step 1 screening in this study align with these previously reported prevalence rates, indicating that these screening questions are likely effective in general clinical practice.

This study highlights the relationship between service time and patient satisfaction, with findings consistent with previous research suggesting that higher satisfaction levels are associated with shorter waiting and service times.38 However, older adults may prioritize interpersonal aspects of care and the thoroughness of assessments over efficiency alone.38,39 The present study aligns with these observations, as the comprehensive screening process employed here provides a holistic evaluation, likely contributing to the overall satisfaction of patients despite the extended service time.

Strengths

Several notable strengths of this study can be identified. First, the check-up clinic’s ability to detect unrecognized GSs before they lead to further deterioration or hospitalization is a substantial advantage. Early detection through comprehensive assessments allows multidisciplinary teams to intervene promptly, thereby preserving the functional capacity and enhancing the quality of life of older adults.40 Second, the large sample size used in the primary data collection phase strengthens the generalizability of the findings, providing robust evidence on the efficacy of geriatric assessments in detecting prevalent yet often overlooked conditions. Third, the

implementation of standardized screening tools across both steps of the service process constitutes a key strength of this study. These validated tools, which adhere to international guidelines and established cutoff points, can be easily replicated in other health care settings, both within Thailand and globally, owing to the availability of translations and the use of standardized instruments. Finally, this study examined service-related metrics, including data collection times, waiting periods, and examination durations, providing valuable quantitative data for enhancing service quality. These metrics can be integrated with patient satisfaction data to inform targeted interventions aimed at improving service delivery.41 By leveraging these data, the service team can optimize both the efficiency of care and the overall patient experience, ensuring that future improvements are data driven and aligned with patient expectations.

Limitations

Some limitations emerged in this study. First, social desirability bias, recall bias, or information bias may have influenced the responses, as participants might have underreported or misremembered relevant details during the self-reported questionnaires. Furthermore, participants may have tended to provide socially desirable responses when completing formal questionnaires.42 Second, the reliance on the adapted version of screening questionnaires in step 1 is important, particularly for malnutrition and cognitive impairment.12,15 Even though these adapted versions are based on previously validated instruments, these questionnaires may alter the sensitivity required for early detection, potentially resulting in the under- or over-detection of at-risk individuals. While practical for high-volume settings, incorporating more validated and sensitive questions could enhance the detection of early-stage conditions. Finally, the specific characteristics of the population at a check-up clinic in a high-volume hospital located in an urban setting may limit the generalizability of the results to rural populations or other health care settings with different demographic profiles and health care access challenges.43 Future research should consider these limitations when designing studies applicable to broader populations.

Clinical implications

The findings from this study have several important implications for clinical practice. First, early detection of GSs through comprehensive geriatric screening can mitigate the progression of these conditions, reducing the need for more intensive health care services and improving overall well-being.44,45 Second, the two-step

comprehensive screening process for older adults offers a replicable model for other health care services. Health care systems can adapt and integrate similar comprehensive screening protocols into their services, particularly those focused on time management and the refinement of questionnaires to fit their specific contexts. Finally, the data on service efficiency and patient satisfaction underscore the importance of streamlining health care delivery without compromising the quality of care. These insights can guide future efforts to optimize service processes, ensuring that care remains both efficient and patient-centered.

CONCLUSION

This study highlights the effectiveness of a two-step comprehensive geriatric screening process in detecting GSs among older adults attending a check-up clinic at a tertiary care hospital. The findings revealed a high prevalence of GSs, including cognitive impairment, fall risk, and oral health issues, highlighting the critical role of early detection and timely intervention. The utilization of standardized screening tools facilitated reliable and consistent assessments, contributing to the reproducibility of the results across different settings. Moreover, despite extended service times, patient satisfaction remained notably high, reflecting the overall quality of care provided. However, this study identified certain limitations in the sensitivity of specific screening instruments, indicating the need for further refinement to improve early detection capabilities. These findings offer important insights into the improvement of geriatric care practices and the optimization of health care service delivery, both within Thailand and globally, through the implementation of structured and efficient screening protocols.

ACKNOWLEDGEMENTS

I would like to express my profound gratitude to the staff and colleagues at the Geriatric Clinic and CGCC at Siriraj Hospital for their invaluable support and assistance throughout the duration of this study. Their expertise and encouragement were instrumental in the successful completion of this research.

DECLARATION

Grants and Funding Information

This project is not funded by any sources.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Author Contributions

Conceptualization and methodology, H.P., and W.M.; Investigation and data collection, S.C., T.V., N.P., P.C., U.V., J.W., A.T., S.T., and A.J.; Formal analysis, H.P., W.M.; Visualization and writing – drafted the original manuscript, H.P.; Writing – review and editing, H.P., W.M.; Supervision, W.M. All authors have read and agreed to the final version of the manuscript.

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‌Effectiveness of Personalized Multifactorial Fall Risk Assessment and Intervention in Reducing Fall Rates Among Older Adults: A Retrospective Study

Piyapat Dajpratham, M.D.1,* , Poungkaew Thitisakulchai, M.D.1, Rinlada Pongratanakul, M.D.1, Rachaporn Prapavanond, M.D.1, Sirapat Haridravedh, M.D.1, Weerasak Muangpaisan, M.D.2

1Department of Rehabilitation Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 2Department of Preventive and

Social Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

*Corresponding author: Piyapat Dajpratham E-mail: piyapat.daj@mahidol.ac.th

Received 30 September 2024 Revised 1 November 2024 Accepted 11 November 2024 ORCID ID:http://orcid.org/0000-0002-6067-0319 https://doi.org/10.33192/smj.v77i1.271422

All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.

INTRODUCTION

Falls and instability among the older people have significant global repercussions, including disability and increased mortality.1 On an individual level, falls often lead to a decline in self-care abilities, reduced independence, and even death, emphasizing their severe impact. Nationally, the economic burden of falls is considerable, with healthcare costs escalating due to hospitalizations and long-term care expenses for fall-related injuries. A 2014 study in the United States estimated that the annual cost of elderly fall care ranges from $68 million to $2.8 trillion, underscoring the substantial financial strain associated with falls.2

A fall is defined as an unexpected and sudden loss of control, causing an individual to collapse to the ground or assume a seated or prone position, typically due to impaired balance.3

To address these challenges, the American Geriatric Society and British Geriatric Society have established guidelines focusing on fall prevention and comprehensive risk assessments for older adults. These guidelines emphasized proactive strategies, including regular evaluations using tools such as the Timed Up and Go Test, the Morse Fall Scale, and the Berg Balance Test.4 Additionally, the CDC’s Stopping Elderly Accidents, Deaths & Injuries (STEADI) Initiative emphasized three key components: Screen, Assess, and Intervene.5 For individuals experiencing recurrent falls or abnormal

gait, thorough assessments by interdisciplinary teams are essential. Evidence-based interventions, such as balance training, muscle strengthening exercises for the hips, knees, and ankles, and joint flexibility exercises were crucial in managing fall risks.6 Additionally, making appropriate modifications to the home environment was recommended to further reduce fall risks among the older people.7,8

At Siriraj Hospital, the Geriatric Rehabilitation Clinic works in conjunction with the geriatric clinic to provide specialized care for individuals aged 70 and older, or those aged 60 and above with cognitive impairments. The clinic focuses on enhancing the functional capacity of older adults at risk of functional decline. Patients with movement or balance issues and a history of falls receive comprehensive, multifactorial fall risk assessments and personalized interventions. This study aimed to investigate the characteristics and fall risk among older patients attending the geriatric rehabilitation clinic. In addition, the incidence of recurrent fall was also examined as an outcome of the fall management interventions in this vulnerable population.

MATERIALS AND METHODS

Study Design

This retrospective study involved a review of medical records from the Geriatric Rehabilitation Clinic at Siriraj Hospital. The research project was reviewed and approved

by the Human Research Ethics Committee of the Faculty of Medicine Siriraj Hospital (Project SI 1003/2020, Code 761/2020 [IRB1]). Authorization to access medical record information was granted by the hospital director.

Participants

We evaluated patients treated at the Geriatric Rehabilitation Clinic for eligibility based on the following inclusion criteria: a history of at least one fall within the past year or walking instability between April 2016 and April 2021, along with abnormal functional mobility tests. Additionally, patients needed to have accessible medical record data from at least one baseline, one follow-up assessment within the year, and one year follow-up visit. Patients were excluded if their data on risk factors, complications from various diseases, functional mobility tests, or dependency status were incomplete at the three specified time points.

Data collection and assessment

Study measurements were recorded at initial and one year follow-up visits. Patients with at least one fall or gait instability underwent a multifactorial fall risk assessment and intervention. This assessment included evaluating various fall risk factors such as comorbidities, medication use (including sedatives and hypnotic drugs), visual and auditory function, cognitive function, frequent urination (≥8 times per day), urinary incontinence (stress, urge, overflow, and mixed incontinence), foot deformities (e.g., hallux valgus, hammer toe, Charcot arthropathy), back/ leg pain, and external factors like home environment and presence of pets. Activities of daily living (ADL) were assessed using the KATZ ADL9 and LAWTON IADL scales.10

Fall history was documented by recording the location and time of each fall. Balance impairments were evaluated using functional mobility tests, including the Timed Up and Go (TUG), Functional Reach, and 30-second Chair Stand tests, with results documented in clinic records. According to the CDC’s STEADI tool,5 a TUG score of 12 seconds or more, a low number of 30-second chair stands based on age groups, and a Functional Reach score of less than 10 inches indicate a fall risk.9

Patients exhibiting abnormal functional mobility tests were scheduled for regular follow-ups, approximately 2-3 times annually. During these visits, they underwent repeat functional mobility assessments and received personalized advice, counseling, exercise recommendations, and environmental adjustments based on the multifactorial fall risk assessment results. Follow-up visits included a comparison of current functional mobility test results with

previous assessments, and patients and their caregivers were provided feedback regarding their performance. Patients were then encouraged to adhere to the recommended interventions, with exercise programs reviewed and adjusted according to each individual’s functional capacity.

Multifactorial fall risk interventions

The Geriatric Rehabilitation Clinic collaborated closely with the geriatric clinic, where geriatricians addressed medical issues that could contribute to falls, such as polypharmacy, postural hypotension, and cardiopulmonary conditions. Physiatrists in the rehabilitation clinic assessed and managed neuro-musculoskeletal issues and other risk factors, including gait and balance impairments, back and leg pain, and foot deformities. For specific conditions like visual or auditory impairments that required further assessment by other specialties, consultations were initiated. Living environments were screened, and necessary adjustments were recommended. Exercise recommendations in our clinic were based on the Otago Exercise Program (OEP), a home-based initiative designed for fall prevention in older adults.11 This program emphasized three key areas: strength, balance, and endurance. Strength and balance training was recommended three days a week, for 15-20 minutes twice daily, while endurance training involved 30 minutes of daily walking, which could be divided into 10-minute sessions throughout the day. These exercise programs were tailored to each patient’s functional status and physical capacity. To ensure proper execution of the exercises at home, patients and their caregivers were instructed on the exercises in the clinic. Clinicians demonstrated each exercise, emphasizing proper technique and safety precautions. For patients who experienced instability during standing or walking, additional support was recommended, such as using their hands for balance while performing the exercises. In terms of enhancing exercise adherence, patients were encouraged to record their exercise sessions using smartphones. This self-monitoring strategy helped reinforce their commitment and allowed clinicians to review the patient’s progress during follow-up visits. For patients who did not use smartphones, written instructions were provided as an alternative. To further ensure adherence and proper execution, caregivers were asked to supervise the patients during their exercise sessions at home. This support from caregivers was vital for reinforcing the routine and providing assistance if needed. As the program was conducted in an outpatient (OPD) setting, our role was to select the appropriate exercises from the OEP, which patients were expected to perform at home. Adherence was closely monitored

through regular follow-up appointments, during which clinicians reviewed the patients’ exercise performance and made any necessary adjustments. We also ensured that all procedures adhered to the Privacy and Data Protection Act (PDPA) of 2019, especially in regard to patients using smartphones to record their exercises.

Data collection and classification

Demographic data, including age, gender, body mass index (BMI), fall risk factors, functional mobility tests, and ADL scores (KATZ ADL and LAWTON IADL), were collected at the initial assessment and again at 12 months. This information was extracted from medical records and entered into a prepared case record form. Participants were initially categorized into two groups: fallers (those with at least one fall in the preceding year) and non-fallers (those without falls). Fallers were further classified into two subgroups: recurrent faller (those with multiple falls) and zero-fall (those with no falls during the follow-up year).

Sample size calculation

The sample size calculation was based on a study involving multifactorial interventions to reduce the risk of falls among elderly individuals living in the community.12 This study indicated an average decrease in recurrent falls of 33%, an acceptable width of 95% confidence interval (24%, 42%). The sample size would be 105 cases.

Statistical analysis

Statistical analyses were performed using PASW Statistics version 18.0 (SPSS Inc., Chicago, IL, USA).13 Descriptive statistics were applied to assess demographic characteristics, fall risk factors, functional mobility test results, and ADL abilities at baseline between fallers and non-fallers. Comparisons were also made between recurrent fall and zero fall groups at the one-year follow- up. Categorical variables, such as gender and the presence of common risk factors, were compared using Chi-square tests, while Fisher’s exact test was used for the number of 30-second chair stands. Continuous data, including age, BMI, number of medications, functional test times, and ADL scores, were compared using independent sample t-tests. Statistical significance was defined as a p-value

< 0.05. Odds ratios with 95% confidence intervals were reported for univariate analyses.

RESULTS

From April 2016 to April 2021, a review of outpatient medical records at the Siriraj Geriatric Rehabilitation Clinic identified 134 patients who underwent multifactorial fall

risk assessment and intervention for falls and unsteady walking. Of these, 18 patients did not return for follow-up, seven were unable to participate due to conditions such as cerebrovascular disease or other serious illnesses, and four missed their follow-up appointments. Therefore, data from 105 patients were included in the final analysis. The cohort was predominantly female (65.5%), with an average age of 81.5 years (SD 6.8) and an average body mass index (BMI) of 22.8 kg/m² (SD 3.2). The most common risk factors were hypertension (82.9%), back or leg pain (81.0%), and cognitive impairment (61.0%). Falls were most frequently reported at home (82.2%) and during the daytime (74.6%).

Participants were divided into two groups based on their fall history over the past year: 84 patients were categorized as Fallers, individuals with a history of falls, while 21 were classified as Non-fallers, individuals with no fall history. Basic demographic and clinical characteristics, including gender, age, BMI, and common risk factors, were provided in Table 1. The Faller group exhibited higher prevalence rates for several factors compared to the Non-faller group. Specifically, pet ownership was more common among Fallers, as was diabetes, frequent urination, foot deformities, and the use of sedating medications. The Fallers also had longer completion times for the TUG test. Most Fallers reported difficulties in performing activities of daily living. No significant differences were observed in the other functional mobility tests between the Faller and Non-faller groups.

After 12 months of follow-up, 27 patients from both groups experienced falls, while 78 patients did not. Among the 84 patients with a history of falls prior to the study, 23 (27.4%) experienced recurrent falls, while 61 (72.6%) did not. The recurrent fall group had significantly higher use of sedating medications compared to the zero-fall group (OR 4.15 [1.5,11.44]; P < 0.05) and this magnitude could be interpreted as large effect size.14 Other risk factors did not show significant differences between the groups. The recurrent fall group was more likely to have hypertension, diabetes, cognitive impairment, foot deformities, and polypharmacy. Additionally, the recurrent fall group took longer to complete the TUG test compared to zero fall group, suggesting a higher fall risk despite improvements since the initial assessment (Table 2).

DISCUSSION

This study explored the characteristics, prevalent risk factors, and functional mobility among older adults attending a geriatric rehabilitation clinic. Our findings indicated that the majority of participants were elderly

TABLE 1. Demographic characteristics, common risk factors, and functional tests of all participants at baseline (N=105).

Data presented as number (%), 1mean ± SD, 2median (Min-Max); *p value< 0.05 indicates statistical significance

females, with hypertension, back and leg pain, cognitive disorders, visual impairment, and frequent urination identified as the most common risk factors for falls, listed in order of prevalence.

Upon comparison of individuals with and without a history of falls at baseline, associations were observed between pet ownership, diabetes mellitus, frequent urination, foot deformities, and the use of sedative medications; however, these associations did not achieve statistical significance. Over the one-year follow-up, we identified significant risk factors for recurrent falls. Specifically, the use of sedative/hypnotic drugs was significantly

associated with recurrent falls, with a prevalence of 65.2% in the recurrent faller group compared to 31.1% in the zero-fall group (OR 4.15[1.5,11.44]; P < 0.05). While cognitive impairment, hypertension, foot deformities, and polypharmacy were more prevalent among recurrent fallers, these factors did not reach statistical significance.

The Timed Up and Go (TUG) test demonstrated that both the faller and recurrent faller groups took longer to complete the test than the non-faller and zero-fall groups. Notably, no significant differences were found in other balance assessments at baseline or at the one- year follow-up. At baseline, 80% of participants reported

TABLE 2. Demographic characteristic, common risk factors, and functional tests of the faller group at 1-year follow-up (N=84).

Data presented as number (%), 1mean ± SD, 2median (Min-Max), *p value< 0.05 indicates statistical significance

having fallen in the previous year, a higher prevalence than observed in other studies, likely attributable to the specialized nature of our clinic. For instance, Assantachai et al. reported a fall prevalence of 19.8% among elderly individuals in urban Thailand over six months,15 which aligned with our findings that high blood pressure, cognitive impairment, and functional difficulties are prevalent among fallers.16

Our results support a recent review indicating that multifactorial fall risk assessment and intervention strategies could effectively reduce fall rates.17 Lee et al. documented a 32% reduction in falls among participants

who received such interventions.16 Additionally, our study highlighted a fourfold increase in the risk of falling associated with sedative medications among recurrent fallers. This finding corroborated the work of Woolcott et al., who identified sedatives as significant contributors to fall risk.18 Various medication categories, including antihypertensives, antiarrhythmics, anticholinergics, antihistamines, and other fall-risk-increasing-drugs, have been linked to heightened fall risk.19-24 Among older patients with comorbidities, cumulative exposure to anticholinergic and sedative medications was associated with poorer performance in multiple gait dimensions,

including slow walking speed and impaired walking balance.25,26

Cognitive decline significantly increased fall risk in older adults due to specific associations between gait parameters and cognitive function.27 In our study, cognitive impairment did not emerge as a statistically significant risk factor for recurrent falls, potentially due to the personalized multifactorial fall risk assessments and interventions including the OEP implemented upon clinic entry. Counseling on home modifications and safety concerns during daily activities was also emphasized, underscoring the effectiveness of home fall-hazard interventions in reducing both fall rates and the number of fallers among high-risk individuals.28 In addition, the OEP has positive effects on motor function in improving neurocognitive function in older adult.29 Hypertension is prevalent in the older population and

is recognized as a risk factor for falls, often necessitating medications that may further exacerbate fall risk.30,31 Orthostatic hypotension, particularly when coupled with hypertension, has been independently associated with an increased risk of future falls. In our study, hypertension was not identified as a significant risk factor for recurrent falls, likely due to the proactive management of medications and efforts to minimize polypharmacy by geriatricians. Although foot deformities were not statistically significant as a risk factor for recurrent falls, they remained a consistent concern among both baseline and recurrent fallers, suggesting that footwear modifications could enhance safety. Cultural factors, such as the Thai preference for barefoot living at home, may contribute to ongoing fall risks. Additionally, diabetes was recognized as a common risk factor that can lead to falls due to complications such as peripheral neuropathy,32 retinopathy, vestibular dysfunction, cognitive impairment and hypoglycemic events associated with insulin use.33 The implementation of diabetic foot problem screening, foot care advice, and appropriate shoe prescriptions in our geriatric rehabilitation clinic may explain the lack of significant association between diabetes and recurrent falls in our

study.

Falls among older adults arise from a complex interplay of risk factors, emphasizing the necessity for comprehensive assessment and intervention strategies to mitigate these risks. The recurrent fall group in our study exhibited poorer balance function, as evidenced by longer TUG completion times compared to the zero-fall group. Both multifactorial and exercise interventions were associated with beneficial outcomes related to fall prevention.34 Given the constraints of time and resources in outpatient settings, some clinicians may opt

to implement only a single strategy. However, network meta-analyses indicated that exercise alone was linked to reductions in fall rates, incidence of fallers, and fall- related fractures compared to usual care.35 A review by Guirguis-Blake et al. supported strength and balance training as effective interventions for older adults with a history of recurrent falls. Promoting such interventions can enhance health, independence, and overall quality of life.36 The OEP has been demonstrated to effectively reduce falls and related injuries while also improving cognitive function, lower limb strength, and balance abilities, which were critical for fall prevention in older adults.37 Additionally, it has shown cost-effectiveness for individuals over 80 years of age.38

This study possessed several strengths, notably demonstrating the benefits of personalized multifactorial fall risk assessments and interventions among high-risk elderly individuals, and showcasing the feasibility of implementing such strategies in an outpatient setting. However, limitations should be acknowledged. Selection bias may have occurred due to the recruitment of participants with a history of falls or gait instability, resulting in a higher fall rate compared to community- based studies. Furthermore, during the COVID-19 pandemic, the utilization of telemedicine for follow- up visits led to the exclusion of 16% of participants who were unable to attend in-person functional mobility tests. Recall bias concerning fall history may also have influenced outcomes and specific interventions. Lastly, this study was conducted within a tertiary care geriatric clinic, where resources for personalized assessments and interventions were available; therefore, the findings may not be generalizable to other care settings. Future research should consider prospective cohort studies with larger sample sizes to address these limitations, facilitate more comprehensive data collection, and strengthen the robustness of study findings.

CONCLUSION

The personalized multifactorial fall risk assessment and intervention reduced the prevalence of falls among older adults from 80% to 27.4%. Sedative medication was identified as a significant factor associated with an increased risk of falls. The majority of falls occurred during the daytime, highlighting the importance of addressing medication-related fall risks and implementing personalized preventive strategies.

ACKNOWLEDGEMENTS

The authors are grateful to Mr.Suthipol Udompunthurak, of the Faculty of Medicine Siriraj

Hospital, Mahidol University, for his help with the statistical analyses. The authors also appreciate the help of Aditya Rana with English language editing.

DECLARATION

Grants and Funding Information

None

Conflict of Interests

The authors declare no conflict of interest.

Authors Contributions

P.D. : conception and design, interpretation of data, revising it critically for important intellectual content; and final approval of the version to be published. P.T.

: acquisition of data, revising it critically for important intellectual content and final approval of the version to be published. R.P. : acquisition of data, revising it critically for important intellectual content and final approval of the version to be published. R.P. : analysis and interpretation of data, drafting the article. S.H. : interpretation of data, drafting the article. W.M. : revising it critically for important intellectual content and final approval of the version to be published.

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22. Seppala LJ, van de Glind EMM, Daams JG, Ploegmakers KJ, de Vries M, Wermelink A, et al. Fall-Risk-Increasing Drugs: a systematic review and meta-analysis: III. others. J Am Med Dir Assoc. 2018;19(4):372.e1-.e8.

23. Seppala LJ, Wermelink A, de Vries M, Ploegmakers KJ, van de Glind EMM, Daams JG, et al. Fall-Risk-Increasing Drugs: a systematic review and meta-analysis: II. psychotropics. J Am Med Dir Assoc. 2018;19(4):371.e11-.e17.

24. Xue L, Boudreau RM, Donohue JM, Zgibor JC, Marcum ZA, Costacou T, et al. Persistent polypharmacy and fall injury risk: the health, aging and body composition study. BMC Geriatr. 2021;21(1):710.

25. Wouters H, Van Campen JP, Kuitert MJ, Kikkert L, Hilmer SN, Taxis K, et al. Anticholinergic and sedative medications and dynamic gait parameters in older patients. Drugs Aging. 2021;38(12):1087-96.

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27. Herrero A, Velilla N, Renedo F. Deterioro cognitivo y riesgo de caída en el anciano [cognitive impairment and the risk of falling in the elderly]. Rev Esp Geriatr Gerontol. 2011;46(6): 311-8.

28. Clemson L, Stark S, Pighills AC, Fairhall NJ, Lamb SE, Ali J, et al. Environmental interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2023;3(3):CD013258.

29. Yang Y, Wang K, Liu H, Qu J, Wang Y, Chen P, Zhang T, Luo J. The impact of Otago exercise programme on the prevention of falls in older adult: A systematic review. Front Public Health. 2022;10:953593.

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‌Depressive Symptoms and Poor Functional Status are Factors Associated with Frailty and Decreased Quality of Life in Thai Older Breast Cancer Survivors

Arpa Satayasanskul, M.D.1, Prasert Assantachai, M.D., MRCP (UK), FRCP2, Suebwong Chuthapisith, M.D., M.Sc., Ph.D., FRCST, FICS3,*, Monthira Thammasalee, B.N.S.2, Thapanee Chimchanwet, B.S.W.3, Suthipol Udompunturak, M.Sc.4

1Geriatric Department, Ratchaphiphat Hospital, Bangkok, Thailand, 2Department of Preventive and Social Medicine, Faculty of Medicine Siriraj

Hospital, Mahidol University, Bangkok, Thailand, 3Division of Head, Neck, and Breast Surgery, Department of Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, 4Research Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

*Corresponding author: Suebwong Chuthapisith E-mail: suebwong.chu@gmail.com

Received 1 October 2024 Revised 3 December 2024 Accepted 5 December 2024 ORCID ID:http://orcid.org/0000-0002-6177-4099 https://doi.org/10.33192/smj.v77i1.271452

All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.

INTRODUCTION

Frailty, characterized by increased vulnerability to endogenous and exogenous stressors, presents significant public health challenges, especially among aging populations. The prevalence of frailty, ranges from 4% to 59% in older adults living in the community, increasing with age and being significantly higher in women than in men.1 This condition imposes substantial risks, including falls, hospitalizations, and increased mortality, amplifying the urgency to effectively address this problem.2,3 The impact of frailty is not only societal, but also personal, worsening quality of life, inducing feelings of loneliness, and imposing significant financial burdens due to escalating care costs.4-6

In the context of breast cancer survivors (BCS), frailty assumes a unique dimension. Previous studies have shown that a substantial proportion of older BCS, particularly those aged 70-79, experience frailty or pre- frailty, highlighting the need for tailored healthcare interventions.7 Additionally, the combination of breast cancer and its treatments further complicates the health aspects of these survivors, affecting not only their physical well-being, but also their mental health and quality of life (QoL).8 Previous research have demonstrated that predictors of psychological well-being among BCS were resilience, stress, and social support.9 However, recent advances in breast cancer therapies have led to treatments that are less aggressive but more effective, potentially

altering the landscape of frailty prevalence and health- related quality of life (HR-QoL) among older BCS.10-13 With the complexities of recent advances in adjuvant endocrine therapy and chemotherapy through intensive therapeutic escalation14, it is challenging in daily clinical practice to deliver comprehensive care to older breast cancer survivors (BCS) who are already suffering from declining cognitive abilities and physical frailty without a comprehensive geriatric assessment.15 However, recent evidence has shown that various types knowledge sharing for geriatric patients are important and can serve as effective tools for increasing patient satisfaction.16 Therefore, a specific study is needed to investigate all associated factors of frailty and HR-QoL, within the context of physical, mental, social, and functional aspects of a comprehensive geriatric assessment.17 Through this exploration, we aim to facilitate targeted interventions and improved healthcare strategies tailored to the unique needs of this

population.

MATERIALS AND METHODS

Ethical issues

The research protocol was approved by the Human Research Ethics Committee of the Faculty of Medicine Siriraj Hospital, Mahidol University (Si 213/2022). The research was also registered through the Thai Clinical Trials Registry (TCTR20230811012).

Participants and sample size

Breast cancer survivors were recruited from the Breast Clinic, Department of Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Thailand. The eligibility criteria included individuals who were 60 years or older, and cancer-free for more than 3 years. Exclusion criteria included communication problems, moderate to severe dementia, end-stage renal disease, or receiving renal replacement therapy, as well as women with cancers other than breast cancer (except non-melanoma skin cancer).

The prevalence of frailty in cancer patients has previously been reported to be 48% (p = 0.48) at a confidence level of 95%, with a margin of error of 6.5% (d = 0.065).18 Using the sample size formula to estimate the proportion of a population, the calculated number of samples was 227. Consequently, 230 subjects were ultimately recruited for the study.

Data collection and assessment

Relevant demographic data, clinical and pathological data, and breast cancer treatment were retrieved from medical records. The variables related to comprehensive geriatric assessment (CGA) were directly evaluated by well-trained research assistants using structured questionnaires. Physical Performance and muscle strength were also measured on site.

Frailty status was diagnosed using the Fried frailty phenotype.19 The cutoff points for each were as follows.

• The grip strength less than 28 kg for men and 18 kg for women

• Unintentional loss of body weight of more than

  4.5 kg in the past year.

• 6-meter walk with gait speed less than 1 m/s.

• Feeling exhausted by 1 or 2 positive questions established by Center for Epidemiology Studies Depression Scale (CES-D)

• Global Physical Activity Questionnaire (GPAQ) less than 20th percentile.

Those who met 1-2 of 5 abnormalities were categorized as pre-frailty, and those with 3 or more abnormalities were categorized as frailty. The Functional Assessment of Cancer Therapy-Breast (FACT-B) was used to assess HR-QoL.20 Individuals with FACT-B scores lower than the 50th percentile were categorized as having a poor HR-QoL. Other important variables included body weight, height, BMI, calf circumferences, Charlson’s comorbidity index21, Mini-Cog test22, Six-item version of the Thai Geriatric Depression Scale (TGDS-6)23, Short- form Mini Nutritional Assessment-Short Form (MNA-

SF)24, Barthel’s index of activities of daily living (iADL)25 and Lawton’s iADL.26

Statistical analysis

The mean with standard deviation (SD) or median (interquartile range) were used for quantitative variables. Qualitative data were presented as numbers and percentage. To compare quantitative variables, Student’s t tests and Mann-Whitney U tests were used for normal and non- normal distribution data, respectively. Chi-square tests or Fisher’s exact tests were used to compare qualitative variables. Stepwise forward logistic regression analysis was used to identify independent factors associated with frailty, poor HR-QoL, and the combination of frailty and poor HR-QoL.

Statistical significance was set at a p-value <0.05. PASW Statistics for Windows, Version 18.0. Chicago: SPSS Inc; 2009, was used for all statistical analysis.

RESULTS

The prevalence of frailty, pre-frailty, and robust groups diagnosed by the Fried frailty phenotype was 16.5%, 47.4%, and 36.1%, respectively. The baseline characteristics of the three groups shown in Table 1.

Almost half of the participants were married (44.3%) and had received education for 12 years or more (70.4%). 17.4% had a history of breast cancer among their first- degree relatives. Invasive ductal carcinoma was the most common pathology (91.2%), followed by intralobular carcinoma, mucinous carcinoma, and malignant phyllodes breast cancer. The staging distribution was as follows: stage 0 (15%), stage 1 (33%), stage 2 (33%), stage 3 (15%), and stage 4 (1.3%). Triple-negative breast cancer (poor prognosis) breast cancer was present in 11.2% of the cases.

Regarding cancer treatment, all of them had undergone surgery, specifically mastectomy in 71.7% and breast-conserving therapy (BCT) in 28.3%. More than half of them received chemotherapy (CMT) (55.1%), while 91.1% had completed CMT. The commonly used chemotherapies were as follows: 60.2% had doxorubicin and cyclophosphamide (AC), 22.8% had their combination with taxane (AC+T), 5.7% had CMT with targeted therapy, and 14% had other regimens such as methotrexate. Among them, 72.2% had received endocrine therapy and 52.6% had received radiotherapy.

Comparisons between the frailty and non-frailty groups are presented in Table 1. Sequentially, the independent factors associated with frailty among BCS were identified by a stepwise forward binary logistic

TABLE 1. Baseline characteristics, and relevant clinical data of the three frailty status groups (n = 230).

Note: The Nonfrailty group comprises individuals from both the pre-frail and frail groups.

* = statistically significant; iADL = index of activities of daily living; GPAQ = Global Physical Activity Questionnaire; TGDS = Thai Geriatric Depression Scale; CES-D = Center for Epidemiology Studies Depression Scale; MNA-SF = Mini Nutritional Assessment-Short Form

regression analysis, as shown in Table 4. Comorbidities assessed by Charlson’s comorbidity index, activities of daily living (Barthel’s index for basic ADL and Lawton’s index for instrumental ADL), depressive symptoms and poor nutritional status were found to be associated with frailty.

Likewise, the comparisons of clinical characteristics between the good and poor HR-QoL groups and the independent factors associated with the poor HR-QoL groups were demonstrated in Table 2 and 4, respectively. The only independent factors associated with poor HR- QoL were depressive symptoms, poor instrumental ADL, and being single. Interestingly, the total FACT-B score for the frailty group (115.95±17.14) was significantly lower than that of the non-frailty group (128.91±11.87), p <0.01. All other subdomains of the FACT-B score of the frailty group were also lower than those of the non- frailty group, as shown in Table 5.

Finally, comparisons of clinical characteristics between those with and without the combination of frailty and poor HR-QoL and the factors independently associated with the combination are shown in Tables 3 and 4, respectively. Again, depressive symptoms and poor Lawton iADL, Barthel index ADL scores, and being single were found to be statistically significant associated factors.

DISCUSSION

Depression increased the risk of frailty through physical inactivity and decreased motivation, which

are commonly observed in depression, leading to a loss of energy and overall functioning.27,28 Depression and frailty are also important risk factors for malnutrition in older adults with cancer.29 Our results revealed an independent association between malnutrition and frailty (Table 4). Some common risk factors for depression and frailty have previously been highlighted, for example, oxidative stress, hypothalamic-pituitary-adrenal axis, and mitochondrial dysregulation.30-32 Our subjects with depressive symptoms had a higher probability of frailty (OR=13.1, 95%CI:4.0-42.7), whereas a meta-analysis in older adults conducted by Soysal et al reported an OR of 4.07 (95%CI 1.93-8.55).33 These findings highlight significantly higher risk of frailty in older adult with breast cancer compared to healthy older adults.(Fig 1) Due to the atypical presentation of depression in older adults, overcoming these barriers and recognizing the impact of depression on cancer outcomes are crucial for improving overall well-being and prognosis in older cancer patients.27,34 Given that depression is a treatable disease and associated with a poor HR-QoL among older BCS, healthcare personnel involved in their care should be aware of these relationships. Integrating depression screening into routine clinical services is essential, as it can reduce risk of frailty, and improve HR-QoL.35 Treatment options for depression include psychotherapy, medication, lifestyle modifications, increased physical activity, and enhanced social support and connection. BCS who reported a higher HR-QoL were able to maintain higher levels of physical activity and the ability

Fig 1. Schematic figure summarizing risk factors related for frailty and poor HR-QoL.

TABLE 2. Comparisons of baseline characteristics, staging, and treatments, as well as relevant clinical data between the good and poor HR-QoL groups.

* = statistically significant; QoL = quality of life; iADL = index of activities of daily living; GPAQ = Global Physical Activity Questionnaire; TGDS = Thai Geriatric Depression Scale; CES-D = Center for Epidemiology Studies Depression Scale; MNA-SF = Mini Nutritional Assessment- Short Form

TABLE 3. Comparisons of baseline characteristics, staging, and treatments, as well as relevant clinical data between those with and without the combination of frailty and poor HR-QoL.

Physical activity (GPAQ)

* = statistically significant; QoL = quality of life; iADL = index of activities of daily living; GPAQ = Global Physical Activity Questionnaire; TGDS = Thai Geriatric Depression Scale; CES-D = Center for Epidemiology Studies Depression Scale; MNA-SF = Mini Nutritional Assessment- Short Form

TABLE 4. Crude and adjusted odds ratios of the independent factors associated with BCS with frailty, poor HR- QoL, and those who had the combination of frailty and poor HR-QoL.

Independent factors associated with frailty and poor HR-QoL

QoL = quality of life; iADL = index of activities of daily living; MNA-SF = Mini Nutritional Assessment-Short Form

TABLE 5. Comparisons of the FACT-B score between the frailty and non-frailty groups.