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Original Article
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Chalothorn Taesilapasathit, M.D.*, Ittikorn Spanuchart, M.D.**, Supawadee Suppadungsuk, M.D.*, Napun
Sutharattanapong, M.D.**, Kotcharat Vipattawat, M.D.***, Sethanant Sethakarun, M.D.***, Kanin ammavaranucupt,
M.D.*
*Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samut Prakan 10540, ailand, **Department
of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, ailand, ***Bhumirajanagarindra Kidney Institute
Hospital, Bangkok 10400, ailand.
Accumulation of Advanced Glycation End Products
Independently Increases the Risk of Hospitalization
Among Hemodialysis Patients
ABSTRACT
Objective: To determine the association between AGE accumulation detected by skin-autouorescence (SAF) and
hospitalization among ESKD patients.
Materials and Methods: 196 ESKD patients from two hemodialysis (HD) units in Bangkok were enrolled in this
retrospective study from November 2015 to March 2016. Before HD treatment, AGEs were measured with the SAF
device on the area with intact skin on the volar surface of the non-stula arm. e study concluded in December
2020, and the number of and causes of hospitalization were reviewed. A logistic regression model was used to
determine the association between SAF level and patient hospitalization.
Results: Of the 196 patients enrolled in the study, SAF was measured in 165 patients with a mean (SD) age of 69.2
(13.0) years. Most of the participants were non-smokers who had hypertension and diabetes and were on high-ux
dialyzers. e average weekly spKt/V was 2.1, and the mean (SD) SAF was 3.05 (0.81) AU. e group with high
SAF consisted of older patients and had a higher proportion of diabetics and smokers, but this was not statistically
signicant when compared to the low SAF group. In the multivariable analysis model, SAF greater or equal to
3.05 AU (OR = 2.28; 95% CI, 1.05–4.94; P < 0.05) and increased age (OR = 1.05; 95% CI, 1.01–1.09; P < 0.05) were
associated with an increased risk of hospitalization.
Conclusion: Higher values of age and SAF were independently associated with increased risk of hospitalization
among ESKD patients.
Keywords: Hospitalization; skin autouorescence; advanced glycation end-products; end-stage kidney disease
(Siriraj Med J 2022; 74: 305-313)
Corresponding author: Kanin ammavaranucupt
E-mail: geng103@hotmail.com
Received 30 January 2022 Revised 13 March 2022 Accepted 14 March 2022
ORCID ID: https://orcid.org/0000-0002-9873-3848
http://dx.doi.org/10.33192/Smj.2022.37
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
End-stage kidney disease (ESKD) is recognized as
one of the leading non-communicable diseases worldwide.
e global prevalence of ESKD patients requiring renal
replacement therapy is estimated to be between 4.9 and
7.1 million
1
, and the total number of aected patients has
been steadily increasing. Progression of chronic kidney
disease (CKD) are associated with an increased risk of
morbidity, mortality, and decreased quality of life.
2,3
Moreover, ESKD causes a substantial nancial burden
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306
on the patients, and its treatment requires an immense
amount of human resources.
4
Compared with the general population and non-
dialysis CKD patients, dialysis patients have higher
hospitalization and in-hospital mortality rates.
5,6
With
the elevated cardiovascular risk that is related to ESKD,
cardiovascular disease (CVD) is the major cause of
hospitalization among these patients.
7
Hospitalization
of ESKD patients is associated with an increased risk of
hospital-acquired infection, malnutrition, depression,
and impaired quality of life, and it oen results in higher
overall costs.
8,9
Strategies for preventing the hospitalization
of ESKD patients are yet to be determined.
In the general population, hypertension, diabetes
mellitus, dyslipidemia, age, and tobacco use are known risk
factors for developing CVD. Non-traditional risk factors
contributing to CVD among patients with ESKD include
anemia, mineral bone disease from the accumulation of
calcium and phosphorous levels, and uremic toxins.
10
In
recent times, greater evidence shows markedly increased
levels of advanced glycation end-products (AGEs) in
ESKD patients, leading to atherosclerosis-one of the
established risk factors for CVD.
11
AGEs are medium-sized uremic toxin molecules
12
that are formed as by-products of non-enzymatic reactions
between the glucose and amino groups in proteins and
nucleic acids. AGEs can also be formed through the
oxidation of lipid-derived intermediates, resulting in
advanced lipid oxidation products.
13,14
Moreover, ingestion
of processed food and smoking habits are exogenous
sources of AGEs. As AGEs are mainly excreted in the urine,
AGE accumulation can be found in patients with ESKD.
AGEs accumulate in tissues and aect protein structures,
leading to the stiness of tissues and blood vessels. Further,
the binding of AGEs to AGE receptors (RAGE) activates
the intracellular transduction mechanisms, resulting in
cytokine release and oxidative stress. ese can cause
further tissue damage and accelerate the atherosclerotic
process.
15,16
Previous studies have reported that AGE
accumulation in tissues is associated with an increased
risk of CVD.
17,18
However, to date, the association between
AGE accumulation and hospitalization has never been
conducted in a formal study.
ere are several techniques of AGE measurement.
Plasma AGEs are easier to detect, but the plasma levels in
patients on dialysis keep uctuating and is less reliable;
this is because dialysis may result in some types of AGEs
being removed.
13
Tissue AGEs can be measured via tissue
biopsy, but the process is invasive, time-consuming,
less specic, and poorly reproducible. Recently, a novel
AGE measurement technique with skin autouorescence
(SAF) has been developed. Compared to other methods,
SAF is non-invasive and reproducible. e tissue levels
measured using this method tend to be more constant
and reliable despite the patient undergoing regular
dialysis.
18,19
To address the gap in the literature, this
study aimed to evaluate the association between tissue
AGE accumulation measured by SAF and the incidence
of all-cause hospitalization among ESKD patients.
MATERIALS AND METHODS
Participants
We enrolled ESKD patients from Ramathibodi
Hospital and Bhumirajanagarindra Kidney Institute
Hospital, Bangkok, ailand. e enrollment period was
from November 2015 to March 2016. e participants aged
18-90 years who had received regular chronic hemodialysis
(HD) for more than one week, signed the informed
consent form, and completed AGE measurements using
the SAF device at the enrollment were included in this
study. e patients were dialyzed twice or thrice weekly
using high-ux HD or hemodialtration. Unfractionated
heparin was administered as an anticoagulant during
HD sessions. Pre-HD blood chemistry was obtained and
processed using a standard central laboratory analyzer.
Patients hospitalized for elective surgery were excluded.
ose participants were followed until December 31
st
,
2020 when the study concluded.
Ethics
e present study was approved by the Human
Research Ethics Committee from the Faculty of Medicine
Ramathibodi Hospital, Mahidol University (the approval
number MURA2021/1052, dated December 29, 2021)
and from Bhumirajanagarindra Kidney Institute Hospital
(the approval number Ref. no. 1/2016, dated January 14,
2016).
Study design
is study was a retrospective cohort study. e
patients’ baseline characteristics, dialysis proles, and
laboratory parameters were collected through interviews and
from their electronic medical records. Patient-identifying
information was removed. e SAF measurements were
performed at the time the participants were initially
enrolled between November 2015 and March 2016.
ose participants were followed until December 31
st
,
2020 for hospitalization events.
Measurement of tissue AGEs
Trained nurses were designated to perform AGE
measurement as standard instruction. Tissue AGEs were
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measured using the skin autouorescence ultraviolet
technique (AGEs reader, DiagnOptics, e Netherlands).
e device has been clinically validated and shown to be
highly correlated with tissue AGEs that are histologically
measured from a skin biopsy.
20
e area with intact skin
on the volar surface of the non-stula arm was examined
while the patient was in a seated position. Blemishes and
hairy areas were avoided. An additional light source was
used for naturally pigmented skin color.
21
Before an HD
treatment session, tissue AGEs were measured three times
consecutively with the SAF device, calculated using the
AGE reader soware, and reported in arbitrary units
(AU). e mean of the three measurements was used
for the statistical analyses. e SAF measurements are
nonoperator-dependent, reliable, not uctuating between
pre- and post-dialysis, and highly reproducible.
18,19
To
the best of our knowledge, there are no standard criteria
for dening high SAF values. erefore, we divided the
patients into two groups, high and low SAF, using the
mean SAF from our study as the cut-o point.
Primary outcome of all-cause hospitalization
e term ‘Hospitalization’ was dened as the event
when the patient was hospitalized due to any causes at least
once except elective surgery. Multiple rehospitalizations
in the same participant would be counted as one.
Statistical analysis
e baseline characteristics of the patients, including
their demographic data, underlying diseases, and laboratory
results, were reported as mean and standard deviation
(SD) or median (interquartile range, IQR) values for
continuous variables and as frequencies (%) for categorical
variables. Student’s t test and the Wilcoxon rank sum
test were used to compare the means and medians of
the two SAF groups, while the chi-square test was used
to analyze the categorical variables.
e event of hospitalization was analyzed using
a logistic regression model from the time of AGE
measurement to the rst hospitalization. To test the
associations between AGE accumulation and ESKD patient
hospitalization, factors that might aect hospitalization
were also analyzed using a logistic regression model
and reported as odds ratios (OR) with a 95% condence
interval (CI). Variables identied by univariate analysis
with P value less than .1 were subsequently analyzed
using a multivariable analysis model.
A scatter diagram was formed to depict hospitalization,
SAF, and any other interesting factors. Two-tailed P values
less than .05 were considered statistically signicant. All
the statistical analyses were performed using IBM SPSS
Statistics for Windows, Version 24.0 (Armonk, NY: IBM
Corp).
RESULTS
Of 196 enrolled, 165 patients met the inclusion
criteria and were included in the study, with a mean (SD)
age of 69.2 (13.0) years. Most of the patients were non-
smokers with hypertension and diabetes. 38% had CVD,
and 9% had cerebrovascular disease (CVA). Most of the
patients were hemodialyzed using a high-ux dialyzer
for 4 hours per HD session. e median dialysis vintage
was 21.0 (range 1-41) months, and the mean (SD) weekly
spKt/V was 2.1 (0.4). e patients’ vascular accesses were
44.2% arteriovenous stula (AVF), 29.1% arteriovenous
gra (AVG), and 26.7% tunneled cued catheter (TCC).
e mean (SD) SAF level was 3.05 (0.81) AU. ere was
no signicant dierence between the characteristics of
patients with SAF less than 3.05 AU and those with SAF
greater or equal to 3.05 AU. e comorbidities, dialysis
proles, and laboratory parameters were similar for both
groups of participants (Table 1).
During the 56-month study period, the total number
of hospitalizations was 410. Of 165, 20 patients (12.1% of
the cohort) had no hospitalization, and 33 patients (20%)
had one hospitalization. e causes of hospitalization
(Fig 2) were infection (37.3%), cardiovascular disease
(22.2%), stroke (2.2%), and malignancy (1.7%). However,
up to 36.6% had no clear documentation regarding the
cause of hospitalization. During the follow-up period,
48 patients died while hospitalized; 22 patients (25%) in
the low SAF group and 26 patients (33.8%) in the high
SAF group. One patient in the low SAF group had died
before hospitalization due to infection.
Univariate analysis (Table 2) showed that patient
hospitalization was associated with dierent vascular
access types, ages, and SAF levels. When compared with
arteriovenous stula (AVF) or arteriovenous gra (AVG),
tunneled cued catheter (TCC) was associated with an
increased risk of hospitalization (OR = 4.49; 95% CI,
1.02–19.77; P = 0.05). Greater patient age was associated
with increased hospitalization (OR = 1.05; 95% CI,
1.02–1.08; P = 0.005). Further, the risk of hospitalization
was higher among patients with SAF greater or equal to
3.05 AU (OR = 4.06; 95% CI, 1.29–12.72; P = 0.02). ese
associations were signicant even aer adjustments for
other covariates. e multiple regression model (Table
2) showed that older age groups and SAF greater or
equal to 3.05 AU were independently associated with an
increased risk of hospitalization, with ORs of 2.28 (95%
CI, 1.05–4.94; P = 0.04) and 1.05 (95% CI, 1.01–1.09;
P = 0.01), respectively. e multiple regression analysis
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TABLE 1. Baseline characteristics stratied by skin autouorescence level.
No. (%)
Characteristics Total SAF<3.05AU SAF≥3.05AU P value*
(N = 165) (n = 88) (n = 77)
Age, mean (SD), y 69.2 (13.0) 68.0 (13.7) 70.4 (12.2) 0.24
Female 96 (58.1) 51 (57.9) 45 (58.4) 0.95
Body mass index, mean (SD), kg/m
2
22.4 (4.3) 22 (4.6) 22.8 (3.9) 0.23
Bodyweight, mean (SD), kg 57.3 (12.4) 56.7 (12.9) 57.9 (11.9) 0.56
Height, mean (SD), cm 159.7 (8.2) 160.4 (8.5) 159 (8.0) 0.27
Hypertension 157 (95) 83 (94) 74 (96) 0.59
Diabetes 95 (57.6) 48 (54.5) 47 (61.0) 0.40
Smoker 32 (19.3) 15 (17) 17 (22) 0.42
Coronary artery disease 54 (38) 28 (32) 26 (38) 0.79
Cerebrovascular disease 15 (9) 8 (9) 7 (9) 0.98
Dialysis vintage, median (IQR), mo 21 (20) 21 (19.2) 27 (21.5) 0.15
Residual urine volume, median (IQR), mL 0 (1100) 0 (1110) 0 (1170) 0.52
Vascular access 0.95
AVF 73 (44.2) 40 (45.4) 33 (42.9)
AVG 48 (29.1) 25 (28.4) 23 (29.8)
TCC 44 (26.7) 23 (26.2) 21 (27.3)
Hemodialtration 21 (12.7) 11 (12.5) 10 (13) 0.93
3 times/week dialysis 76 (46) 39 (44.3) 37 (48) 0.63
Time, mean (SD), min 239.2 (4.8) 239.2 (4.9) 239.2 (4.8) 0.98
Hemoglobin, mean (SD), g/dL 11 (1.4) 11 (1.5) 11 (1.3) 0.98
HbA1C, mean (SD), % 6 (5.6) 6 (1.3) 6 (1.1) 0.80
Serum albumin, mean (SD), g/dL 3.7 (0.4) 3.8 (0.4) 3.7 (0.4) 0.40
Serum calcium, mean (SD), mg/dL 9.2 (0.7) 9.2 (0.7) 9.2 (0.7) 0.57
Serum phosphorus, mean (SD), mg/dL 4.6 (1.4) 4.6 (1.4) 4.6 (1.3) 0.90
Serum iPTH, median (IQR), pg/mL 355 (452.9) 382.5 (510.5) 353.0 (366.8) 0.24
Serum B
2
-microglobulin, mean (SD), ug/mL 31.2 (10.2) 31.7 (9.7) 30.7 (10.8) 0.57
hsCRP, median (IQR), mg/L 0.16 (0.5) 0.17 (0.51) 0.15 (0.54) 0.63
spKt/V, mean (SD) 2.1 (0.4) 2.1 (0.4) 2.1 (0.4) 0.86
nPCR, mean (SD) 1 (0.3) 1 (0.3) 1 (0.3) 0.61
Abbreviations: AVF; arteriovenous stula, AVG; arteriovenous gra, hsCRP; high sensitivity C-reactive protein, iPTH; intact parathyroid
hormone, nPCR; normalized protein catabolic rate, SAF; skin autouorescence, spKt/V; single-pool Kt/V, TCC; tunneled cued catheter.
* Signicance threshold, P < .05
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revealed no association between vascular access type and
hospitalization (OR = 2.70; 95% CI, 0.58–12.61; P = 0.21).
According to our results, SAF is an independent factor
associated with the primary endpoint of hospitalization
even aer adjustment for age and vascular access types.
e AUROC of SAF for prediction of hospitalization was
0.70 (95% CI, 0.566-0.825). e sensitivity was 50.3% and
the specicity was 80%. e scatter plot of SAF-stratied
hospitalization and age (Fig 3) shows that increased SAF
levels in ESKD patients are associated with hospitalization.
196 Patients were enrolled.
31 Patients were unable to obtain complete SAF results.
165 Patients obtained complete SAF results and were included.
Abbreviation: SAF; skin autouorescence
Fig 1. Flow chart shows that 196 patients were eligible for the study, and SAF was measured for 165 patients.
Cardiovascular
disease
22.2%
Infection
37.3%
Malignancy
1.7%
Stroke
2.2%
Others
36.6%
Causes of Hospitalization (N=410)
Fig 2. Causes of hospitalization.
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TABLE 2. Univariate and multiple logistic regression analyses of factors associated with hospitalization among
hemodialysis cohort.
Hospitalization
Risk factor Univariate Multivariate‡
OR (95% CI) P value* OR (95% CI) P value*
Vascular access
AVF/AVG 1.00 [Reference] NA 1.00 [Reference] NA
TCC 4.49 (1.02–19.77) 0.05 2.70 (0.58–12.61) 0.21
Age 1.05 (1.02–1.08) 0.005* 1.05 (1.01–1.09) 0.01†
SAF ≥ 3.05 AU 4.06 (1.29–12.72) 0.02* 2.28 (1.05–4.94) 0.04†
Female 1.03 (0.44–2.38) 0.95
Body weight 0.98 (0.95–1.01) 0.22
Height 0.76 (0.17–3.40) 0.72
Body mass index 0.94 (0.86–1.03) 0.19
Hypertension 2.46 (0.62–9.76) 0.20
Diabetes 1.06 (0.45–2.46) 0.90
Smoker 0.69 (0.27–1.77) 0.44
Coronary artery disease 1.32 (0.52–3.34) 0.56
Dialysis vintage 0.99 (0.98–1.00) 0.25
Residual urine volume 1.00 (0.99–1.00) 0.24
Hemodialtration 3.73 (0.48–28.92) 0.21
3 times/week dialysis 0.85 (0.37–1.97) 0.71
Hemoglobin 0.87 (0.65–1.16) 0.34
HbA1C 0.90 (0.66–1.22) 0.49
Serum calcium 1.10 (0.60–2.02) 0.75
Serum phosphorus 1.06 (0.78–1.44) 0.71
Serum albumin 0.79 (0.26–2.34) 0.66
Serum iPTH 1.00 (0.99–1.00) 0.38
Serum B
2
-microglobulin 0.97 (.092–1.01) 0.11
hsCRP 0.88 (0.59–1.31) 0.53
spKt/V 1.57 (0.53–4.61) 0.41
nPCR 1.53 (0.39–5.90) 0.54
Abbreviations: AVF; arteriovenous stulae, AVG; arteriovenous gra, CI; condence intervals, HbA1C; hemoglobin A1c, hsCRP; high
sensitivity C-reactive protein, iPTH; intact parathyroid hormone, NA; not applicable, nPCR; normalized protein catabolic rate, OR; odds
ratio, SAF; skin autouorescence, spKt/V; single-pool Kt/V, TCC; tunneled cued catheter.
* Signicance threshold, P < 0.05
‡ Adjusted for age, vascular access, SAF.
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Fig 3. Scatter plot for the hospitalization of ESKD patients stratied by SAF level and age
Abbreviations: ESKD; end-stage kidney disease, SAF; skin autouorescence.
DISCUSSION
To our knowledge, plasma AGE concentrations
uctuate from one dialysis treatment to another and
are aected by dietary intake. In contrast, tissue AGE
concentration is relatively constant and likely reects
the chronically elevated plasma AGE level.
22
SAF measurements, representing tissue AGE
accumulation, have been reported to be reliable markers
of AGEs and independently associated with overall and
cardiovascular mortality among ESKD patients of all
ethnicities.
21
Elevated tissue AGEs are associated with
advanced age, diabetes, smoking, and inammatory
states. e baseline characteristics of the patients in the
present study (Table 1) showed no dierence between the
higher and lower SAF groups in terms of age, diabetes,
smoking status, serum albumin, or CRP, a surrogate
marker of inammation.
e multivariable analysis revealed that SAF level and
age are independently associated with hospitalization. e
age factor was in agreement with previous studies.
10,23,24
is study reinforces that AGE levels greater or equal to
3.05 AU, measured using SAF, constitute an independent
factor associated with an increased risk of hospitalization.
While TCC utilization was found to be associated with an
increased risk of hospitalization in the univariate analysis
model, the eect became statistically insignicant when
analyzed in the nal multivariable analysis model. is
might be due to a preference for using TCC over AVF
or AVG in elderly patients with higher risk of CVD or
with limited life expectancy.
In this study, the most common causes of hospitalization
were infection and cardiovascular disease. Previous
studies have indicated that AGE accumulation might
increase a patient’s susceptibility to infection. Previous
observation studies also suggest that AGEs might attenuate
the activation of the NLRP3 inammasome in bone
marrow-derived macrophages. Besides, AGEs might
dampen innate immune responses, including NLRP3
inammasome activation and type-I interferon production
in macrophages upon infection.
25,26
erefore, AGEs could
impair host NLRP3 inammasome–mediated innate
immune defenses against infection. AGE accumulation not
only induces immune system dysregulation but also leads
to endothelial dysfunction, arterial stiness, myocardial
changes, and atherosclerosis progression.
27
Previous
studies have reported that tissue AGE accumulation
measured by SAF is associated with higher prevalence
of cardiovascular events, cardiovascular mortality, and
all-cause mortality among non-dialysis and dialysis
CKD patients.
28
This evidence supports the present
study’s result of CVD being the second most common
cause of hospitalization. us, this study emphasizes
that high SAF is an independent risk factor for patient
hospitalization.
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Interestingly, our results showed that the plasma
levels of beta-2-microglobulin, one of the middle-molecule
uremic toxins similar to AGEs, in the higher and lower
SAF did not dier. is discordance between the plasma
beta-2-microglobulin level and the tissue AGE level
measured by SAF could be from the following reasons.
First, plasma uremic toxins could generally be removed
with HD more than those accumulated in the tissue.
29
e same principle applies to HD clearance of plasma
beta-2-microglobulin compared to tissue AGEs. Second,
dierent kinds of uremic toxins might have dierent HD
clearance properties, even only plasma uremic toxins are
considered. Compared to plasma beta-2-microglobulin,
plasma AGEs are marginally removed, despite the utilization
of a high ux dialyzer or increased dialysate ow rate,
given their higher molecular weight of greater than 12 kDa
and higher binding anity to protein. ese techniques
would not provide any signicant eect on the clearance
of the solutes.
30-32
Moreover, ingestion of a particular type
of food can further increase the accumulation of AGEs
whereas beta-2-microglobulin has a lesser correlation
with the dietary factor.
33
Accordingly, measuring AGEs by SAF in ESKD patients
may have several clinical applications, including prognosis
prediction and possible SAF lowering interventions,
such as AGE-rich diet restriction, oral AGE-adsorbent
use, or hemodialtration. According to our result of the
positive association between tissue AGE accumulation
and all-cause hospitalization, this may open an avenue
for future research in AGE lowering intervention.
To the best of our knowledge, this is the rst study
that showed the association between AGEs accumulation
and hospitalization in ESKD patients. Also, this is the rst
study that applied SAF to determine dialysis adequacy in
ai populations. Moreover, this study had a long follow-
up period to determine study outcome of hospitalization.
However, our study has some limitations. First, this
study consisted of a retrospective cohort with a small
sample size. Second, since all the participants were of
the Asian ethnicity, the results cannot be generalized
to the overall population. ird, as the SAF principle is
based on the interaction of ultraviolet radiation (UV)
irradiation with the AGE chromophore in skin, dierent
skin types may result in dierent SAF ndings. Our study
was conducted with ai patients who normally have
Fitzpatrick skin type IV-V, which represents a certain
degree of skin pigmentation in response to UV exposure.
us, our SAF ndings may not be applicable to other
skin types. Fourth, the SAF cuto considered was based
on the mean SAF value of the study cohort, which may
limit the generalizability of results to other ESKD patients.
Although classifying the SAF outcome by tertile or quartile
is a standard method for non-established cut-o point
variable, our study is the early stage with the modest
sample size. By this method, the number of sample size
in each group is small. Further prospective study in larger
number of participants would be appropriate. Last, a
large proportion of unidentied causes of hospitalization
(36.6%) due to poor documentation in our study might
aect the reported outcome.
Although SAF was shown to be an independent risk
factor for hospitalization in this study, we can only report
an association between increased SAF and hospitalization,
not the causality. Nevertheless, our results and AGE
measurements by SAF in ai patients can be considered
as preliminary data that would be benecial for future
research.
CONCLUSION
e present study revealed that SAF, as a measurement
of tissue AGE deposition, is an independent factor associated
with an increased risk of hospitalization.
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