Evaluation of accuracy between GAPs, RTS, and ISS to predict Mortality rate in 24 hours among Traumatic Patients, A single trial study

Abstract

Background: Traffic accident has been a leading cause of death worldwide and there is a difference between the violence and the mortality risk of each casualty. By comparing the GCS-Age-SBP scores (GAPs), the Revised Trauma Score (RTS), and the Injury Severity Score (ISS), for the prediction of casualties within 24 hours to find out which tool is most accurate.

Objective: To compare the accuracy in mortality prediction of casualties from traffic accidents between the GAPs, RTS, and ISS.

Methods: The data of road casualties from Tharongchang Hospital from 1 October 2020 to 30 September 2021 were studied, recorded, and statistically analyzed.

Results: From a total of 1,005 road casualties, 956 patients and 49 patients met the inclusion and exclusion criteria respectively. Most of the casualties were 608 males aged 20 to 60. Most accidents involved motorcycles. A large number of the casualties denied a medical condition or drug use. The level of injury severity was semi-urgency and 933 patients survived. The significant risk factors of death within 24 hours were age, mechanisms of injury, drug abuse, anticoagulants use, underlying disease, and emergency severity index level (P-value < 0.05). 

Of the 956 patients, 99.9% had an RTS of <11 that should be taken to the Trauma center. 95.7% with a GAPS of 19-25 were in the low-risk group, and these patients’ mortality rate was 2.8%. and 92.2% with an ISS of 1-8 suffered minor injuries. When we analyzed by multi-logistic regression, GAPS, and ISS were the best tool for mortality prediction within 24 hours that was statistically significant due to P-value < 0.05

Conclusion: The GAPs were the best tool for mortality prediction within 24 hours which was statistically significant due to an AUC of ROC 0.998, Standard Error of 0.01, and 95% CI 0.995 – 1.000.