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. 2023 Nov-Dec;45(6):340-351.
doi: 10.1097/JHQ.0000000000000402. Epub 2023 Aug 18.

Diagnostic Accuracy of a Trauma Risk Assessment Tool Among Geriatric Patients With Crash Injuries

Diagnostic Accuracy of a Trauma Risk Assessment Tool Among Geriatric Patients With Crash Injuries

Oluwaseun John Adeyemi et al. J Healthc Qual. 2023 Nov-Dec.

Abstract

The Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) is a risk stratification tool. We evaluated the STTGMA's accuracy in predicting 30-day mortality and the odds of unfavorable clinical trajectories among crash-related trauma patients. This retrospective cohort study (n = 912) pooled adults aged 55 years and older from a single institutional trauma database. The data were split into training and test data sets (70:30 ratio) for the receiver operating curve analysis and internal validation, respectively. The outcome variables were 30-day mortality and measures of clinical trajectory. The predictor variable was the high-energy STTGMA score (STTGMAHE). We adjusted for the American Society of Anesthesiologists Physical Status. Using the training and test data sets, STTGMAHE exhibited 82% (95% CI: 65.5-98.3) and 96% (90.7-100.0) accuracies in predicting 30-day mortality, respectively. The STTGMA risk categories significantly stratified the proportions of orthopedic trauma patients who required intensive care unit (ICU) admissions, major and minor complications, and the length of stay (LOS). The odds of ICU admissions, major and minor complications, and the median difference in the LOS increased across the risk categories in a dose-response pattern. STTGMAHE exhibited an excellent level of accuracy in identifying middle-aged and geriatric trauma patients at risk of 30-day mortality and unfavorable clinical trajectories.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1:
Figure 1:
Receiver Operating Curves generated from STTGMAHE, ASA-PS, and STTGMAHE+ASA-PS Predicted Probabilities of 30-day Mortality Using the Training (n=638) and Test Datasets (n=274)

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