External Validation of the Trauma Early Mortality Prediction Tool (TEMPT) in an Iranian Trauma Population.

BACKGROUND

Trauma remains the leading cause of mortality in the first four decades of life globally. Despite advances in trauma care, accurate early mortality prediction remains challenging. The Trauma Early Mortality Prediction Tool (TEMPT) was developed as a simplified scoring system, but its validity in diverse populations requires evaluation.

METHODS

This cross-sectional study analyzed trauma patients admitted to Sina Hospital between 2019 and 2021. TEMPT variables, including age, systolic blood pressure, International Normalized Ratio (INR), Partial Thromboplastin Time (PTT), base excess, temperature, and traumatic brain injury (TBI) presence, were collected retrospectively. Glasgow Coma Scale (GCS) and Injury Severity Score (ISS) were also assessed. Logistic regression and ROC curve analysis compared TEMPT's predictive performance. Of 1,052 eligible patients, 809 (77%) were excluded due to incomplete data, potentially introducing selection bias. The primary outcome was in-hospital mortality.

RESULTS

Of 1,052 eligible patients, complete data were available for 243 patients. The cohort was predominantly male (82.7%), with a mean age of 41.9±18.4 years. Overall mortality was 11.1%. Among TEMPT variables, only age (OR: 1.053, 95% CI: 1.02-1.08, P=0.002) and TBI presence (OR: 5.128, 95% CI: 1.28-20.47, P=0.021) significantly predicted mortality in multivariate analysis. GCS (OR: 0.754, 95% CI: 0.635-0.895, P=0.001) and ISS (OR: 1.042, 95% CI: 1.047-1.164, P<0.001) demonstrated superior predictive accuracy. ROC analysis showed an AUC of 0.586 (95% CI: 0.422-0.750) for TEMPT, 0.847 (95% CI: 0.745-0.949) for GCS, and 0.865 (95% CI: 0.786-0.944) for ISS.

CONCLUSION

TEMPT demonstrated limited external validity in this Iranian trauma population. Traditional scoring systems (GCS and ISS) outperformed TEMPT in mortality prediction. Population-specific validation and potential recalibration of scoring thresholds are essential before implementing TEMPT in diverse healthcare settings.