Mortality Prediction in Multiple Trauma Patients Using GAP, RTS and NTS Models

There are several models to predict the prognosis of trauma patients. The present study aimed to evaluate age, systolic blood pressure (GAP), revised trauma score (RTS), and new trauma score (NTS) to predict mortality rate in multiple trauma patients referring to Imam Reza Hospital, Tabriz, Iran.
The present descriptive-analytical study was carried out on 544 multiple trauma patients from July 2018 to Aug 2019. GAP, RTS, and NTS models were adopted to collect data on the variables. The GAP, RTS, and NTS scores were calculated, and their relationship with hospital outcome was then assessed.
In total, 31 patients out of the selected sample died during the study. The cut-off point (sensitivity and specificity) of RTS, NTS, and GAP models for hospital survival rates was equal to 6.07 (0.97 and 0.98), 5.59 (0.94 and 0.99), and 15.5 (0.97 and 0.97), respectively.  A logistic regression test was run to determine the effects of GCS, GAP, RTS, and NTS models. The results showed that the RTS and NTS scores had the highest value in determining the chances of survival, with the respective odds ratios (OR) of 13.74 and 10.207.
Considering the high sensitivity and specificity of RTS, GAP, and NTS models in determining patient survival rates, these models have good predictive value in determining hospital outcomes. The effect of these models on the patient outcome based on OR values, RTS and NTS models showed high values.