Predicting Outcomes of Penetrating Cardiovascular Injuries at a Rural Center by Different Scoring Systems

Abstract

Objective: To compare the anatomical and physiological scoring systems and the outcomes of surgical management of penetrating cardiovascular trauma at a rural center. Methods: Seventy-seven patients underwent emergency surgery at our center between January/2012 and October/2018 due to penetrating cardiovascular trauma. Injury Severity Score (ISS), Revised Trauma Score (RTS), New Injury Severity Score (NISS), and Trauma and Injury Severity Score (TRISS) were calculated. The validation of these risk scores to predict mortality was assessed by the area under the receiver operating characteristic curve analysis. Results: All trauma scores were correlated with mortality. As ISS, NISS, and TRISS values increased and RTS values decreased, the mortality rate increased. The area under the curve (AUC) in the receiver operating characteristic curve analysis was 0.943 for TRISS, 0.915 for RTS, 0.890 for ISS, and 0.896 for NISS (P<0.001 for each). Logistic regression analysis revealed that scores were correlated with mortality (P<0.001 for each). By investigating cardiac injuries alone, only TRISS and RTS results correlated with mortality for cardiac injuries (Mann-Whitney U test, P=0.003 and P=0.01, respectively). The AUC was only statistically significant for TRISS and RTS (AUC=0.929, P<0.05 for both). For vascular injuries, all the scores were significantly correlated with in-hospital mortality (Mann-Whitney U test, P<0.001 for each). TRISS had the highest AUC (AUC=0.946, P<0.001). Conclusion: TRISS has the highest predictivity for in-hospital mortality in patients with penetrating cardiovascular trauma.

Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study

“…Otherwise, little has previously been known regarding RCWS predictive ability for mortality. In non-conflict settings better predictive abilities for KTS and RTS regarding mortality following weapon-related injuries have been reported [ 36 , 37 ]. The worse predictive ability observed in our study could be explained by the survival bias where patients with the most altered vital signs die before reaching the hospital.…”