M-study from an urban trauma center in Tokyo

Modification of the Trauma and Injury Severity Score (TRISS) method provides better survival prediction in Asian blunt trauma victims

BACKGROUND

The objective of the present study was to identify logistic regression models with better survival prediction than the Trauma and Injury Severity Score (TRISS) method in assessing blunt trauma (BT) victims in Japan and Thailand. An additional aim was to demonstrate the feasibility of probability of survival (Ps) estimation without respiratory rate (RR) on admission, which is often missing or unreliable in Asian countries.

METHODS

We used BT patient data (n = 15,524) registered in the Japan Trauma Data Bank (JTDB, 2005-2008). We also extracted data on BT patients injured in the Khon Kaen District between January 2005 and December 2008 (n = 6,411) from the Khon Kaen Hospital Trauma Registry. For logistic regression analyses, we chose the Injury Severity Score (ISS), age year (AY), Glasgow Coma Scale (GCS) score, systolic blood pressure (SBP), RR, and their coded values (c) as explanatory variables, as well as the Revised Trauma Score (RTS). We estimated parameters by the method of maximum likelihood estimation, and utilized Akaike's Information Criterion (AIC), the area under the receiver operating characteristic curve (AUROCC), and accuracy for model comparison. A model having the lower AIC is considered to be the better model.

RESULTS

The AIC of the model using AY was lower than that of the model using the coded value for AY (cAY) (used by the TRISS method). The model using ISS, AY and cGCS, cSBP, and cRR instead of the RTS demonstrated the lowest AIC in both data groups. The same trend could be observed in the AUROCCs and the accuracies. In the Khon Kaen data, we found no additional reduction of the AIC in the model using the cRR variable compared to the model without cRR.

CONCLUSIONS

For better prediction of Ps, the actual number of the AY should be used as an explanatory variable instead of the coded value (used by the TRISS method). The logistic regression model using the ISS, AY, and coded values of SBP, GCS, and RR estimates the best prediction. Information about RR seems to be unimportant for survival prediction in BT victims in Asian countries.

Analysis of Trauma Outcome Using the TRISS Method at a Tertiary Care Centre in Pune

Out of the various systems used to assess the outcome of polytrauma patients, trauma and injury severity score (TRISS) is considered as the standard tool for evaluating the performance of trauma centres. The present study was carried out to evaluate the outcome of severely injured patients using the TRISS method in a developing country like India and to compare it with the major trauma outcome study (MTOS). A prospective study of 300 patients of trauma was done. Outcome assessment was done for the severely injured patients using the TRISS method. Road traffic accidents (213 cases) were the most common cause of injury. Fifty-seven (19%) cases were severely injured defined as having an injury severity score ≥16. Outcome assessment was done for these patients using the TRISS method. The predicted mortality was 15.7%, while the observed mortality was 33.3%. The mean revised trauma score was 6.63 ± 1.79 and the mean injury severity score (ISS) was 23.7 ± 8.17. Compared to the MTOS, the patients in the present study had more severe injuries with higher mortality. The present method of comparison of trauma care, i.e. TRISS which uses the MTOS coefficients, does not accurately predict survival of trauma patients in the developing countries as indicated by the present and other studies. There is a need for developing a national trauma registry to derive new coefficients for trauma scoring for the Indian subcontinent so that the quality of trauma care can be compared with that in the developed countries.