Modification of the Trauma and Injury Severity Score (TRISS) Method Provides Better Survival Prediction in Asian Blunt Trauma Victims

• Published in: World journal of surgery Vol. 36; no. 4; pp. 813 - 818
• Main Authors: Kimura, Akio, Chadbunchachai, Witaya, Nakahara, Shinji
• Format: Journal Article
• Language: English
• Published: New York Springer-Verlag 01-04-2012; Springer‐Verlag; Springer Nature B.V
• Subjects: Abbreviate Injury Scale; Abdominal Surgery; Blunt Trauma; Cardiac Surgery; Female; General Surgery; Glasgow Coma Scale; Humans; Injury Severity Score; Japan; Logistic Models; Male; Medicine; Medicine & Public Health; Middle Aged; Prognosis; Revise Trauma Score; Surgery; Thailand; Thoracic Surgery; Trauma Severity Indices; Vascular Surgery; Wounds, Nonpenetrating - mortality; Thailand; Japan; Revise Trauma Score; Abbreviate Injury Scale; Glasgow Coma Scale; Blunt Trauma; Injury Severity Score
• DOI: 10.1007/s00268-012-1498-z
• EISSN: 1432-2323
• ISSN: 0364-2313

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.