Yonsei Med J.  2016 May;57(3):728-734. 10.3349/ymj.2016.57.3.728.

The Applicability of Trauma and Injury Severity Score for a Blunt Trauma Population in Korea and a Proposal of New Models Using Score Predictors

Affiliations
  • 1Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea. jake98@daum.net
  • 2Ajou Regional Trauma Center, Ajou University Hospital, Suwon, Korea.

Abstract

PURPOSE
The purpose of this study was to verify the utility of existing Trauma and Injury Severity Score (TRISS) coefficients and to propose a new prediction model with a new set of TRISS coefficients or predictors.
MATERIALS AND METHODS
Of the blunt adult trauma patients who were admitted to our hospital in 2014, those eligible for Korea Trauma Data Bank entry were selected to collect the TRISS predictors. The study data were input into the TRISS formula to obtain "probability of survival" values, which were examined for consistency with actual patient survival status. For TRISS coefficients, Major Trauma Outcome Study-derived values revised in 1995 and National Trauma Data Bank-derived and National Sample Project-derived coefficients revised in 2009 were used. Additionally, using a logistic regression method, a new set of coefficients was derived from our medical center's database. Areas under the receiver operating characteristic (ROC) curve (AUC) for each prediction ability were obtained, and a pairwise comparison of ROC curves was performed.
RESULTS
In the statistical analysis, the AUCs (0.879-0.899) for predicting outcomes were lower than those of other countries. However, by adjusting the TRISS score using a continuous variable rather than a code for age, we were able to achieve higher AUCs [0.913 (95% confidence interval, 0.899 to 0.926)].
CONCLUSION
These results support further studies that will allow a more accurate prediction of prognosis for trauma patients. Furthermore, Korean TRISS coefficients or a new prediction model suited for Korea needs to be developed using a sufficiently sized sample.

Keyword

Injury Severity Score; Korea; trauma; trauma centers

MeSH Terms

Adolescent
Adult
Aged
Databases, Factual
Female
Humans
*Injury Severity Score
Logistic Models
Male
Middle Aged
Predictive Value of Tests
Probability
Prognosis
ROC Curve
Republic of Korea
Trauma Centers/statistics & numerical data
*Trauma Severity Indices
Wounds, Nonpenetrating/*diagnosis

Figure

  • Fig. 1 A diagram of the patients' enrollment. KTDB, Korea Trauma Data Bank.

  • Fig. 2 Receiver operating characteristic curves for the TRISS models from each database. TRISS, Trauma and Injury Severity Score; MTOS, Major Trauma Outcome Study; NTDBc, National Trauma Data Bank-complete; NTDBi, NTDB-imputed; NSPc, National Sample Project-complete; NSPi, NSP-imputed; ATDB, Ajou Trauma Data Bank.

  • Fig. 3 Receiver operating characteristic curves for MTOS, ATDB, and modified TRISSs. MTOS, Major Trauma Outcome Study; ATDB, Ajou Trauma Data Bank; mTRISS, modified Trauma and Injury Severity Score.


Cited by  1 articles

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Jonghwan Moon, Kyungjin Hwang, Dukyong Yoon, Kyoungwon Jung
Acute Crit Care. 2020;35(2):102-109.    doi: 10.4266/acc.2019.00780.


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