The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems
Background: Injury severity scoring systems that quantify and predict trauma outcomes have not been established in Korea. This study was designed to determine the best system for use in the Korean trauma population. Methods: We collected and analyzed the data from trauma patients admitted to our ins...
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| Format: | Article |
| Language: | English |
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Korean Society of Critical Care Medicine
2016-08-01
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| Series: | Korean Journal of Critical Care Medicine |
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| Online Access: | http://www.kjccm.org/upload/pdf/kjccm-2016-00486.pdf |
| _version_ | 1818512641394475008 |
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| author | Kyoungwon Jung John Cook-Jong Lee Rae Woong Park Dukyong Yoon Sungjae Jung Younghwan Kim Jonghwan Moon Yo Huh Junsik Kwon |
| author_facet | Kyoungwon Jung John Cook-Jong Lee Rae Woong Park Dukyong Yoon Sungjae Jung Younghwan Kim Jonghwan Moon Yo Huh Junsik Kwon |
| author_sort | Kyoungwon Jung |
| collection | DOAJ |
| description | Background: Injury severity scoring systems that quantify and predict trauma outcomes have not been established in Korea. This study was designed to determine the best system for use in the Korean trauma population. Methods: We collected and analyzed the data from trauma patients admitted to our institution from January 2010 to December 2014. Injury Severity Score (ISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) were calculated based on the data from the enrolled patients. Area under the receiver operating characteristic (ROC) curve (AUC) for the prediction ability of each scoring system was obtained, and a pairwise comparison of ROC curves was performed. Additionally, the cut-off values were estimated to predict mortality, and the corresponding accuracy, positive predictive value, and negative predictive value were obtained. Results: A total of 7,120 trauma patients (6,668 blunt and 452 penetrating injuries) were enrolled in this study. The AUCs of ISS, RTS, and TRISS were 0.866, 0.894, and 0.942, respectively, and the prediction ability of the TRISS was significantly better than the others (p < 0.001, respectively). The cut-off value of the TRISS was 0.9082, with a sensitivity of 81.9% and specificity of 92.0%; mortality was predicted with an accuracy of 91.2%; its positive predictive value was the highest at 46.8%. Conclusions: The results of our study were based on the data from one institution and suggest that the TRISS is the best prediction model of trauma outcomes in the current Korean population. Further study is needed with more data from multiple centers in Korea. |
| first_indexed | 2024-12-10T23:49:45Z |
| format | Article |
| id | doaj.art-099d8ce0ce054ab7aafb697da083097d |
| institution | Directory Open Access Journal |
| issn | 2383-4870 2383-4889 |
| language | English |
| last_indexed | 2024-12-10T23:49:45Z |
| publishDate | 2016-08-01 |
| publisher | Korean Society of Critical Care Medicine |
| record_format | Article |
| series | Korean Journal of Critical Care Medicine |
| spelling | doaj.art-099d8ce0ce054ab7aafb697da083097d2022-12-22T01:28:49ZengKorean Society of Critical Care MedicineKorean Journal of Critical Care Medicine2383-48702383-48892016-08-0131322122810.4266/kjccm.2016.004861039The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring SystemsKyoungwon Jung0John Cook-Jong Lee1Rae Woong Park2Dukyong Yoon3Sungjae Jung4Younghwan Kim5Jonghwan Moon6Yo Huh7Junsik Kwon8 Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, KoreaBackground: Injury severity scoring systems that quantify and predict trauma outcomes have not been established in Korea. This study was designed to determine the best system for use in the Korean trauma population. Methods: We collected and analyzed the data from trauma patients admitted to our institution from January 2010 to December 2014. Injury Severity Score (ISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) were calculated based on the data from the enrolled patients. Area under the receiver operating characteristic (ROC) curve (AUC) for the prediction ability of each scoring system was obtained, and a pairwise comparison of ROC curves was performed. Additionally, the cut-off values were estimated to predict mortality, and the corresponding accuracy, positive predictive value, and negative predictive value were obtained. Results: A total of 7,120 trauma patients (6,668 blunt and 452 penetrating injuries) were enrolled in this study. The AUCs of ISS, RTS, and TRISS were 0.866, 0.894, and 0.942, respectively, and the prediction ability of the TRISS was significantly better than the others (p < 0.001, respectively). The cut-off value of the TRISS was 0.9082, with a sensitivity of 81.9% and specificity of 92.0%; mortality was predicted with an accuracy of 91.2%; its positive predictive value was the highest at 46.8%. Conclusions: The results of our study were based on the data from one institution and suggest that the TRISS is the best prediction model of trauma outcomes in the current Korean population. Further study is needed with more data from multiple centers in Korea.http://www.kjccm.org/upload/pdf/kjccm-2016-00486.pdfKoreainjury severity scoremortalitypredictiontrauma centersoutcomes |
| spellingShingle | Kyoungwon Jung John Cook-Jong Lee Rae Woong Park Dukyong Yoon Sungjae Jung Younghwan Kim Jonghwan Moon Yo Huh Junsik Kwon The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems Korean Journal of Critical Care Medicine Korea injury severity score mortality prediction trauma centers outcomes |
| title | The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems |
| title_full | The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems |
| title_fullStr | The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems |
| title_full_unstemmed | The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems |
| title_short | The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems |
| title_sort | best prediction model for trauma outcomes of the current korean population a comparative study of three injury severity scoring systems |
| topic | Korea injury severity score mortality prediction trauma centers outcomes |
| url | http://www.kjccm.org/upload/pdf/kjccm-2016-00486.pdf |
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