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Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes
Various assessment methods based on the International Classification of Diseases, Tenth Edition, Clinical Modification (ICD-10-CM), such as ICD-10-CM Injury Severity Score (ICISS), trauma mortality prediction model (TMPM-ICD10), and injury mortality prediction (IMP-ICDX), are purely anatomic trauma...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351923/ https://www.ncbi.nlm.nih.gov/pubmed/35945731 http://dx.doi.org/10.1097/MD.0000000000029714 |
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author | Zhang, Guohu Wang, Muding Cong, Degang Zeng, Yunji Fan, Wenhui |
author_facet | Zhang, Guohu Wang, Muding Cong, Degang Zeng, Yunji Fan, Wenhui |
author_sort | Zhang, Guohu |
collection | PubMed |
description | Various assessment methods based on the International Classification of Diseases, Tenth Edition, Clinical Modification (ICD-10-CM), such as ICD-10-CM Injury Severity Score (ICISS), trauma mortality prediction model (TMPM-ICD10), and injury mortality prediction (IMP-ICDX), are purely anatomic trauma assessment, which need to be further improved. Traumatic injury mortality prediction (TRIMP-ICDX) is a comprehensive assessment method based on anatomic injuries and incorporating available information to determine whether it is superior to Trauma and Injury Severity Score (TRISS) and IMP-ICDX in predicting trauma outcomes. This retrospective cohort study was based on data from 704,287 trauma patients admitted to 710 trauma centers in the National Trauma Data Bank of the United States in 2016. The TRIMP-ICDX was established using anatomical injury, physiological reserves, and physiological response indicators. Its performance was compared with the IMP-ICDX and TRISS by examining the area under the receiver operating characteristic curve (AUC), calibration (Hosmer-Lemeshow goodness-of-fit test, HL), and the Akaike information criterion (AIC). The TRIMP-ICDX showed significantly better discrimination (AUC(TRIMP-ICDX) 0.968; 95% confidence interval (CI), 0.966–0.970, AUC(TRISS) 0.922; 95% CI, 0.918–0.925, and AUC(IMP-ICDX) 0.894; 95% CI, 0.890–0.899), better calibration (HL(TRIMP-ICDX) 5.6; 95% CI, 3.0–8.0, HL(TRISS) 72.7; 95% CI, 38.4–104.5, and HL(IMP-ICDX) 53.1; 95% CI, 26.6–77.8), and a lower AIC (AIC(TRIMP-ICDX) 24,774, AIC(TRISS) 30,753, and AIC(IMP-ICDX) 32,780) compared with TRISS and IMP-ICDX. Similar results were found in statistical comparisons among different body regions. As a comprehensive evaluation method based on the ICD-10-CM lexicon TRIMP-ICDX is significantly better than IMP-ICDX and TRISS with respect to both discriminative power and calibration. The TRIMP-ICDX should become a research method for the comprehensive evaluation of trauma severity. |
format | Online Article Text |
id | pubmed-9351923 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-93519232022-08-05 Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes Zhang, Guohu Wang, Muding Cong, Degang Zeng, Yunji Fan, Wenhui Medicine (Baltimore) Research Article Various assessment methods based on the International Classification of Diseases, Tenth Edition, Clinical Modification (ICD-10-CM), such as ICD-10-CM Injury Severity Score (ICISS), trauma mortality prediction model (TMPM-ICD10), and injury mortality prediction (IMP-ICDX), are purely anatomic trauma assessment, which need to be further improved. Traumatic injury mortality prediction (TRIMP-ICDX) is a comprehensive assessment method based on anatomic injuries and incorporating available information to determine whether it is superior to Trauma and Injury Severity Score (TRISS) and IMP-ICDX in predicting trauma outcomes. This retrospective cohort study was based on data from 704,287 trauma patients admitted to 710 trauma centers in the National Trauma Data Bank of the United States in 2016. The TRIMP-ICDX was established using anatomical injury, physiological reserves, and physiological response indicators. Its performance was compared with the IMP-ICDX and TRISS by examining the area under the receiver operating characteristic curve (AUC), calibration (Hosmer-Lemeshow goodness-of-fit test, HL), and the Akaike information criterion (AIC). The TRIMP-ICDX showed significantly better discrimination (AUC(TRIMP-ICDX) 0.968; 95% confidence interval (CI), 0.966–0.970, AUC(TRISS) 0.922; 95% CI, 0.918–0.925, and AUC(IMP-ICDX) 0.894; 95% CI, 0.890–0.899), better calibration (HL(TRIMP-ICDX) 5.6; 95% CI, 3.0–8.0, HL(TRISS) 72.7; 95% CI, 38.4–104.5, and HL(IMP-ICDX) 53.1; 95% CI, 26.6–77.8), and a lower AIC (AIC(TRIMP-ICDX) 24,774, AIC(TRISS) 30,753, and AIC(IMP-ICDX) 32,780) compared with TRISS and IMP-ICDX. Similar results were found in statistical comparisons among different body regions. As a comprehensive evaluation method based on the ICD-10-CM lexicon TRIMP-ICDX is significantly better than IMP-ICDX and TRISS with respect to both discriminative power and calibration. The TRIMP-ICDX should become a research method for the comprehensive evaluation of trauma severity. Lippincott Williams & Wilkins 2022-08-05 /pmc/articles/PMC9351923/ /pubmed/35945731 http://dx.doi.org/10.1097/MD.0000000000029714 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Zhang, Guohu Wang, Muding Cong, Degang Zeng, Yunji Fan, Wenhui Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes |
title | Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes |
title_full | Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes |
title_fullStr | Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes |
title_full_unstemmed | Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes |
title_short | Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes |
title_sort | traumatic injury mortality prediction (trimp-icdx): a new comprehensive evaluation model according to the icd-10-cm codes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351923/ https://www.ncbi.nlm.nih.gov/pubmed/35945731 http://dx.doi.org/10.1097/MD.0000000000029714 |
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