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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...

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Autores principales: Zhang, Guohu, Wang, Muding, Cong, Degang, Zeng, Yunji, Fan, Wenhui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
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.
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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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