Evidence map›Paper›PMID 31632453›Full record

ArticleWorld journal of emergency surgery : WJES2019

IMP-ICDX: an injury mortality prediction based on ICD-10-CM codes.

Muding Wang, Wusi Qiu, Yunji Zeng, Wenhui Fan, Xiao Lian, Yi Shen

Abstract read
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Article in World journal of emergency surgery : WJES, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Muding Wang1Department of Emergency Medicine, Affiliated Hospital of Hangzhou Normal University, 126 Wenzhou Road, Gongshu District, Hangzhou, 310015 Zhejiang People's Republic of China.ORCID 0000-0002-1788-2658
Wusi Qiu2Department of Neurosurgery, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015 Zhejiang People's Republic of China.
Yunji Zeng3Department of Orthopedic, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015 Zhejiang People's Republic of China.
Wenhui Fan1Department of Emergency Medicine, Affiliated Hospital of Hangzhou Normal University, 126 Wenzhou Road, Gongshu District, Hangzhou, 310015 Zhejiang People's Republic of China.
Xiao Lian3Department of Orthopedic, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015 Zhejiang People's Republic of China.
Yi Shen4Department of Epidemiology and Health Statistics, School of Public Health, Zhejiang University, Hangzhou, 310058 Zhejiang People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) Injury Severity Score (ICISS) is a risk adjustment model when injuries are recorded using ICD-9-CM coding. The trauma mortality prediction model (TMPM-ICD9) provides better calibration and discrimination compared with ICISS and injury severity score (ISS). Though TMPM-ICD9 is statistically rigorous, it is not precise enough mathematically and has the tendency to overestimate injury severity. The purpose of this study is to develop a new ICD-10-CM injury model which estimates injury severities for every injury in the ICD-10-CM lexicon by a combination of rigorous statistical probit models and mathematical properties and improves the prediction accuracy. Methods: We developed an injury mortality prediction (IMP-ICDX) using data of 794,098 patients admitted to 738 hospitals in the National Trauma Data Bank from 2015 to 2016. Empiric measures of severity for each of the trauma ICD-10-CM codes were estimated using a weighted median death probability (WMDP) measurement and then used as the basis for IMP-ICDX. ISS (version 2005) and the single worst injury (SWI) model were re-estimated. The performance of each of these models was compared by using the area under the receiver operating characteristic (AUC), the Hosmer-Lemeshow (HL) statistic, and the Akaike information criterion statistic. Results: IMP-ICDX exhibits significantly better discrimination (AUC Conclusions: The IMP-ICDX has a better discrimination and calibration compared to ISS. Therefore, we believe that IMP-ICDX could be a new viable trauma research assessment method.

Indexed as

PrognosisAdultAgedFemaleHumansInternational Classification of DiseasesMaleMiddle AgedProbabilitySeverity of Illness IndexWounds and InjuriesInjury mortality prediction for ICD-10-CM (IMP-ICDX)Injury severity score (ISS)International Classification of Diseases Tenth Edition (ICD-10-CM)Mortality prediction

Identifiers

PMID31632453
PMCPMC6787998

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.