Development and external validation of a machine learning model for predicting 28-day mortality in patients with acute myocardial infarction complicated by malignant arrhythmia: a study using the MIMIC database and a Chinese cohort.

Jiechun Yao, Chun Lin, Qingbo Xu, Guode Li, Jinmei Pan, Jiancheng Wang, Yan Lin

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Article in Frontiers in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Jiechun YaoCardiac and Circulatory Medicine Section, Maoming People's Hospital, Maoming, Guangdong, China.

Chun LinInternal Medicine Division, Maoming People's Hospital, Maoming, Guangdong, China.

Qingbo XuCardiac and Circulatory Medicine Section, Maoming People's Hospital, Maoming, Guangdong, China.

Guode LiCardiac and Circulatory Medicine Section, Maoming People's Hospital, Maoming, Guangdong, China.

Jinmei PanCardiac and Circulatory Medicine Section, Maoming People's Hospital, Maoming, Guangdong, China.

Jiancheng WangInformation Technology Department, Maoming People's Hospital, Maoming, Guangdong, China.

Yan LinDepartment of Cardiovascular Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Acute myocardial infarction (AMI) complicated by malignant ventricular arrhythmia (MVA) carries high 28-day mortality. Existing risk scores inadequately capture this population. We aimed to develop and externally validate an interpretable machine learning model for predicting 28-day mortality in AMI-MVA patients. Methods: This retrospective study included 952 AMI-MVA patients from MIMIC-IV (training Results: 28-day mortality was 32.46% (309/952). The SVM model (linear kernel, Conclusion: This interpretable SVM model supports bedside risk stratification for AMI-MVA patients within the first 24 h of ICU admission. The model should be understood as a prognostic snapshot rather than an early prediction tool. Prospective, multicentre validation with standardised severity scores and coronary-anatomy variables is required before routine clinical use.

Indexed as

28-day mortalityacute myocardial infarctionmachine learningmalignant ventricular arrhythmiarisk prediction model

Identifiers

PMID42591658

DOI10.3389/fcvm.2026.1908251

PMCPMC13462401

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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.