Evidence map›Paper›PMID 38883350›Full record

ArticleAmerican journal of translational research2024

Risk factors for ventricular arrhythmias after emergency percutaneous coronary intervention in elderly patients with acute myocardial infarction.

Yajun He, Jilun Liu, Yue Zhang, Ye Tian, Yuqiu Li, Erwei Liu, Rui Cao

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Article in American journal of translational research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yajun HeDepartment of Cardiovascular, No. 215 Hospital of Shaanxi Nuclear Industry Xianyang 712000, Shaanxi, China.
Jilun LiuDepartment of Cardiovascular, No. 215 Hospital of Shaanxi Nuclear Industry Xianyang 712000, Shaanxi, China.
Yue ZhangDepartment of Cardiovascular, No. 215 Hospital of Shaanxi Nuclear Industry Xianyang 712000, Shaanxi, China.
Ye TianDepartment of Cardiovascular, No. 215 Hospital of Shaanxi Nuclear Industry Xianyang 712000, Shaanxi, China.
Yuqiu LiDepartment of Cardiovascular, No. 215 Hospital of Shaanxi Nuclear Industry Xianyang 712000, Shaanxi, China.
Erwei LiuDepartment of Cardiovascular, No. 215 Hospital of Shaanxi Nuclear Industry Xianyang 712000, Shaanxi, China.
Rui CaoDepartment of Cardiovascular, No. 215 Hospital of Shaanxi Nuclear Industry Xianyang 712000, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the risk factors for ventricular arrhythmia after percutaneous coronary intervention (PCI) in elderly patients with acute myocardial infarction (AMI).

methodsA retrospective cohort of 201 elderly AMI patients who underwent PCI in the emergency department of No. 215 Hospital of Shaanxi Nuclear Industry from April 2020 to January 2023 was analyzed. The patients were randomly divided into a training set (n=134) for model development and a test set (n=67) for model validation. The training set was divided into a ventricular arrhythmia group (n=51) and a non-ventricular arrhythmia group (n=83), based on the occurrence of ventricular arrhythmia post-PCI. The factors affecting ventricular arrhythmias were analyzed by logistic regression and Lasso regression models.

resultsLasso regression screened 12 characteristic factors at λ=0.1 se. In the training set, the area under the ROC curve (AUC) of the Lasso model for predicting ventricular arrhythmia was 0.954, which was significantly higher than 0.826 for the Logistic model (P < 0.001). In the test set, the AUC of the Lasso model was 0.962, which was also significantly higher than 0.825 for the Logistic model (P=0.003).

conclusionCompared to the logistic regression model, the Lasso regression model can more accurately predict the occurrence of ventricular arrhythmia after PCI in elderly AMI patients. The Lasso regression model constructed in this study can provide a reference for the clinical identification of high-risk elderly AMI patients and the development of targeted monitoring and treatment.

Indexed as

Acute myocardial infarctionpercutaneous coronary interventionrisk factorsventricular arrhythmia

Identifiers

PMID38883350
PMCPMC11170566

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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.