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November 30, 2025JMIR Medical InformaticsOpen Access

Risk Prediction of Major Adverse Cardiovascular Events Within One Year After Percutaneous Coronary Intervention in Patients With Acute Coronary Syndrome: Machine Learning–Based Time-to-Event Analysis

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Overview

Time-to-event machine learning model identifies risk factors for major adverse cardiovascular events in ACS patients, suggesting improved management strategies.

Key Points

  • Major adverse cardiovascular events occurred in 19.8% of the cohort during a median follow-up of 3.8 years.
  • The best-performing model achieved a time-dependent Brier score indicating accuracy in risk assessment over time.
  • Analysis utilized electronic health records from 3159 patients with acute coronary syndrome undergoing PCI between 2008 and 2020.
  • Findings support individualized management for postdischarge cardiovascular risk in patients with acute coronary syndrome.

Cite This Study

A 2025 study studied this question.

synapsesocial.com/papers/692b9d8d1d383f2b2a379bcbhttps://doi.org/10.2196/81778
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Systematic Review and Meta-Analysis2025 · 10 citations
  2. 2Enhancing one-year mortality prediction in STEMI patients post-PCI: an interpretable machine learning model with risk stratification2025
  3. 3Comparison of the Prognostic Performance of Various Machine Learning Models in Patients with Acute Myocardial Infarction: Results from the COREA-AMI Registry2025
  4. 4Predicting Mortality After Percutaneous Coronary Intervention in a Multiethnic Southeast Asian Population: Insights From Machine Learning2026
  5. 5Development of a Risk Prediction Model for Major Adverse Cardiovascular Events After PCI in Patients with Coronary Heart Disease2025