Synapse
⌘+K
Synapse
PulseExploreJournal ClubResearchersJournals
Instagram
HomeJournal ClubExplore
August 16, 2025Open Access

Development of a Risk Prediction Model for Major Adverse Cardiovascular Events After PCI in Patients with Coronary Heart Disease

View Full Paper
Ask AI
Bookmark
Share

Authors

YLYe LinXGXinru GuoSMShumei Mi

Discussion

Loading...

Member takes

Overview

Retrospective study predicts major adverse cardiovascular events after PCI, suggesting effective risk management strategies.

Key Points

  • Major adverse cardiovascular events rates were reported as 32.8%, 37.0%, and 37.4% at one, two, and three years, revealing significant long-term risk.
  • Independent predictors for MACE were identified, with model performance AUCs of 0.754, 0.747, and 0.771 for respective timeframes, indicating robust predictive capacity.
  • Assessment involved various metrics including Brier score, sensitivity, and specificity, employing techniques like LASSO regression and Cox proportional hazard model.
  • Effective risk stratification highlights the potential for enhanced patient management, with evidence suggesting clinical applicability through advanced modeling.

Cite This Study

Lin et al. (2025) studied this question.

synapsesocial.com/papers/68c23626b210217d64773522https://doi.org/10.21203/rs.3.rs-6994881/v1
View Full Paper
Ask AI
Bookmark
Share

Also Consider

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

  1. 1Risk 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 Analysis2025
  2. 2Risk Prediction Models for Hospital Readmission After Percutaneous Coronary Intervention: A Systematic Review and Meta-Analysis2025
  3. 3Development and Validation of a Prognostic Nomogram Integrating CMR and Clinical Data for Predicting 1- to 3-Year Major Adverse Cardiovascular Events in New-Onset STEMI Patients Post-PCI2025
  4. 4XGBoost based machine learning prediction model for major adverse cardiovascular events after PCI in STEMI patients2026
  5. 5A nomogram model based on HALP score and sST2 for predicting 1-year MACE risk after PCI in acute myocardial infarction patients2025 · 1 citations