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October 12, 2025Reviews in Cardiovascular MedicineOpen Access

Risk Prediction Models for Hospital Readmission After Percutaneous Coronary Intervention: A Systematic Review and Meta-Analysis

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Authors

YMYufeng MaoHFHui FanWHWenjing He

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Overview

Systematic review finds moderate predictive performance in hospital readmission risk models for PCI patients, highlighting significant bias issues.

Key Points

  • The combined AUROC curve for nine validated models was 0.80, suggesting moderate discrimination ability.
  • Ten studies incorporating 18 risk prediction models for hospital readmission following PCI were analyzed for biases.
  • Key predictive factors identified include age, diabetes, concurrent heart failure, and chronic lung disease.
  • Most included studies have a high risk of bias, particularly related to deficiencies in data analysis.

Cite This Study

Mao et al. (2025) studied this question.

synapsesocial.com/papers/68ec1be02b8fa9b2b78ad05fhttps://doi.org/10.31083/rcm39409
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