Development and Validation of a Prediction Rule for Major Adverse Cardiac and Cerebrovascular Events in High-Risk Myocardial Infarction Patients After Primary Percutaneous Coronary Intervention

Clin Interv Aging. 2022 Jul 18:17:1099-1111. doi: 10.2147/CIA.S358761. eCollection 2022.

Abstract

Background and aims: We aimed to develop a clinical prediction tool to improve the prognosis of major adverse cardiac and cerebrovascular events (MACCE) among high-risk myocardial infarction (MI) patients undergoing primary percutaneous coronary intervention (PCI).

Methods: The present study was a prospective and observational study. A total of 4151 consecutive MI patients who underwent primary PCI at Fuwai Hospital in Beijing, China (January 2010 and June 2017) were enrolled. Forty-eight patients without follow-up data were excluded from the study. The pre-specified criteria (Supplementary Information 1) were chosen to enroll MI patients at high risk for MACCE complications after PCI.

Results: The full model included seven variables, with a risk score of 160 points. Derivation and validation cohort models predicting MACCE had C-statistics of 0.695 and 0.673. The area under the curve (AUC) of the survival receiver operating characteristic curve (ROC) for predicting MACCE was 0.991 and 0.883 in the derivation and validation cohorts, respectively.

Conclusion: The predicted model was internally validated and calibrated in large cohorts of patients with high-risk MI receiving primary PCI to predict MACCE and showed modest accuracy in the derivation and validation cohorts.

Keywords: follow-up; high-risk; primary percutaneous coronary intervention; risk prediction score.

Publication types

  • Observational Study

MeSH terms

  • Coronary Artery Disease*
  • Heart
  • Humans
  • Myocardial Infarction*
  • Percutaneous Coronary Intervention* / adverse effects
  • Prospective Studies
  • Risk Assessment
  • Risk Factors
  • Treatment Outcome

Grants and funding

This study was supported by the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2016-I2M-1–009), National Natural Science Funds (number: 81970308), the Fund of “Sanming” Project of Medicine in Shenzhen (number: SZSM201911017) and Shenzhen Key Medical Discipline Construction Fund (number: SZXK001).