Derivation and validation of a prediction model for long-term mortality in patients with ST-segment elevation

Luis Ortega-Paz1, Claudio Laudani1,2, Salvatore Brugaletta3

  • 1Division of Cardiolgy, University of Florida College of Medicine - Jacksonville, Jacksonville, Florida, USA.

Insights

A new PREDICT-STEMI score predicts long-term mortality in ST-elevation myocardial infarction (STEMI) patients after percutaneous coronary intervention (PCI). This simple tool aids in early risk stratification and clinical decision-making for STEMI patients.

Area of Science:

  • Cardiology
  • Clinical Prediction Models
  • Public Health

Background:

  • Limited models exist for predicting long-term mortality in ST-elevation myocardial infarction (STEMI) patients undergoing percutaneous coronary intervention (PCI).
  • Developing a reliable predictive tool is crucial for risk stratification and clinical decision-making in this patient population.

Purpose of the Study:

  • To derive and validate a predictive model for long-term mortality in patients with STEMI undergoing PCI.
  • To develop a simple, accessible score for clinical use.

Main Methods:

  • A total of 23,086 STEMI patients were included in the derivation cohort.
  • Time-to-event regression analysis identified predictors of long-term mortality.
  • The model was validated in two independent cohorts (n=1498 and n=1112).

Main Results:

  • The PREDICT-STEMI score includes seven variables: age, diabetes, prior myocardial infarction, prior ischemic stroke/TIA, hemodynamic status, three-vessel disease, and mechanical circulatory support.
  • The score demonstrated good predictive performance with a Concordance index of 0.81 in the derivation cohort and 0.81-0.84 in validation cohorts.
  • A score of 60 was identified as the optimal cut-off, with higher scores indicating a sixfold increased risk of long-term mortality.

Conclusions:

  • The PREDICT-STEMI score is a validated, simple tool for predicting long-term mortality in STEMI patients undergoing PCI.
  • It facilitates early risk stratification, enabling informed clinical decision-making.
  • This score can improve patient management and outcomes.
Abstract