A Multivariate Model to Predict Chronic Heart Failure after Acute ST-Segment Elevation Myocardial Infarction:

Valentin Elievich Oleynikov1, Elena Vladimirovna Averyanova1, Anastasia Aleksandrovna Oreshkina1

  • 1Department of Therapy, Medical Institute, Penza State University, 440026 Penza, Russia.

Insights

A new model predicts chronic heart failure (CHF) risk after myocardial infarction. This tool helps identify high-risk patients early for better management.

Area of Science:

  • Cardiology
  • Medical Prognostics

Background:

  • ST-segment elevation myocardial infarction (STEMI) survivors face a significant risk of developing decompensated chronic heart failure (CHF).
  • Early identification of patients at high risk for CHF progression post-STEMI is crucial for timely intervention and improved outcomes.

Purpose of the Study:

  • To develop and validate a multivariate model for predicting the risk of decompensated CHF within 48 weeks following STEMI.
  • To assess the diagnostic efficiency of the developed predictive model.

Main Methods:

  • The study involved 173 STEMI patients, utilizing 2D speckle-tracking echocardiography (STE) and 24-hour ECG monitoring for parameters including global longitudinal strain (GLS) and heart rate turbulence (HRT).
  • A multivariate model was constructed using data from 113 patients (Group M) and validated on 60 patients (Group T).

Main Results:

  • The predictive model incorporated HRT, left ventricular end-systolic dimension (ESD), and GLS.
  • The model demonstrated significant predictive value for CHF progression, with HRT (RR 3.92), ESD (RR 1.04), and GLS (RR 0.9) as key factors.
  • Validation showed high diagnostic performance: 83.3% specificity, 95.8% sensitivity, and 93.3% accuracy.

Conclusions:

  • The developed multivariate model effectively predicts CHF progression in STEMI patients within 48 weeks.
  • The model exhibits high diagnostic efficiency and can be utilized in the early stages post-myocardial infarction for patient risk stratification.

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