A predictive model for heart failure with preserved ejection fraction following acute myocardial infarction: the

Xi Wu1, Mingxing Wu1, Haobo Huang1

  • 1Department of Cardiology, Xiangtan Central Hospital (the affiliated hospital of Hunan University), Xiangtan, 411100, Hunan, People's Republic of China.

PubMed

Insights

A new HFpEF-AMI Score identifies patients at risk for heart failure with preserved ejection fraction (HFpEF) after acute myocardial infarction (AMI). This tool aids in early risk stratification and long-term prognosis following PCI.

Area of Science:

  • Cardiology
  • Clinical Medicine
  • Biomarkers

Background:

  • Heart failure with preserved ejection fraction (HFpEF) is a frequent complication post-acute myocardial infarction (AMI), especially after percutaneous coronary intervention (PCI).
  • Early identification of patients susceptible to HFpEF after AMI remains a significant clinical challenge.

Purpose of the Study:

  • To develop and validate a predictive model for early HFpEF identification in AMI patients undergoing PCI.
  • To assess the clinical utility of the novel HFpEF-AMI Score for risk stratification.

Main Methods:

  • Retrospective analysis of 458 first-episode AMI patients treated with emergency PCI.
  • Stratification into HFpEF (n=107) and non-HF (n=351) groups based on 2021 ESC criteria.
  • Logistic regression identified predictors, leading to the development of the HFpEF-AMI Score.

Main Results:

  • 23.4% of AMI patients developed HFpEF post-PCI.
  • Key predictors included elevated D-dimer, peak NT-proBNP, increased LVMI, and LAD artery involvement.
  • The HFpEF-AMI Score demonstrated high discriminatory performance (AUC 0.882) with excellent sensitivity (74.8%) and specificity (86.6%).
  • HFpEF patients faced higher rates of MACCE and heart failure rehospitalizations during 2-year follow-up.

Conclusions:

  • The HFpEF-AMI Score is a valuable tool for early risk assessment of HFpEF in AMI patients.
  • The score integrates routine laboratory and angiographic data for improved clinical decision-making.
  • It aids in risk stratification and long-term prognostic evaluation post-AMI.
Abstract

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