Diagnostic accuracy of artificial-intelligence-based electrocardiogram algorithm to estimate heart failure with reduced ejection fraction: A systematic review and meta-analysis.

Journal: Current problems in cardiology
PMID: 39909205

Abstract

INTRODUCTION: AI-based ECG has shown good accuracy in diagnosing heart failure. However, due to the heterogeneity of studies regarding cutoff points, its precision for specifically detecting heart failure with left ventricle reduced ejection fraction (LVEF <40 %) is not yet well established. What is the sensitivity and specificity of artificial-based electrocardiogram to diagnose heart failure with low ejection fraction (cut-off of 40 %.

Authors

  • André Luiz Carvalho Ferreira
    Pontifical Catholic University of Paraná, Curitiba, Brazil. Electronic address: ferreira.andre98@hotmail.com.
  • Luanna Paula Garcez de Carvalho Feitoza
    Center University Fametro, Manaus, Brazil.
  • Maria E Benitez
    Advocate illinois Masonic Medical Center, Chicago, IL, United States.
  • Buena Aziri
    Sarajevo Medical School, Sarajevo School of Science and Technology, Sarajevo, Bosnia and Herzegovina.
  • Edin Begic
    Department of Cardiology, General Hospital «Prim. dr. Abdulah Nakas», Sarajevo, Bosnia and Herzegovina.
  • Luciana Vergara Ferraz de Souza
    University of Connecticut, CT, United States.
  • Elísio Bulhões
    College of Higher Education of the United Amazon, Redenção, Brazil.
  • Sarah O N Monteiro
    Redentor University Center, Itaperuna, Brazil.
  • Maria L R Defante
    Redentor University Center, Medicine Department, Itaperuna, Brazil.
  • Roberto Augusto Mazetto Silva Vieira
    Amazon State University, Manaus, Brazil.
  • Camila Guida
    Dante Pazzanese Institute of Cardiology, Brazil.

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