Left ventricular systolic dysfunction predicted by artificial intelligence using the electrocardiogram in Chagas disease patients-The SaMi-Trop cohort.

Journal: PLoS neglected tropical diseases
PMID: 34871321

Abstract

BACKGROUND: Left ventricular systolic dysfunction (LVSD) in Chagas disease (ChD) is relatively common and its treatment using low-cost drugs can improve symptoms and reduce mortality. Recently, an artificial intelligence (AI)-enabled ECG algorithm showed excellent accuracy to detect LVSD in a general population, but its accuracy in ChD has not been tested.

Authors

  • Bruno Oliveira de Figueiredo Brito
    Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
  • Zachi I Attia
    Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Larissa Natany A Martins
    Telehealth Center, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
  • Pablo Perel
    Department of Non-communicable Diseases Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK.
  • Maria Carmo P Nunes
    Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
  • Ester Cerdeira Sabino
    Institute of Tropical Medicine, University of São Paulo, São Paulo, São Paulo 470-05403-000,Brazil.
  • Clareci Silva Cardoso
    Federal University of São João del-Rei, Divinópolis, Brazil.
  • Ariela Mota Ferreira
    Graduate Program in Health Sciences, State University of Montes Claros, Montes Claros, Minas Gerais, Brazil.
  • Paulo R Gomes
    Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
  • Antonio Luiz Pinho Ribeiro
    Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
  • Francisco Lopez-Jimenez
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.

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