A deep learning approach identifies new ECG features in congenital long QT syndrome.

Journal: BMC medicine
PMID: 35501785

Abstract

BACKGROUND: Congenital long QT syndrome (LQTS) is a rare heart disease caused by various underlying mutations. Most general cardiologists do not routinely see patients with congenital LQTS and may not always recognize the accompanying ECG features. In addition, a proportion of disease carriers do not display obvious abnormalities on their ECG. Combined, this can cause underdiagnosing of this potentially life-threatening disease.

Authors

  • Simona Aufiero
    University of Amsterdam, Heart Center; Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Meibergdreef 9, Amsterdam, The Netherlands.
  • Hidde Bleijendaal
    Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Meibergdreef 9, Amsterdam, the Netherlands.
  • Tomas Robyns
    Department of Cardiovascular Diseases, University Hospitals Leuven, Leuven, Belgium.
  • Bert Vandenberk
  • Christian Krijger
    Department of Experimental Cardiology, Amsterdam UMC, Amsterdam, The Netherlands.
  • Connie Bezzina
    Department of Experimental Cardiology, Amsterdam UMC, Amsterdam, The Netherlands.
  • Aeilko H Zwinderman
    Amsterdam UMC, University of Amsterdam, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam, The Netherlands.
  • Arthur A M Wilde
    European Reference Network for Rare, Low Prevalence and Complex Diseases of the Heart: ERN GUARD-Heart (P.D.L., A.A.M.W.).
  • Yigal M Pinto
    Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.

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