Electronic Health Record-Based Deep Learning Prediction of Death or Severe Decompensation in Heart Failure Patients.

Journal: JACC. Heart failure
Published Date: Jul 6, 2022

Abstract

BACKGROUND: Surgical mechanical ventricular assistance and cardiac replacement therapies, although life-saving in many heart failure (HF) patients, remain high-risk. Despite this, the difficulty in timely identification of medical therapy nonresponders and the dire consequences of nonresponse have fueled early, less selective surgical referral. Patients who would have ultimately responded to medical therapy are therefore subjected to the risk and life disruption of surgical therapy.

Authors

  • Martha M O McGilvray
    Division of Cardiothoracic Surgery, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
  • Jeffrey Heaton
    Sever Institute, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.
  • Aixia Guo
    Institute for Informatics (I2), Washington University School of Medicine, St. Louis, MO, United States.
  • M Faraz Masood
    Division of Cardiothoracic Surgery, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
  • Brian P Cupps
    Department of Surgery, Washington University School of Medicine, St. Louis, MO, United States.
  • Marci Damiano
    Division of Cardiothoracic Surgery, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
  • Michael K Pasque
    Department of Surgery, Washington University School of Medicine, St. Louis, MO, United States.
  • Randi Foraker
    Institute for Informatics, Division of General Medical Sciences, Washington University School of Medicine, St. Louis, MO, USA.

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