Prediction of 90 day mortality in elderly patients with acute HF from e-health records using artificial intelligence.

Journal: ESC heart failure
PMID: 39949136

Abstract

AIMS: Mortality risk after hospitalization for heart failure (HF) is high, especially in the first 90 days. This study aimed to construct a model automatically predicting 90 day post-discharge mortality using electronic health record (EHR) data 48 h after admission and artificial intelligence.

Authors

  • Joconde Weller
    Direction of Medical Information, Prospects and Data Sciences, Hôpitaux Paris Saint-Joseph and Marie-Lannelongue, Paris, France.
  • Johann Gutton
    Direction of Medical Information, Prospects and Data Sciences, Hôpitaux Paris Saint-Joseph and Marie-Lannelongue, Paris, France.
  • Guillaume Hocquet
    Direction of Medical Information, Prospects and Data Sciences, Hôpitaux Paris Saint-Joseph and Marie-Lannelongue, Paris, France.
  • Leïla Pellet
    Direction of Medical Information, Prospects and Data Sciences, Hôpitaux Paris Saint-Joseph and Marie-Lannelongue, Paris, France.
  • Marie-José Aroulanda
    Department of Cardiology, Hôpital Paris Saint-Joseph, Paris, France.
  • Amélie Bruandet
    Department of Medical Information, CHU Lille, Lille, France.
  • Didier Theis
    Department of Medical Information, CHU Lille, Lille, France.
  • Fabio Boudis
    Department of Medical Information, CHU Lille, Lille, France.
  • Romain Cador
    Department of Cardiology, Hôpital Paris Saint-Joseph, Paris, France.
  • Pierre Zweigenbaum
  • Anne Buronfosse
    Medical Information Department, Paris Saint Joseph Hospital, Paris, France.
  • Pascal de Groote
    Department of Cardiology, CHU Lille, Lille, France.
  • Michel Komajda
    Department of Cardiology, Hôpital Paris Saint-Joseph, Paris, France.

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