Can machine learning provide preoperative predictions of biological hemostasis after extracorporeal circulation for cardiac surgery?

Journal: The Journal of thoracic and cardiovascular surgery
PMID: 37931798

Abstract

OBJECTIVES: The goal of this study was to improve decision making regarding the transfusion of patients at the end of extracorporeal circulation for cardiac surgery through machine learning predictions of the evolution of platelets counts, prothrombin ratio, and fibrinogen assay.

Authors

  • Vittorio Perduca
    Université Paris Cité, CNRS, MAP5, Paris, France.
  • Olivier Bouaziz
    Université Paris Cité, CNRS, MAP5, Paris, France.
  • Kostantinos Zannis
    Department of Cardiac surgery, Institut Mutualiste Montsouris, Paris, France.
  • Marc Beaussier
    Department of Anesthesiology, Institut Mutualiste Montsouris, Paris, France.
  • Olivier Untereiner
    Department of Anesthesiology, Institut Mutualiste Montsouris, Paris, France. Electronic address: olivier.untereiner@imm.fr.

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