Anti-factor Xa during unfractionated heparin therapy in critically ill patients: Development of prediction models using machine learning

Anti-factor Xa during unfractionated heparin therapy in critically ill patients: Development of prediction models using machine learning

Objective Unfractionated heparin (UFH) is a widely used therapy in intensive care units (ICUs) and is associated with an increased risk of serious adverse events or death if the therapeutic target is not reached quickly. Adjusting UFH dosage is challenging, and no reliable algorithms exist for predi...

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Bibliographic Details
Main Authors: Boris Delange, Guillaume Bouzillé, Pauline Guillot, Anaëlle Bichon, Océane Bernard de Lajartre, Isabelle Gouin, Yoann Launey, Alexandre Mansour, Mathieu Lesouhaitier, Jean-Marc Tadié, Arnaud Gacouin, Marc Cuggia, Adel Maamar
Format: Article
Language:English
Published: SAGE Publishing 2025-04-01
Series:Digital Health
Online Access:https://doi.org/10.1177/20552076241305957
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