Artificial intelligence in the management of patient-ventilator asynchronies: A scoping review.

Journal: Heart & lung : the journal of critical care
Published Date: May 23, 2025

Abstract

BACKGROUND: Patient-ventilator asynchronies (PVAs) are frequent complications in mechanically ventilated patients, contributing to adverse outcomes such as ventilator-induced lung injury, prolonged mechanical ventilation, and increased mortality. Artificial intelligence (AI) has emerged as a promising tool for enhancing PVA detection, prediction, and optimization. Despite its growing potential, the full scope of AI applications in this field and persistent gaps in evidence remain inadequately explored.

Authors

  • Javier Muñoz
    ICU. Hospital General Universitario Gregorio Marañón, Madrid, Spain. Electronic address: j.munoz@salud.madrid.org.
  • Rocío Ruíz-Cacho
    ICU. Hospital General Universitario Gregorio Marañón, Madrid, Spain.
  • Nerio José Fernández-Araujo
    ICU. Hospital General Universitario Gregorio Marañón, Madrid, Spain.
  • Alberto Candela
    The Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
  • Lourdes Carmen Visedo
    C.S. San Juan de Dios. Pozuelo de Alarcón. Madrid. Spain.
  • Javier Muñoz-Visedo
    ICU. Hospital General Universitario Gregorio Marañón, Madrid, Spain.

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