Impact on the ability of healthcare professionals to correctly identify patient-ventilator asynchronies of the simultaneous visualization of estimated muscle pressure curves on the ventilator display: a randomized study (P study).

Journal: Critical care (London, England)
PMID: 36998022

Abstract

BACKGROUND: Patient-ventilator asynchronies are usually detected by visual inspection of ventilator waveforms but with low sensitivity, even when performed by experts in the field. Recently, estimation of the inspiratory muscle pressure (P) waveforms through artificial intelligence algorithm has been proposed (Magnamed®, São Paulo, Brazil). We hypothesized that the display of these waveforms could help healthcare providers identify patient-ventilator asynchronies.

Authors

  • Daniel Oliveira Silva
    Intensive Care Unit, Hospital Sírio-Libanes, São Paulo, Brazil.
  • Patrícia Nery de Souza
    Intensive Care Unit, Hospital Sírio-Libanes, São Paulo, Brazil. patnerysouza@gmail.com.
  • Mayson Laercio de Araujo Sousa
    Interdepartmental Division of Critical Care Medicine, St. Michael's Hospital, Toronto, Canada.
  • Caio Cesar Araujo Morais
    Universidade Federal de Pernambuco, UFPE, Pernambuco, Brazil.
  • Juliana Carvalho Ferreira
    Disciplina de Pneumologia, Heart Institute (Incor), Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
  • Marcelo Alcantara Holanda
    Departamento de Medicina Clínica, Universidade Federal do Ceará, Fortaleza, Brazil.
  • Wellington Pereira Yamaguti
    Intensive Care Unit, Hospital Sírio-Libanes, São Paulo, Brazil.
  • Laerte Pastore Junior
    Intensive Care Unit, Hospital Sírio-Libanes, São Paulo, Brazil.
  • Eduardo Leite Vieira Costa
    Disciplina de Pneumologia, Heart Institute (Incor), Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.

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