Patient-Ventilator Synchronization During Non-invasive Ventilation : A Pilot Study of an Automated Analysis System
Letellier, Christophe (Parc Taulí Hospital Universitari. Institut d'Investigació i Innovació Parc Taulí (I3PT))
Luján, Manel (Universitat Autònoma de Barcelona. Departament de Medicina)
Arnal, Jean-Michel (Hôpital Sainte Musse)
Carlucci, Annalisa (University of Insubria)
Chatwin, Michelle (Royal Brompton & Harefield (Regne Unit))
Ergan, Begum (Dokuz Eylul University)
Kampelmacher, Mike (University Hospital Antwerp)
Storre, Jan Hendrik (University Medical Hospital (Alemanya))
Hart, Nicholas (Lane Fox Clinical Respiratory Physiology Research Centre (Regne Unit))
Gonzalez-Bermejo, Jesus (Sorbonne Université)
Nava, Stefano (University of Bologna)

Date:	2021
Abstract:	Background: Patient-ventilator synchronization during non-invasive ventilation (NIV) can be assessed by visual inspection of flow and pressure waveforms but it remains time consuming and there is a large inter-rater variability, even among expert physicians. ™ software developed by Breas Medical (Mölnycke, Sweden) provides an automatic detection and scoring of patient-ventilator asynchrony to help physicians in their daily clinical practice. This study was designed to assess performance of the automatic scoring by the software using expert clinicians as a reference in patient with chronic respiratory failure receiving NIV. Methods: From nine patients, 20 min data sets were analyzed automatically by software and reviewed by nine expert physicians who were asked to score auto-triggering (AT), double-triggering (DT), and ineffective efforts (IE). The study procedure was similar to the one commonly used for validating the automatic sleep scoring technique. For each patient, the asynchrony index was computed by automatic scoring and each expert, respectively. Considering successively each expert scoring as a reference, sensitivity, specificity, positive predictive value (PPV), κ-coefficients, and agreement were calculated. Results: The asynchrony index assessed by was not significantly different from the one assessed by the experts (18. 9 ± 17. 7 vs. 12. 8 ± 9. 4, p = 0. 19). When compared to an expert, the sensitivity and specificity provided by for DT, AT, and IE were significantly greater than those provided by an expert when compared to another expert. Conclusions: software is able to score asynchrony events within the inter-rater variability. When the breathing frequency is not too high (<24), it therefore provides a reliable assessment of patient-ventilator asynchrony; AT is over detected otherwise.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Non-invasive ventilation ; Patient ventilator asynchrony ; Chronic obstructive pulmonary disease ; Ineffective triggering ; Monitoring ; Automatic scoring
Published in:	Frontiers in Medical Technology, Vol. 3 (july 2021) , ISSN 2673-3129

DOI: 10.3389/fmedt.2021.690442
PMID: 35047935

11 p, 2.5 MB

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Research literature > UAB research groups literature > Research Centres and Groups (research output) > Health sciences and biosciences > Parc Taulí Research and Innovation Institute (I3PT
Articles > Research articles
Articles > Published articles