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Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System
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. SyncSmart™ software developed by Breas Me...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8757845/ https://www.ncbi.nlm.nih.gov/pubmed/35047935 http://dx.doi.org/10.3389/fmedt.2021.690442 |
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author | Letellier, Christophe Lujan, Manel Arnal, Jean-Michel Carlucci, Annalisa Chatwin, Michelle Ergan, Begum Kampelmacher, Mike Storre, Jan Hendrik Hart, Nicholas Gonzalez-Bermejo, Jesus Nava, Stefano |
author_facet | Letellier, Christophe Lujan, Manel Arnal, Jean-Michel Carlucci, Annalisa Chatwin, Michelle Ergan, Begum Kampelmacher, Mike Storre, Jan Hendrik Hart, Nicholas Gonzalez-Bermejo, Jesus Nava, Stefano |
author_sort | Letellier, Christophe |
collection | PubMed |
description | 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. SyncSmart™ 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 SyncSmart 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 SyncSmart 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 SynSmart 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 SyncSmart for DT, AT, and IE were significantly greater than those provided by an expert when compared to another expert. Conclusions: SyncSmart 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. |
format | Online Article Text |
id | pubmed-8757845 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87578452022-01-18 Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System Letellier, Christophe Lujan, Manel Arnal, Jean-Michel Carlucci, Annalisa Chatwin, Michelle Ergan, Begum Kampelmacher, Mike Storre, Jan Hendrik Hart, Nicholas Gonzalez-Bermejo, Jesus Nava, Stefano Front Med Technol Medical Technology 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. SyncSmart™ 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 SyncSmart 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 SyncSmart 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 SynSmart 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 SyncSmart for DT, AT, and IE were significantly greater than those provided by an expert when compared to another expert. Conclusions: SyncSmart 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. Frontiers Media S.A. 2021-07-07 /pmc/articles/PMC8757845/ /pubmed/35047935 http://dx.doi.org/10.3389/fmedt.2021.690442 Text en Copyright © 2021 Letellier, Lujan, Arnal, Carlucci, Chatwin, Ergan, Kampelmacher, Storre, Hart, Gonzalez-Bermejo and Nava. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medical Technology Letellier, Christophe Lujan, Manel Arnal, Jean-Michel Carlucci, Annalisa Chatwin, Michelle Ergan, Begum Kampelmacher, Mike Storre, Jan Hendrik Hart, Nicholas Gonzalez-Bermejo, Jesus Nava, Stefano Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System |
title | Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System |
title_full | Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System |
title_fullStr | Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System |
title_full_unstemmed | Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System |
title_short | Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System |
title_sort | patient-ventilator synchronization during non-invasive ventilation: a pilot study of an automated analysis system |
topic | Medical Technology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8757845/ https://www.ncbi.nlm.nih.gov/pubmed/35047935 http://dx.doi.org/10.3389/fmedt.2021.690442 |
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