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Assessing the Asynchrony Event Based on the Ventilation Mode for Mechanically Ventilated Patients in ICU

Respiratory system modelling can assist clinicians in making clinical decisions during mechanical ventilation (MV) management in intensive care. However, there are some cases where the MV patients produce asynchronous breathing (asynchrony events) due to the spontaneous breathing (SB) effort even th...

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Autores principales: Muhamad Sauki, Nur Sa’adah, Damanhuri, Nor Salwa, Othman, Nor Azlan, Chiew Meng, Belinda Chong, Chiew, Yeong Shiong, Mat Nor, Mohd Basri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8698314/
https://www.ncbi.nlm.nih.gov/pubmed/34940375
http://dx.doi.org/10.3390/bioengineering8120222
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author Muhamad Sauki, Nur Sa’adah
Damanhuri, Nor Salwa
Othman, Nor Azlan
Chiew Meng, Belinda Chong
Chiew, Yeong Shiong
Mat Nor, Mohd Basri
author_facet Muhamad Sauki, Nur Sa’adah
Damanhuri, Nor Salwa
Othman, Nor Azlan
Chiew Meng, Belinda Chong
Chiew, Yeong Shiong
Mat Nor, Mohd Basri
author_sort Muhamad Sauki, Nur Sa’adah
collection PubMed
description Respiratory system modelling can assist clinicians in making clinical decisions during mechanical ventilation (MV) management in intensive care. However, there are some cases where the MV patients produce asynchronous breathing (asynchrony events) due to the spontaneous breathing (SB) effort even though they are fully sedated. Currently, most of the developed models are only suitable for fully sedated patients, which means they cannot be implemented for patients who produce asynchrony in their breathing. This leads to an incorrect measurement of the actual underlying mechanics in these patients. As a result, there is a need to develop a model that can detect asynchrony in real-time and at the bedside throughout the ventilated days. This paper demonstrates the asynchronous event detection of MV patients in the ICU of a hospital by applying a developed extended time-varying elastance model. Data from 10 mechanically ventilated respiratory failure patients admitted at the International Islamic University Malaysia (IIUM) Hospital were collected. The results showed that the model-based technique precisely detected asynchrony events (AEs) throughout the ventilation days. The patients showed an increase in AEs during the ventilation period within the same ventilation mode. SIMV mode produced much higher asynchrony compared to SPONT mode (p < 0.05). The link between AEs and the lung elastance ([Formula: see text] was also investigated. It was found that when the AEs increased, the [Formula: see text] decreased and vice versa based on the results obtained in this research. The information of AEs and [Formula: see text] provides the true underlying lung mechanics of the MV patients. Hence, this model-based method is capable of detecting the AEs in fully sedated MV patients and providing information that can potentially guide clinicians in selecting the optimal ventilation mode of MV, allowing for precise monitoring of respiratory mechanics in MV patients.
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spelling pubmed-86983142021-12-24 Assessing the Asynchrony Event Based on the Ventilation Mode for Mechanically Ventilated Patients in ICU Muhamad Sauki, Nur Sa’adah Damanhuri, Nor Salwa Othman, Nor Azlan Chiew Meng, Belinda Chong Chiew, Yeong Shiong Mat Nor, Mohd Basri Bioengineering (Basel) Article Respiratory system modelling can assist clinicians in making clinical decisions during mechanical ventilation (MV) management in intensive care. However, there are some cases where the MV patients produce asynchronous breathing (asynchrony events) due to the spontaneous breathing (SB) effort even though they are fully sedated. Currently, most of the developed models are only suitable for fully sedated patients, which means they cannot be implemented for patients who produce asynchrony in their breathing. This leads to an incorrect measurement of the actual underlying mechanics in these patients. As a result, there is a need to develop a model that can detect asynchrony in real-time and at the bedside throughout the ventilated days. This paper demonstrates the asynchronous event detection of MV patients in the ICU of a hospital by applying a developed extended time-varying elastance model. Data from 10 mechanically ventilated respiratory failure patients admitted at the International Islamic University Malaysia (IIUM) Hospital were collected. The results showed that the model-based technique precisely detected asynchrony events (AEs) throughout the ventilation days. The patients showed an increase in AEs during the ventilation period within the same ventilation mode. SIMV mode produced much higher asynchrony compared to SPONT mode (p < 0.05). The link between AEs and the lung elastance ([Formula: see text] was also investigated. It was found that when the AEs increased, the [Formula: see text] decreased and vice versa based on the results obtained in this research. The information of AEs and [Formula: see text] provides the true underlying lung mechanics of the MV patients. Hence, this model-based method is capable of detecting the AEs in fully sedated MV patients and providing information that can potentially guide clinicians in selecting the optimal ventilation mode of MV, allowing for precise monitoring of respiratory mechanics in MV patients. MDPI 2021-12-18 /pmc/articles/PMC8698314/ /pubmed/34940375 http://dx.doi.org/10.3390/bioengineering8120222 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Muhamad Sauki, Nur Sa’adah
Damanhuri, Nor Salwa
Othman, Nor Azlan
Chiew Meng, Belinda Chong
Chiew, Yeong Shiong
Mat Nor, Mohd Basri
Assessing the Asynchrony Event Based on the Ventilation Mode for Mechanically Ventilated Patients in ICU
title Assessing the Asynchrony Event Based on the Ventilation Mode for Mechanically Ventilated Patients in ICU
title_full Assessing the Asynchrony Event Based on the Ventilation Mode for Mechanically Ventilated Patients in ICU
title_fullStr Assessing the Asynchrony Event Based on the Ventilation Mode for Mechanically Ventilated Patients in ICU
title_full_unstemmed Assessing the Asynchrony Event Based on the Ventilation Mode for Mechanically Ventilated Patients in ICU
title_short Assessing the Asynchrony Event Based on the Ventilation Mode for Mechanically Ventilated Patients in ICU
title_sort assessing the asynchrony event based on the ventilation mode for mechanically ventilated patients in icu
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8698314/
https://www.ncbi.nlm.nih.gov/pubmed/34940375
http://dx.doi.org/10.3390/bioengineering8120222
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