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Model-based PEEP optimisation in mechanical ventilation
BACKGROUND: Acute Respiratory Distress Syndrome (ARDS) patients require mechanical ventilation (MV) for breathing support. Patient-specific PEEP is encouraged for treating different patients but there is no well established method in optimal PEEP selection. METHODS: A study of 10 patients diagnosed...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3339371/ https://www.ncbi.nlm.nih.gov/pubmed/22196749 http://dx.doi.org/10.1186/1475-925X-10-111 |
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author | Chiew, Yeong Shiong Chase, J Geoffrey Shaw, Geoffrey M Sundaresan, Ashwath Desaive, Thomas |
author_facet | Chiew, Yeong Shiong Chase, J Geoffrey Shaw, Geoffrey M Sundaresan, Ashwath Desaive, Thomas |
author_sort | Chiew, Yeong Shiong |
collection | PubMed |
description | BACKGROUND: Acute Respiratory Distress Syndrome (ARDS) patients require mechanical ventilation (MV) for breathing support. Patient-specific PEEP is encouraged for treating different patients but there is no well established method in optimal PEEP selection. METHODS: A study of 10 patients diagnosed with ALI/ARDS whom underwent recruitment manoeuvre is carried out. Airway pressure and flow data are used to identify patient-specific constant lung elastance (E(lung)) and time-variant dynamic lung elastance (E(drs)) at each PEEP level (increments of 5cmH(2)O), for a single compartment linear lung model using integral-based methods. Optimal PEEP is estimated using E(lung )versus PEEP, E(drs)-Pressure curve and E(drs )Area at minimum elastance (maximum compliance) and the inflection of the curves (diminishing return). Results are compared to clinically selected PEEP values. The trials and use of the data were approved by the New Zealand South Island Regional Ethics Committee. RESULTS: Median absolute percentage fitting error to the data when estimating time-variant E(drs )is 0.9% (IQR = 0.5-2.4) and 5.6% [IQR: 1.8-11.3] when estimating constant E(lung). Both E(lung )and E(drs )decrease with PEEP to a minimum, before rising, and indicating potential over-inflation. Median E(drs )over all patients across all PEEP values was 32.2 cmH(2)O/l [IQR: 26.1-46.6], reflecting the heterogeneity of ALI/ARDS patients, and their response to PEEP, that complicates standard approaches to PEEP selection. All E(drs)-Pressure curves have a clear inflection point before minimum E(drs), making PEEP selection straightforward. Model-based selected PEEP using the proposed metrics were higher than clinically selected values in 7/10 cases. CONCLUSION: Continuous monitoring of the patient-specific E(lung )and E(drs )and minimally invasive PEEP titration provide a unique, patient-specific and physiologically relevant metric to optimize PEEP selection with minimal disruption of MV therapy. |
format | Online Article Text |
id | pubmed-3339371 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33393712012-05-02 Model-based PEEP optimisation in mechanical ventilation Chiew, Yeong Shiong Chase, J Geoffrey Shaw, Geoffrey M Sundaresan, Ashwath Desaive, Thomas Biomed Eng Online Research BACKGROUND: Acute Respiratory Distress Syndrome (ARDS) patients require mechanical ventilation (MV) for breathing support. Patient-specific PEEP is encouraged for treating different patients but there is no well established method in optimal PEEP selection. METHODS: A study of 10 patients diagnosed with ALI/ARDS whom underwent recruitment manoeuvre is carried out. Airway pressure and flow data are used to identify patient-specific constant lung elastance (E(lung)) and time-variant dynamic lung elastance (E(drs)) at each PEEP level (increments of 5cmH(2)O), for a single compartment linear lung model using integral-based methods. Optimal PEEP is estimated using E(lung )versus PEEP, E(drs)-Pressure curve and E(drs )Area at minimum elastance (maximum compliance) and the inflection of the curves (diminishing return). Results are compared to clinically selected PEEP values. The trials and use of the data were approved by the New Zealand South Island Regional Ethics Committee. RESULTS: Median absolute percentage fitting error to the data when estimating time-variant E(drs )is 0.9% (IQR = 0.5-2.4) and 5.6% [IQR: 1.8-11.3] when estimating constant E(lung). Both E(lung )and E(drs )decrease with PEEP to a minimum, before rising, and indicating potential over-inflation. Median E(drs )over all patients across all PEEP values was 32.2 cmH(2)O/l [IQR: 26.1-46.6], reflecting the heterogeneity of ALI/ARDS patients, and their response to PEEP, that complicates standard approaches to PEEP selection. All E(drs)-Pressure curves have a clear inflection point before minimum E(drs), making PEEP selection straightforward. Model-based selected PEEP using the proposed metrics were higher than clinically selected values in 7/10 cases. CONCLUSION: Continuous monitoring of the patient-specific E(lung )and E(drs )and minimally invasive PEEP titration provide a unique, patient-specific and physiologically relevant metric to optimize PEEP selection with minimal disruption of MV therapy. BioMed Central 2011-12-23 /pmc/articles/PMC3339371/ /pubmed/22196749 http://dx.doi.org/10.1186/1475-925X-10-111 Text en Copyright ©2011 Chiew et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Chiew, Yeong Shiong Chase, J Geoffrey Shaw, Geoffrey M Sundaresan, Ashwath Desaive, Thomas Model-based PEEP optimisation in mechanical ventilation |
title | Model-based PEEP optimisation in mechanical ventilation |
title_full | Model-based PEEP optimisation in mechanical ventilation |
title_fullStr | Model-based PEEP optimisation in mechanical ventilation |
title_full_unstemmed | Model-based PEEP optimisation in mechanical ventilation |
title_short | Model-based PEEP optimisation in mechanical ventilation |
title_sort | model-based peep optimisation in mechanical ventilation |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3339371/ https://www.ncbi.nlm.nih.gov/pubmed/22196749 http://dx.doi.org/10.1186/1475-925X-10-111 |
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