Cargando…

Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia

Busana et al. (doi.org/10.1152/japplphysiol.00871.2020) published 5 patients with COVID-19 in whom the fraction of non-aerated lung tissue had been quantified by computed tomography. They assumed that shunt flow fraction was proportional to the non-aerated lung fraction, and, by randomly generating...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Haopeng, Petousi, Nayia, Robbins, Peter A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9426945/
https://www.ncbi.nlm.nih.gov/pubmed/36040974
http://dx.doi.org/10.1371/journal.pone.0273214
_version_ 1784778792894464000
author Xu, Haopeng
Petousi, Nayia
Robbins, Peter A.
author_facet Xu, Haopeng
Petousi, Nayia
Robbins, Peter A.
author_sort Xu, Haopeng
collection PubMed
description Busana et al. (doi.org/10.1152/japplphysiol.00871.2020) published 5 patients with COVID-19 in whom the fraction of non-aerated lung tissue had been quantified by computed tomography. They assumed that shunt flow fraction was proportional to the non-aerated lung fraction, and, by randomly generating 10(6) different bimodal distributions for the ventilation-perfusion ([Image: see text] ) ratios in the lung, specified as sets of paired values {[Image: see text] }, sought to identify as solutions those that generated the observed arterial partial pressures of CO(2) and O(2) (Pa(CO2) and Pa(O2)). Our study sought to develop a direct method of calculation to replace the approach of randomly generating different distributions, and so provide more accurate solutions that were within the measurement error of the blood-gas data. For the one patient in whom Busana et al. did not find solutions, we demonstrated that the assumed shunt flow fraction led to a non-shunt blood flow that was too low to support the required gas exchange. For the other four patients, we found precise solutions (prediction error < 1x10(-3) mmHg for both Pa(CO2) and Pa(O2)), with distributions qualitatively similar to those of Busana et al. These distributions were extremely wide and unlikely to be physically realisable, because they predict the maintenance of very large concentration gradients in regions of the lung where convection is slow. We consider that these wide distributions arise because the assumed value for shunt flow is too low in these patients, and we discuss possible reasons why the assumption relating to shunt flow fraction may break down in COVID-19 pneumonia.
format Online
Article
Text
id pubmed-9426945
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-94269452022-08-31 Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia Xu, Haopeng Petousi, Nayia Robbins, Peter A. PLoS One Research Article Busana et al. (doi.org/10.1152/japplphysiol.00871.2020) published 5 patients with COVID-19 in whom the fraction of non-aerated lung tissue had been quantified by computed tomography. They assumed that shunt flow fraction was proportional to the non-aerated lung fraction, and, by randomly generating 10(6) different bimodal distributions for the ventilation-perfusion ([Image: see text] ) ratios in the lung, specified as sets of paired values {[Image: see text] }, sought to identify as solutions those that generated the observed arterial partial pressures of CO(2) and O(2) (Pa(CO2) and Pa(O2)). Our study sought to develop a direct method of calculation to replace the approach of randomly generating different distributions, and so provide more accurate solutions that were within the measurement error of the blood-gas data. For the one patient in whom Busana et al. did not find solutions, we demonstrated that the assumed shunt flow fraction led to a non-shunt blood flow that was too low to support the required gas exchange. For the other four patients, we found precise solutions (prediction error < 1x10(-3) mmHg for both Pa(CO2) and Pa(O2)), with distributions qualitatively similar to those of Busana et al. These distributions were extremely wide and unlikely to be physically realisable, because they predict the maintenance of very large concentration gradients in regions of the lung where convection is slow. We consider that these wide distributions arise because the assumed value for shunt flow is too low in these patients, and we discuss possible reasons why the assumption relating to shunt flow fraction may break down in COVID-19 pneumonia. Public Library of Science 2022-08-30 /pmc/articles/PMC9426945/ /pubmed/36040974 http://dx.doi.org/10.1371/journal.pone.0273214 Text en © 2022 Xu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Xu, Haopeng
Petousi, Nayia
Robbins, Peter A.
Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia
title Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia
title_full Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia
title_fullStr Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia
title_full_unstemmed Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia
title_short Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia
title_sort identifying putative ventilation-perfusion distributions in covid-19 pneumonia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9426945/
https://www.ncbi.nlm.nih.gov/pubmed/36040974
http://dx.doi.org/10.1371/journal.pone.0273214
work_keys_str_mv AT xuhaopeng identifyingputativeventilationperfusiondistributionsincovid19pneumonia
AT petousinayia identifyingputativeventilationperfusiondistributionsincovid19pneumonia
AT robbinspetera identifyingputativeventilationperfusiondistributionsincovid19pneumonia