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Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography

INTRODUCTION: Coronavirus disease-2019 (COVID-19) pneumonia has different phenotypes. Selecting the patient individualized and optimal respirator settings for the ventilated patient is a challenging process. Electric impedance tomography (EIT) is a real-time, radiation-free functional imaging techni...

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Autores principales: Lovas, András, Chen, Rongqing, Molnár, Tamás, Benyó, Balázs, Szlávecz, Ákos, Hawchar, Fatime, Krüger-Ziolek, Sabine, Möller, Knut
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9161711/
https://www.ncbi.nlm.nih.gov/pubmed/35665323
http://dx.doi.org/10.3389/fmed.2022.747570
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author Lovas, András
Chen, Rongqing
Molnár, Tamás
Benyó, Balázs
Szlávecz, Ákos
Hawchar, Fatime
Krüger-Ziolek, Sabine
Möller, Knut
author_facet Lovas, András
Chen, Rongqing
Molnár, Tamás
Benyó, Balázs
Szlávecz, Ákos
Hawchar, Fatime
Krüger-Ziolek, Sabine
Möller, Knut
author_sort Lovas, András
collection PubMed
description INTRODUCTION: Coronavirus disease-2019 (COVID-19) pneumonia has different phenotypes. Selecting the patient individualized and optimal respirator settings for the ventilated patient is a challenging process. Electric impedance tomography (EIT) is a real-time, radiation-free functional imaging technique that can aid clinicians in differentiating the “low” (L-) and “high” (H-) phenotypes of COVID-19 pneumonia described previously. METHODS: Two patients (“A” and “B”) underwent a stepwise positive end-expiratory pressure (PEEP) recruitment by 3 cmH(2)O of steps from PEEP 10 to 25 and back to 10 cmH(2)O during a pressure control ventilation of 15 cmH(2)O. Recruitment maneuvers were performed under continuous EIT recording on a daily basis until patients required controlled ventilation mode. RESULTS: Patients “A” and “B” had a 7- and 12-day long trial, respectively. At the daily baseline, patient “A” had significantly higher compliance: mean ± SD = 53 ± 7 vs. 38 ± 5 ml/cmH(2)O (p < 0.001) and a significantly higher physiological dead space according to the Bohr–Enghoff equation than patient “B”: mean ± SD = 52 ± 4 vs. 45 ± 6% (p = 0.018). Following recruitment maneuvers, patient “A” had a significantly higher cumulative collapse ratio detected by EIT than patient “B”: mean ± SD = 0.40 ± 0.08 vs. 0.29 ± 0.08 (p = 0.007). In patient “A,” there was a significant linear regression between the cumulative collapse ratios at the end of the recruitment maneuvers (R(2) = 0.824, p = 0.005) by moving forward in days, while not for patient “B” (R(2) = 0.329, p = 0.5). CONCLUSION: Patient “B” was recognized as H-phenotype with high elastance, low compliance, higher recruitability, and low ventilation-to-perfusion ratio; meanwhile patient “A” was identified as the L-phenotype with low elastance, high compliance, and lower recruitability. Observation by EIT was not just able to differentiate the two phenotypes, but it also could follow the transition from L- to H-type within patient “A.” CLINICAL TRIAL REGISTRATION: www.ClinicalTrials.gov, identifier: NCT04360837.
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spelling pubmed-91617112022-06-03 Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography Lovas, András Chen, Rongqing Molnár, Tamás Benyó, Balázs Szlávecz, Ákos Hawchar, Fatime Krüger-Ziolek, Sabine Möller, Knut Front Med (Lausanne) Medicine INTRODUCTION: Coronavirus disease-2019 (COVID-19) pneumonia has different phenotypes. Selecting the patient individualized and optimal respirator settings for the ventilated patient is a challenging process. Electric impedance tomography (EIT) is a real-time, radiation-free functional imaging technique that can aid clinicians in differentiating the “low” (L-) and “high” (H-) phenotypes of COVID-19 pneumonia described previously. METHODS: Two patients (“A” and “B”) underwent a stepwise positive end-expiratory pressure (PEEP) recruitment by 3 cmH(2)O of steps from PEEP 10 to 25 and back to 10 cmH(2)O during a pressure control ventilation of 15 cmH(2)O. Recruitment maneuvers were performed under continuous EIT recording on a daily basis until patients required controlled ventilation mode. RESULTS: Patients “A” and “B” had a 7- and 12-day long trial, respectively. At the daily baseline, patient “A” had significantly higher compliance: mean ± SD = 53 ± 7 vs. 38 ± 5 ml/cmH(2)O (p < 0.001) and a significantly higher physiological dead space according to the Bohr–Enghoff equation than patient “B”: mean ± SD = 52 ± 4 vs. 45 ± 6% (p = 0.018). Following recruitment maneuvers, patient “A” had a significantly higher cumulative collapse ratio detected by EIT than patient “B”: mean ± SD = 0.40 ± 0.08 vs. 0.29 ± 0.08 (p = 0.007). In patient “A,” there was a significant linear regression between the cumulative collapse ratios at the end of the recruitment maneuvers (R(2) = 0.824, p = 0.005) by moving forward in days, while not for patient “B” (R(2) = 0.329, p = 0.5). CONCLUSION: Patient “B” was recognized as H-phenotype with high elastance, low compliance, higher recruitability, and low ventilation-to-perfusion ratio; meanwhile patient “A” was identified as the L-phenotype with low elastance, high compliance, and lower recruitability. Observation by EIT was not just able to differentiate the two phenotypes, but it also could follow the transition from L- to H-type within patient “A.” CLINICAL TRIAL REGISTRATION: www.ClinicalTrials.gov, identifier: NCT04360837. Frontiers Media S.A. 2022-05-19 /pmc/articles/PMC9161711/ /pubmed/35665323 http://dx.doi.org/10.3389/fmed.2022.747570 Text en Copyright © 2022 Lovas, Chen, Molnár, Benyó, Szlávecz, Hawchar, Krüger-Ziolek and Möller. 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 Medicine
Lovas, András
Chen, Rongqing
Molnár, Tamás
Benyó, Balázs
Szlávecz, Ákos
Hawchar, Fatime
Krüger-Ziolek, Sabine
Möller, Knut
Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography
title Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography
title_full Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography
title_fullStr Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography
title_full_unstemmed Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography
title_short Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography
title_sort differentiating phenotypes of coronavirus disease-2019 pneumonia by electric impedance tomography
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9161711/
https://www.ncbi.nlm.nih.gov/pubmed/35665323
http://dx.doi.org/10.3389/fmed.2022.747570
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