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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Bibliographic Details
Main Authors: Lovas András
Chen Rongqing
Molnár Tamás
Benyó Balázs István
Szlávecz Ákos József
Hawchar Fatime
Krüger-Ziolek Sabine
Möller Knut
Format: Article
Published: 2022
Series:FRONTIERS IN MEDICINE 9
Subjects:
doi:10.3389/fmed.2022.747570

mtmt:32866513
Online Access:http://publicatio.bibl.u-szeged.hu/30052
Description
Summary: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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ISSN:2296-858X