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Sci Rep . Chest x-ray imaging score is associated with severity of COVID-19 pneumonia: the MBrixia score

tetano

Editor, Senior Moderator
Sci Rep


. 2022 Dec 5;12(1):21019.
doi: 10.1038/s41598-022-25397-7.
Chest x-ray imaging score is associated with severity of COVID-19 pneumonia: the MBrixia score


Christian M Jensen[SUP] 1 [/SUP], Junia C Costa[SUP] 2 [/SUP], Jens C Nørgaard[SUP] 3 [/SUP], Adrian G Zucco[SUP] 3 [/SUP], Bastian Neesgaard[SUP] 3 [/SUP], Carsten U Niemann[SUP] 4 5 [/SUP], Sisse R Ostrowski[SUP] 5 6 [/SUP], Joanne Reekie[SUP] 3 [/SUP], Birgit Holten[SUP] 2 [/SUP], Anna Kalhauge[SUP] 2 [/SUP], Michael A Matthay[SUP] 7 [/SUP], Jens D Lundgren[SUP] 3 5 8 [/SUP], Marie Helleberg[SUP] 3 8 [/SUP], Kasper S Moestrup[SUP] 3 [/SUP]



Affiliations

Abstract

Spatial resolution in existing chest x-ray (CXR)-based scoring systems for coronavirus disease 2019 (COVID-19) pneumonia is low, and should be increased for better representation of anatomy, and severity of lung involvement. An existing CXR-based system, the Brixia score, was modified to increase the spatial resolution, creating the MBrixia score. The MBrixia score is the sum, of a rule-based quantification of CXR severity on a scale of 0 to 3 in 12 anatomical zones in the lungs. The MBrixia score was applied to CXR images from COVID-19 patients at a single tertiary hospital in the period May 4th-June 5th, 2020. The relationship between MBrixia score, and level of respiratory support at the time of performed CXR imaging was investigated. 37 hospitalized COVID-19 patients with 290 CXRs were identified, 22 (59.5%) were admitted to the intensive care unit and 10 (27%) died during follow-up. In a Poisson regression using all 290 MBrixia scored CXRs, a higher MBrixia score was associated with a higher level of respiratory support at the time of performed CXR. The MBrixia score could potentially be valuable as a quantitative surrogate measurement of COVID-19 pneumonia severity, and future studies should investigate the score's validity and capabilities of predicting clinical outcomes.
 
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