Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Novel Risks of Unfavorable Corticosteroid Response in Patients with COVID-19 Identified by Artificial Intelligence-Assisted Analysis of Chest Radiographs

Min Hyung Kim
ORCID logo ,
Hyun Joo Shin
ORCID logo ,
Jaewoong Kim
ORCID logo ,
Sunhee Jo
,
Eun-Kyung Kim
,
Yoon Soo Park
,
Taeyoung Kyong
* ORCID logo
Version 1 : Received: 27 July 2023 / Approved: 28 July 2023 / Online: 28 July 2023 (11:50:44 CEST)

A peer-reviewed article of this Preprint also exists.

Kim, M.H.; Shin, H.J.; Kim, J.; Jo, S.; Kim, E.-K.; Park, Y.S.; Kyong, T. Novel Risks of Unfavorable Corticosteroid Response in Patients with Mild-to-Moderate COVID-19 Identified Using Artificial Intelligence-Assisted Analysis of Chest Radiographs. J. Clin. Med. 2023, 12, 5852. Kim, M.H.; Shin, H.J.; Kim, J.; Jo, S.; Kim, E.-K.; Park, Y.S.; Kyong, T. Novel Risks of Unfavorable Corticosteroid Response in Patients with Mild-to-Moderate COVID-19 Identified Using Artificial Intelligence-Assisted Analysis of Chest Radiographs. J. Clin. Med. 2023, 12, 5852.

Abstract

The prediction of corticosteroid responses in coronavirus disease 2019 (COVID-19) patients is crucial in clinical practice, and exploring the role of artificial intelligence (AI)-assisted analysis of chest radiographs (CXR) is warranted. This retrospective case-control study involving hospitalized COVID-19 patients treated with corticosteroids was conducted from September 4th, 2021, to August 30th, 2022. The primary endpoint of the study was corticosteroid responsiveness, defined as the advancement of two or more of the eight-categories-ordinal scale. Serial abnormality scores for consolidation and pleural effusion on CXR were obtained using a commercial AI-based software based on days from onset of symptoms. Amongst the 258 participants included in the analysis, 147 (57%) were male. Multivariable logistic regression analysis revealed that high pleural effusion score at 6–9 days from onset of symptoms (adjusted odds ratio of [aOR]: 1.022, 95% confidence interval [CI]: 1.003-1.042, p=0.020) and consolidation scores up to 9 days from onset of symptoms (0-2 days: aOR: 1.025, 95% CI: 1.006-1.045, p=0.010; 3-5 days: aOR: 1.03 95% CI: 1.011-1.051, p=0.002; 6-9 days: aOR; 1.052, 95% CI: 1.015-1.089, p=0.005) were associated with an unfavorable corticosteroid response. AI-generated scores could help intervene in the use of corticosteroids in COVID-19 patients who would not benefit from them

Keywords

artificial intelligence; chest radiograph; corticosteroid responsiveness; COVID-19

Subject

Medicine and Pharmacology, Internal Medicine

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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