Assessing the Severity of COVID-19 Lung Injury in Rheumatic Diseases Versus the General Population Using Deep Learning-Derived Chest Radiograph Scores.

Abstract

ObjectiveCOVID‐19 patients with rheumatic disease have a higher risk of mechanical ventilation than the general population. We assessed lung involvement using a validated deep learning algorithm that extracts a quantitative measure of radiographic lung disease severity.MethodsWe performed a comparative cohort study of rheumatic disease patients with COVID‐19 and ≥1chest radiograph within ±2 weeks of COVID‐19 diagnosis and matched comparators. We used unadjusted and adjusted (for age, Charlson Comorbidity Index, and interstitial lung disease) quantile regression to compare the maximum Pulmonary X‐Ray Severity (PXS) score at the 10th‐90th percentiles between groups. We evaluated the association of severe PXS score (>9) with mechanical ventilation and death using Cox regression.ResultsWe identified 70 patients with rheumatic disease and 463 general population comparators. Maximum PXS scores were similar in the rheumatic disease patients and comparators at the 10th‐60th percentiles but significantly higher among rheumatic disease patients at the 70th‐90th percentiles (90th percentile score of 10.2 vs. 9.2, adjusted p=0.03). Rheumatic disease patients were more likely to have a PXS score >9 (20% vs. 11%, p=0.02), indicating severe pulmonary disease. Rheumatic disease patients with PXS scores >9 vs. ≤9 had higher risk of mechanical ventilation (HR 24.1 [95% CI: 6.7, 86.9]) and death (HR 8.2 [95% CI: 0.7, 90.4]).ConclusionsRheumatic disease patients with COVID‐19 had more severe radiographic lung involvement than comparators. Higher PXS scores were associated with mechanical ventilation and will be important for future studies leveraging big data to assess COVID‐19 outcomes in rheumatic disease patients.This article is protected by copyright. All rights reserved.