Abstract

BackgroundEarly identification of risk factors for adverse COVID-19 progression in patients with autoimmune diseases is crucial for patient management, but data on the Chinese population are scarce. ObjectivesThe purpose of this study was to identify predictors of severe COVID-19 in patients using blood cell ratios, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and other inflammatory markers. MethodsA retrospective study of 855 patients (746 females; median age 49 years) with autoimmune diseases and concurrent COVID-19 was conducted from December 2022 to February 2023 at the Rheumatology and Immunology Department of the First Affiliated Hospital of Nanchang University. Disease severity was assessed according to the 8th edition of the National Health Commission of the People's Republic of China's COVID-19 Diagnosis and Treatment Guidelines. The clinical classification criteria group mild and moderate cases as nonsevere cases and severe and critical cases as severe cases. A multivariate logistic regression model was established to evaluate the relationships between COVID-19 severity and demographic characteristics, comorbidities, medication use, and laboratory findings. ResultsThe PLR, NLR, and SII were significantly greater in the severe COVID-19 group than in the nonsevere group (all P < 0.05). In addition to classical independent clinical risk factors, increases in the PLR (OR: 1.004, 95 % CI: 1.001∼1.007, p = 0.001), NLR (OR: 1.180, 95 % CI: 1.041∼1.337, p = 0.010), and SII (OR: 0.999, 95 % CI: 0.998∼1.000, p = 0.005) were identified as risk factors for severe COVID-19 in patients with autoimmune diseases. After adjusting for clinical risk factors, the PLR (AUC: 0.592 vs. 0.865; P < 0.05), NLR (AUC: 0.670 vs. 0.866; P < 0.05), and SII (AUC: 0.616 vs. 0.864; P < 0.05) demonstrated higher predictive values. ConclusionEarly prediction of severe COVID-19 in patients with autoimmune diseases can be achieved using the NLR, PLR, and SII.

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