Predictors of COVID-19 severity in autoimmune disease patients: A retrospective study during full epidemic decontrol in China

IF 2.4 4区 医学 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS Heart & Lung Pub Date : 2024-08-13 DOI:10.1016/j.hrtlng.2024.08.009
Li-Ming Chen , Jian-Bin Li , Rui Wu
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Abstract

Background

Early 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.

Objectives

The 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.

Methods

A 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.

Results

The 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.

Conclusion

Early prediction of severe COVID-19 in patients with autoimmune diseases can be achieved using the NLR, PLR, and SII.

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自身免疫性疾病患者 COVID-19 严重程度的预测因素:中国疫情全面控制期间的回顾性研究
背景早期识别自身免疫性疾病患者COVID-19不良进展的风险因素对患者管理至关重要,但有关中国人群的数据很少。目的本研究旨在利用血细胞比值,如中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)、全身免疫炎症指数(SII)和其他炎症标志物,识别患者严重COVID-19的预测因素。方法 2022年12月至2023年2月,南昌大学第一附属医院风湿免疫科对855名患有自身免疫性疾病并同时患有COVID-19的患者(女性746人,中位年龄49岁)进行了回顾性研究。疾病严重程度根据中华人民共和国国家卫生健康委员会《COVID-19诊疗指南》第八版进行评估。临床分级标准将轻度和中度病例归为非重度病例,将重度和危重病例归为重度病例。结果 COVID-19 重症组的 PLR、NLR 和 SII 显著高于非重症组(P 均为 0.05)。除了传统的独立临床危险因素外,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)和 SII(OR:0.999,95 % CI:0.998∼1.000,p = 0.005)被确定为自身免疫性疾病患者严重 COVID-19 的危险因素。在调整临床风险因素后,PLR(AUC:0.592 vs. 0.865;P <;0.05)、NLR(AUC:0.670 vs. 0.866;P <;0.05)和 SII(AUC:0.616 vs. 0.864;P <;0.05)显示出更高的预测价值。
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来源期刊
Heart & Lung
Heart & Lung 医学-呼吸系统
CiteScore
4.60
自引率
3.60%
发文量
184
审稿时长
35 days
期刊介绍: Heart & Lung: The Journal of Cardiopulmonary and Acute Care, the official publication of The American Association of Heart Failure Nurses, presents original, peer-reviewed articles on techniques, advances, investigations, and observations related to the care of patients with acute and critical illness and patients with chronic cardiac or pulmonary disorders. The Journal''s acute care articles focus on the care of hospitalized patients, including those in the critical and acute care settings. Because most patients who are hospitalized in acute and critical care settings have chronic conditions, we are also interested in the chronically critically ill, the care of patients with chronic cardiopulmonary disorders, their rehabilitation, and disease prevention. The Journal''s heart failure articles focus on all aspects of the care of patients with this condition. Manuscripts that are relevant to populations across the human lifespan are welcome.
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