Sines Benjamin J, Jakharia Kunal K, Lu Chih-Huan, Appleton Leslie, Rice Colleen, Fischer William A, Wallet Shannon M, DeCherney G Stephen, Mock Jason R, Drummond M Bradley
Division of Pulmonary Diseases and Critical Care Medicine, Department of Medicine, University of North Carolina Chapel Hill, 4th Floor Bioinformatics Bldg 130 Mason Farm Road, Chapel Hill, NC, 27599, USA.
Department of Internal Medicine, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
Sci Rep. 2025 Aug 2;15(1):28254. doi: 10.1038/s41598-025-08822-5.
Identifying patients at high mortality risk can improve outcomes in SARS-CoV-2 pneumonia (COVID-19). We validate a prognostic model for mortality in patients hospitalized with COVID-19 receiving dexamethasone using a retrospective multi-centered study. This is a retrospective cohort study using the National COVID Cohort Collaborative (NC3) including 9,708 adult patients admitted for COVID-19 who received dexamethasone within 24 h of admission and remained hospitalized for 72 h. Previous work from a single-center cohort informed selection of prognostic variables including Age, day 3 neutrophil-lymphocyte Ratio, and day 3 C-reactive protein level (ARC Score). Variables from the development cohort were analyzed in a training cohort, and the resulting model was tested in a validation cohort. Age and day 3 measures of the neutrophil-lymphocyte ratio and C-reactive protein level were included in a logistic regression model to predict 28-day mortality. The 28-day mortality in this patient population was 15.4%. The area under the curve for the ARC model was 0.77 (95% confidence interval, 0.74-0.79). The Age, neutrophil-lymphocyte Ratio, and C-reactive protein (ARC) score identifies COVID-19 patients with a high risk of mortality within 28 days of hospitalization using clinical information on day 3 of hospitalization. ARC scores perform well across all variants of concern.
识别高死亡风险患者可改善新冠病毒肺炎（COVID-19）的治疗结果。我们通过一项回顾性多中心研究，验证了使用地塞米松治疗的COVID-19住院患者的死亡预后模型。这是一项回顾性队列研究，使用了国家COVID队列协作组（NC3）的数据，纳入了9708例因COVID-19入院的成年患者，这些患者在入院后24小时内接受了地塞米松治疗，并住院72小时。先前来自单中心队列的研究为预后变量的选择提供了依据，这些变量包括年龄、第3天中性粒细胞与淋巴细胞比值以及第3天C反应蛋白水平（ARC评分）。在一个训练队列中分析了来自开发队列的变量，并在一个验证队列中测试了所得模型。将年龄、第3天的中性粒细胞与淋巴细胞比值和C反应蛋白水平纳入逻辑回归模型，以预测28天死亡率。该患者群体的28天死亡率为15.4%。ARC模型的曲线下面积为0.77（95%置信区间，0.74 - 0.79）。年龄、中性粒细胞与淋巴细胞比值和C反应蛋白（ARC）评分可利用住院第3天的临床信息，识别出住院28天内有高死亡风险的COVID-19患者。ARC评分在所有关注的变异株中表现良好。
