Çopur Betül, Sürme Serkan, Tunçer Gülşah, Bayramlar Osman Faruk
Department of Infectious Diseases and Clinical Microbiology, Haseki Training and Research Hospital, İstanbul, Turkey.
Department of Medical Microbiology, Institute of Graduate Studies, İstanbul University-Cerrahpasa, Istanbul, Turkey.
Infect Dis Clin Microbiol. 2023 Jun 23;5(2):144-152. doi: 10.36519/idcm.2023.233. eCollection 2023 Jun.
Predictors of mortality that indicate disease severity plays an important role in COVID-19 management and treatment decisions. This study aimed to investigate the association between fibrosis-4 (FIB-4) score, aspartate aminotransferase-to-platelet ratio index (APRI), and novel biomarker-based score (SAD-60) with mortality in COVID-19 patients treated in a tertiary hospital.
In this single-center retrospective study, patients ≥18 years of age who were admitted to our hospital for COVID-19 between December 1 and 31, 2021, were included. Patients were divided into two groups as deceased and survived. A comparative analysis was applied. Predictive abilities of the FIB-4, APRI, and SAD-60 scores for in-hospital mortality were evaluated.
Of the 453 patients enrolled in the study, 248 (54.6%) were male, and the mean age was 52.2±14.7 years. Mortality was recorded in 39 (8.5%) of the patients. The median values of APRI (0.43 and 0.58; p=0.001), FIB-4 score (1.66 and 2.91; p<0.001), and SAD-60 (2 and 8.25; p<0.001) were higher in deceased patients than in survivors. The optimal cut-off value for predicting mortality in the receiver operating characteristic (ROC) curve analysis was 0.58 for APRI (sensitivity=56.4%, specificity=63.6%); 2.14 for FIB-4 score (sensitivity=79.5%, specificity=68.2%); 4.25 for SAD-60 (sensitivity=90%, specificity=73.8%). In Cox regression analysis with a model that included gender, chronic obstructive pulmonary disease (COPD), and coronary artery disease (CAD), FIB-4 (hazard ratio [HR]=4.013, 95% confidence interval [CI]=1.643-9.803; p=0.002), and SAD-60 (HR=8.850, 95% CI=1.035-75.696; p=0.046) were independent risk factors for mortality.
SAD-60 and FIB-4 scores are easily applicable and may be used to predict mortality in COVID-19 patients.
表明疾病严重程度的死亡率预测指标在新冠病毒病(COVID-19)的管理和治疗决策中起着重要作用。本研究旨在调查在一家三级医院接受治疗的COVID-19患者中,纤维化-4(FIB-4)评分、天冬氨酸氨基转移酶与血小板比值指数(APRI)以及基于新型生物标志物的评分(SAD-60)与死亡率之间的关联。
在这项单中心回顾性研究中,纳入了2021年12月1日至31日因COVID-19入住我院的18岁及以上患者。患者分为死亡组和存活组,进行比较分析。评估FIB-4、APRI和SAD-60评分对住院死亡率的预测能力。
本研究共纳入453例患者,其中248例(54.6%)为男性,平均年龄为52.2±14.7岁。39例(8.5%)患者记录有死亡情况。死亡患者的APRI中位数(0.43和0.58;p=0.001)、FIB-4评分中位数(1.66和2.91;p<0.001)和SAD-60中位数(2和8.25;p<0.001)均高于存活患者。在受试者工作特征(ROC)曲线分析中,预测死亡率的最佳截断值为:APRI为0.58(灵敏度=56.4%,特异度=63.6%);FIB-4评分为2.14(灵敏度=79.5%,特异度=68.2%);SAD-60为4.25(灵敏度=90%,特异度=73.8%)。在包含性别、慢性阻塞性肺疾病(COPD)和冠状动脉疾病(CAD)的模型进行的Cox回归分析中,FIB-4(风险比[HR]=4.013,95%置信区间[CI]=1.643-9.803;p=0.002)和SAD-60(HR=8.850,95%CI=1.035-75.696;p=0.046)是死亡率的独立危险因素。
SAD-60和FIB-4评分易于应用,可用于预测COVID-19患者的死亡率。