Xiao Benjie, Yang Zhangwei, Liang Huazheng, Han Yudi, Wu Yinyan, Xiao Jingjing, Bi Yong
Department of Neurology, Zhoupu Hospital Affiliated to Shanghai University of Medicine & Health Sciences, Shanghai, China.
Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Front Med (Lausanne). 2024 Jul 31;11:1410179. doi: 10.3389/fmed.2024.1410179. eCollection 2024.
Although the impact of the variants of COVID-19 on the general population is diminishing, there is still a certain mortality rate for severe and critically ill patients, especially for the elderly with comorbidities. The present study investigated whether the D-dimer to albumin ratio (DAR) can predict the severity of illness and mortality in COVID-19 patients.
A total of 1,993 patients with COVID-19 were retrospectively reviewed and the association of DAR with severe or critical illness or death during hospitalization was analyzed. The area under the ROC curve was used to screen the best indicators, Chi-square test, rank sum test, and univariate and multivariate binary logistic regression analysis were used to calculate the mean value of difference and adjusted odds ratio (aORs) with their 95% CI, and finally, survival was analyzed using Kaplan-Meier (KM) curves.
Among 1,993 patients with COVID-19, 13.4% were severely ill, and the mortality rate was 2.3%. The area under the curve (AUC) using DAR to predict severe and critically ill patients was higher than that using other parameters. The best cut-off value of DAR was 21 in the ROC with a sensitivity of 83.1% and a specificity of 68.7%. After adjusting age, gender, comorbidities, and treatment, the binary logistic regression analysis showed that elevated DAR was an independent risk factor for severely ill and mortality of COVID-19 patients. The KM curve suggested that patients with a higher DAR was associated with worse survival. The negative predictive value of DAR (21) for adverse prognosis and death was 95.98 and 99.84%, respectively, with a sensitivity of 80.9 and 95.65%, respectively.
The DAR may be an important predictor for severe illness and mortality in COVID-19 patients.
尽管新冠病毒变异株对普通人群的影响正在减弱,但重症和危重症患者仍有一定死亡率,尤其是合并症的老年患者。本研究调查了D-二聚体与白蛋白比值(DAR)是否可预测新冠患者的疾病严重程度和死亡率。
回顾性分析1993例新冠患者,分析DAR与住院期间重症或危重症或死亡的相关性。采用ROC曲线下面积筛选最佳指标,运用卡方检验、秩和检验以及单因素和多因素二元逻辑回归分析计算差异均值和调整优势比(aORs)及其95%置信区间,最后采用Kaplan-Meier(KM)曲线分析生存情况。
1993例新冠患者中,13.4%为重症,死亡率为2.3%。使用DAR预测重症和危重症患者的曲线下面积(AUC)高于使用其他参数。DAR在ROC中的最佳截断值为21,灵敏度为83.1%,特异度为68.7%。在调整年龄、性别、合并症和治疗因素后,二元逻辑回归分析显示,DAR升高是新冠患者重症和死亡的独立危险因素。KM曲线表明,DAR较高的患者生存情况较差。DAR(21)对不良预后和死亡的阴性预测值分别为95.98和99.84%,灵敏度分别为80.9和95.65%。
DAR可能是新冠患者重症和死亡的重要预测指标。