Sharma Praveen, Naseem Shano, Varma Neelam, Khaire Niranjan, Jindal Nishant, Sharma Abhishek, Verma Brijesh, Malhotra Pankaj, Bastian Sandhya, Sukhacheva Elena
Department of Hematology, Postgraduate Institute of Medical Education and Research, Chandigarh, 160012 India.
Department of Internal Medicine (Clinical Hematology Division), Postgraduate Institute of Medical Education and Research, Chandigarh, India.
Indian J Hematol Blood Transfus. 2023 May 20;40(1):1-5. doi: 10.1007/s12288-023-01665-y.
Identifying patients with Coronavirus disease-2019 (COVID-19) who may have a severe illness is essential for timely intervention and decreasing the fatality rate. In the present study, we evaluated the performance of Monocyte Distribution Width (MDW) as a prognostic marker for identifying disease severity in COVID-19 patients. We included 145 patients with PCR-confirmed COVID-19 infection in the study. The performance of MDW was evaluated by calculating the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, negative predictive value, and positive predictive value. Further analysis was conducted for the disease outcome, comparing COVID-19 patients discharged ( = 135) to deceased COVID-19 patients ( = 10). As a marker of disease severity, MDW demonstrated an AUC of 0.702 (95% CI 0.620-0.775) in ROC analysis. If MDW is considered a marker of patient outcome, AUC was 0.916 (95% CI 0.862-0.953), comparing deceased COVID-19 patients vs. those who survived. At a cut-off of > 25.4 on admission, MDW correlates well with poor disease outcomes in COVID-19 patients. MDW can be considered a helpful parameter in predicting the severity of COVID-19 disease and patient outcomes. Its role and incorporation in the standard diagnostic algorithm and management of COVID-19 patients need further validation.
The online version contains supplementary material available at 10.1007/s12288-023-01665-y.
识别可能患有重症的2019冠状病毒病(COVID-19)患者对于及时干预和降低死亡率至关重要。在本研究中,我们评估了单核细胞分布宽度(MDW)作为识别COVID-19患者疾病严重程度的预后标志物的性能。我们纳入了145例经PCR确诊为COVID-19感染的患者进行研究。通过计算受试者工作特征曲线(ROC)下面积、特异性、敏感性、阴性预测值和阳性预测值来评估MDW的性能。对疾病结局进行了进一步分析,比较了出院的COVID-19患者(n = 135)和死亡的COVID-19患者(n = 10)。作为疾病严重程度的标志物,MDW在ROC分析中的AUC为0.702(95%CI 0.620 - 0.775)。如果将MDW视为患者结局的标志物,比较死亡的COVID-19患者与存活患者时,AUC为0.916(95%CI 0.862 - 0.953)。入院时MDW>25.4的临界值与COVID-19患者不良疾病结局密切相关。MDW可被视为预测COVID-19疾病严重程度和患者结局的有用参数。其在COVID-19患者标准诊断算法和管理中的作用及纳入需要进一步验证。
在线版本包含可在10.1007/s12288-023-01665-y获取的补充材料。