Satici Celal, Demirkol Mustafa Asim, Sargin Altunok Elif, Gursoy Bengul, Alkan Mustafa, Kamat Sadettin, Demirok Berna, Surmeli Cemile Dilsah, Calik Mustafa, Cavus Zuhal, Esatoglu Sinem Nihal
Department of Chest Diseases, Gaziosmanpasa Research and Training Hospital, University of Health Sciences, Istanbul, 34255, Turkey.
Department of Infectious Disease and Clinical Microbiology, Gaziosmanpasa Research and Training Hospital, University of Health Sciences, Istanbul, Turkey.
Int J Infect Dis. 2020 Sep;98:84-89. doi: 10.1016/j.ijid.2020.06.038. Epub 2020 Jun 14.
The aim of the study was to analyze the usefulness of CURB-65 and the pneumonia severity index (PSI) in predicting 30-day mortality in patients with COVID-19, and to identify other factors associated with higher mortality.
A retrospective study was performed in a pandemic hospital in Istanbul, Turkey, which included 681 laboratory-confirmed patients with COVID-19. Data on characteristics, vital signs, and laboratory parameters were recorded from electronic medical records. Receiver operating characteristic analysis was used to quantify the discriminatory abilities of the prognostic scales. Univariate and multivariate logistic regression analyses were performed to identify other predictors of mortality.
Higher CRP levels were associated with an increased risk for mortality (OR: 1.015, 95% CI: 1.008-1.021; p < 0.001). The PSI performed significantly better than CURB-65 (AUC: 0.91, 95% CI: 0.88-0.93 vs AUC: 0.88, 95% CI: 0.85-0.90; p = 0.01), and the addition of CRP levels to PSI did not improve the performance of PSI in predicting mortality (AUC: 0.91, 95% CI: 0.88-0.93 vs AUC: 0.92, 95% CI: 0.89-0.94; p = 0.29).
In a large group of hospitalized patients with COVID-19, we found that PSI performed better than CURB-65 in predicting mortality. Adding CRP levels to PSI did not improve the 30-day mortality prediction.
本研究旨在分析CURB-65和肺炎严重程度指数(PSI)在预测2019冠状病毒病(COVID-19)患者30天死亡率方面的效用,并确定其他与较高死亡率相关的因素。
在土耳其伊斯坦布尔的一家大流行医院进行了一项回顾性研究,纳入了681例实验室确诊的COVID-19患者。从电子病历中记录患者特征、生命体征和实验室参数的数据。采用受试者工作特征分析来量化预后量表的鉴别能力。进行单因素和多因素逻辑回归分析以确定其他死亡率预测因素。
较高的C反应蛋白(CRP)水平与死亡风险增加相关(比值比:1.015,95%置信区间:1.008 - 1.021;p < 0.001)。PSI的表现显著优于CURB-65(曲线下面积:0.91,95%置信区间:0.88 - 0.93,对比曲线下面积:0.88,95%置信区间:0.85 - 0.90;p = 0.01),并且将CRP水平添加到PSI中并不能改善PSI在预测死亡率方面的表现(曲线下面积:0.91,95%置信区间:0.88 - 0.93,对比曲线下面积:0.92,95%置信区间:0.89 - 0.94;p = 0.29)。
在一大组住院的COVID-19患者中,我们发现PSI在预测死亡率方面比CURB-65表现更好。将CRP水平添加到PSI中并不能改善30天死亡率预测。