Endemic Medicine Department, Faculty of Medicine, Helwan University, Cairo, Egypt.
Community, Environmental and Occupational Medicine Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
J Infect Dev Ctries. 2022 Jul 28;16(7):1138-1147. doi: 10.3855/jidc.15984.
COVID-19 severity and mortality predictors could determine admission criteria and reduce mortality. We aimed to evaluate the clinical-laboratory features of hospitalized patients with COVID-19 to develop a novel score of severity and mortality.
This retrospective cohort study was conducted using data from patients with COVID-19 who were admitted to five Egyptian university hospitals. Demographics, comorbidities, clinical manifestations, laboratory parameters, the duration of hospitalization, and disease outcome were analyzed, and a score to predict severity and mortality was developed.
A total of 1308 patients with COVID-19, with 996 (76.1%) being moderate and 312 (23.9%) being severe cases, were included. The mean age was 46.5 ± 17.1 years, and 61.6% were males. The overall mortality was 12.6%. Regression analysis determined significant predictors, and a ROC curve defined cut-off values. The COVEG severity score was defined by age ≥ 54, D-dimer ≥ 0.795, serum ferritin ≥ 406, C-reactive protein ≥ 30.1, and neutrophil: lymphocyte ratio ≥ 2.88. The COVEG mortality score was based on COVEG severity and the presence of cardiac diseases. Both COVEG scores had high predictive values (area under the curve 0.882 and 0.883, respectively).
COVEG score predicts the severity and mortality of patients with COVID-19 accurately.
COVID-19 严重程度和死亡率预测因子可以确定入院标准并降低死亡率。我们旨在评估住院 COVID-19 患者的临床-实验室特征,以制定新的严重程度和死亡率评分。
本回顾性队列研究使用了来自埃及五所大学医院住院的 COVID-19 患者的数据。分析了人口统计学、合并症、临床表现、实验室参数、住院时间和疾病结局,并制定了预测严重程度和死亡率的评分。
共纳入 1308 例 COVID-19 患者,其中 996 例(76.1%)为中度病例,312 例(23.9%)为重度病例。平均年龄为 46.5 ± 17.1 岁,61.6%为男性。总死亡率为 12.6%。回归分析确定了显著的预测因子,ROC 曲线定义了截断值。COVEG 严重程度评分由年龄≥54 岁、D-二聚体≥0.795、血清铁蛋白≥406、C 反应蛋白≥30.1 和中性粒细胞:淋巴细胞比值≥2.88 定义。COVEG 死亡率评分基于 COVEG 严重程度和心脏疾病的存在。这两个 COVEG 评分都具有很高的预测值(曲线下面积分别为 0.882 和 0.883)。
COVEG 评分可准确预测 COVID-19 患者的严重程度和死亡率。