Department of Pediatrics, the First Hospital of Jilin University, China.
Department of Gastrointestinal, the First Hospital of Jilin University, China.
Jpn J Infect Dis. 2021 Jul 21;74(4):359-366. doi: 10.7883/yoken.JJID.2020.718. Epub 2020 Oct 30.
This study aimed to develop and validate a bedside risk analysis system for predicting the clinical severity and prognosis of patients with coronavirus disease 2019 (COVID-19). In total, 444 COVID-19 patients were included and randomly assigned in a 2:1 ratio to 2 groups: derivation group and validation group. The new scoring system comprised of the following 8 variables: history of malignant diseases, history of diabetes mellitus, dyspnea, respiratory rate >24 breaths/min, C-reactive protein level >14 mg/L, white blood cell count >8×10/L, platelets count <180 × 10/L, and lymphocyte count <1 × 10/L. The sensitivity analysis revealed that this new scoring system was more efficient than the sequential organ failure assessment scoring system on the first day of admission. The receiver characteristic curve analysis revealed that the new risk scoring predicted the severe cases of COVID-19 infection with an area under the curve of 0.831 (95% confidence interval [CI]: 0.783-0.879) and 0.798 (95% CI: 0.727-0.869) in the derivation and validation groups, respectively. This proposed risk score system is a fairly reliable and robust tool for evaluating the severity and prognosis of patients with COVID-19. This may help in the early identification of severe COVID-19 patients with poor prognosis, requiring more intense interventions.
本研究旨在开发和验证一种床边风险分析系统，以预测 2019 冠状病毒病（COVID-19）患者的临床严重程度和预后。共纳入 444 例 COVID-19 患者，按 2:1 的比例随机分为两组：推导组和验证组。新的评分系统由以下 8 个变量组成：恶性肿瘤病史、糖尿病史、呼吸困难、呼吸频率>24 次/分钟、C 反应蛋白水平>14mg/L、白细胞计数>8×10/L、血小板计数<180×10/L 和淋巴细胞计数<1×10/L。敏感性分析显示，该新评分系统在入院第 1 天比序贯器官衰竭评估评分系统更有效。受试者工作特征曲线分析显示，新的风险评分预测 COVID-19 感染严重程度的曲线下面积分别为 0.831（95%置信区间[CI]：0.783-0.879）和 0.798（95% CI：0.727-0.869）。该风险评分系统是一种相当可靠和稳健的评估 COVID-19 患者严重程度和预后的工具。这有助于早期识别预后不良的重症 COVID-19 患者，需要更加强烈的干预措施。
