Lu Yanfei, Xia Wenying, Miao Shuxian, Wang Min, Wu Lei, Xu Ting, Wang Fang, Xu Jian, Mu Yuan, Zhang Bingfeng, Pan Shiyang
Department of Laboratory Medicine, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, People's Republic of China.
National Key Clinical Department of Laboratory Medicine, Nanjing, People's Republic of China.
Infect Drug Resist. 2023 Oct 18;16:6735-6745. doi: 10.2147/IDR.S430101. eCollection 2023.
This study aimed to investigate the clinical characteristics and risk factors of death in severe coronavirus disease 2019 (COVID-19) during the epidemic of Omicron variants, assess the clinical value of plasma cell-free DNA (cfDNA), and construct a prediction nomogram for patient mortality.
The study included 282 patients with severe COVID-19 from December 2022 to January 2023. Patients were divided into survival and death groups based on 60-day prognosis. We compared the clinical characteristics, traditional laboratory indicators, and cfDNA concentrations at admission of the two groups. Univariate and multivariate logistic analyses were performed to identify independent risk factors for death in patients with severe COVID-19. A prediction nomogram for patient mortality was constructed using R software, and an internal validation was performed.
The median age of the patients included was 80.0 (71.0, 86.0) years, and 67.7% (191/282) were male. The mortality rate was 55.7% (157/282). Age, tracheal intubation, shock, cfDNA, and urea nitrogen (BUN) were the independent risk factors for death in patients with severe COVID-19, and the area under the curve (AUC) for cfDNA in predicting patient mortality was 0.805 (95% confidence interval [CI]: 0.713-0.898, sensitivity 81.4%, specificity 75.6%, and cut-off value 97.67 ng/mL). These factors were used to construct a prediction nomogram for patient mortality (AUC = 0.856, 95% CI: 0.814-0.899, sensitivity 78.3%, and specificity 78.4%), C-index was 0.856 (95% CI: 0.832-0.918), mean absolute error of the calibration curve was 0.007 between actual and predicted probabilities, and Hosmer-Lemeshow test showed no statistical difference (χ2=6.085, =0.638).
There was a high mortality rate among patients with severe COVID-19. cfDNA levels ≥97.67 ng/mg can significantly increase mortality. When predicting mortality in patients with severe COVID-19, a nomogram based on age, tracheal intubation, shock, cfDNA, and BUN showed high accuracy and consistency.
本研究旨在调查奥密克戎变异株流行期间重症新型冠状病毒肺炎（COVID-19）的临床特征及死亡危险因素，评估血浆游离DNA（cfDNA）的临床价值，并构建患者死亡预测列线图。
本研究纳入了2022年12月至2023年1月期间的282例重症COVID-19患者。根据60天预后将患者分为生存组和死亡组。比较两组患者入院时的临床特征、传统实验室指标及cfDNA浓度。进行单因素和多因素logistic分析以确定重症COVID-19患者死亡的独立危险因素。使用R软件构建患者死亡预测列线图并进行内部验证。
纳入患者的中位年龄为80.0（71.0，86.0）岁，男性占67.7%（191/282）。死亡率为55.7%（157/282）。年龄、气管插管、休克、cfDNA及尿素氮（BUN）是重症COVID-19患者死亡的独立危险因素，cfDNA预测患者死亡的曲线下面积（AUC）为0.805（95%置信区间[CI]：0.713 - 0.898，灵敏度81.4%，特异度75.6%，截断值97.67 ng/mL）。利用这些因素构建了患者死亡预测列线图（AUC = 0.856，95% CI：0.814 - 0.899，灵敏度78.3%，特异度78.4%），C指数为0.856（95% CI：0.832 - 0.918），校准曲线实际概率与预测概率之间的平均绝对误差为0.007，Hosmer-Lemeshow检验无统计学差异（χ2 = 6.085，P = 0.638）。
重症COVID-19患者死亡率较高。cfDNA水平≥97.67 ng/mg可显著增加死亡率。在预测重症COVID-19患者死亡率时，基于年龄、气管插管、休克、cfDNA及BUN的列线图显示出较高的准确性和一致性。
