Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Department of Clinical Laboratory, Wenzhou Central Hospital, Wenzhou 325099, China.
J Zhejiang Univ Sci B. 2021 Apr 15;22(4):318-329. doi: 10.1631/jzus.B2000608.
With the number of cases of coronavirus disease-2019 (COVID-19) increasing rapidly, the World Health Organization (WHO) has recommended that patients with mild or moderate symptoms could be released from quarantine without nucleic acid retesting, and self-isolate in the community. This may pose a potential virus transmission risk. We aimed to develop a nomogram to predict the duration of viral shedding for individual COVID-19 patients. This retrospective multicentric study enrolled 135 patients as a training cohort and 102 patients as a validation cohort. Significant factors associated with the duration of viral shedding were identified by multivariate Cox modeling in the training cohort and combined to develop a nomogram to predict the probability of viral shedding at 9, 13, 17, and 21 d after admission. The nomogram was validated in the validation cohort and evaluated by concordance index (C-index), area under the curve (AUC), and calibration curve. A higher absolute lymphocyte count (=0.001) and lymphocyte-to-monocyte ratio (=0.013) were correlated with a shorter duration of viral shedding, while a longer activated partial thromboplastin time (=0.007) prolonged the viral shedding duration. The C-indices of the nomogram were 0.732 (95% confidence interval (CI): 0.685‒0.777) in the training cohort and 0.703 (95% CI: 0.642‒0.764) in the validation cohort. The AUC showed a good discriminative ability (training cohort: 0.879, 0.762, 0.738, and 0.715 for 9, 13, 17, and 21 d; validation cohort: 0.855, 0.758, 0.728, and 0.706 for 9, 13, 17, and 21 d), and calibration curves were consistent between outcomes and predictions in both cohorts. A predictive nomogram for viral shedding duration based on three easily accessible factors was developed to help estimate appropriate self-isolation time for patients with mild or moderate symptoms, and to control virus transmission.
随着 2019 年冠状病毒病(COVID-19)病例数量的迅速增加,世界卫生组织(WHO)建议轻症或中度症状的患者可以在无需核酸复测的情况下解除隔离,并在社区中进行自我隔离。这可能会带来潜在的病毒传播风险。我们旨在开发一个列线图来预测 COVID-19 患者个体的病毒脱落持续时间。这项回顾性多中心研究纳入了 135 例患者作为训练队列和 102 例患者作为验证队列。通过多变量 Cox 建模在训练队列中确定与病毒脱落持续时间相关的显著因素,并将其结合起来开发一个列线图,以预测入院后 9、13、17 和 21 d 的病毒脱落概率。该列线图在验证队列中进行了验证,并通过一致性指数(C 指数)、曲线下面积(AUC)和校准曲线进行了评估。较高的绝对淋巴细胞计数(=0.001)和淋巴细胞与单核细胞比值(=0.013)与病毒脱落持续时间较短相关,而较长的活化部分凝血活酶时间(=0.007)则延长了病毒脱落持续时间。列线图的 C 指数在训练队列中为 0.732(95%置信区间[CI]:0.685-0.777),在验证队列中为 0.703(95%CI:0.642-0.764)。AUC 显示出良好的判别能力(训练队列:9、13、17 和 21 d 时分别为 0.879、0.762、0.738 和 0.715;验证队列:9、13、17 和 21 d 时分别为 0.855、0.758、0.728 和 0.706),且校准曲线在两个队列中的结果与预测之间均一致。基于三个易于获取的因素开发了病毒脱落持续时间的预测列线图,以帮助估计轻症或中度症状患者的适当自我隔离时间,并控制病毒传播。