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开发和验证一种个体化列线图,用于预测非重症 COVID-19 患者 SARS-CoV-2 脱落持续时间。

Development and validation of an individualized nomogram for early prediction of the duration of SARS-CoV-2 shedding in COVID-19 patients with non-severe disease.

机构信息

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.

出版信息

J Zhejiang Univ Sci B. 2021 Apr 15;22(4):318-329. doi: 10.1631/jzus.B2000608.

Abstract

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.

摘要

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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2013/8042531/fa87d015d196/JZhejiangUnivSciB-22-4-318-g001.jpg

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