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 (P=0.001) and lymphocyte-to-monocyte ratio (P=0.013) were correlated with a shorter duration of viral shedding, while a longer activated partial thromboplastin time (P=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
目的
探索与新型冠状病毒核酸转阴时长相关的因素, 并建立一个模型来预测病毒核酸转阴的概率。
创新点
本研究根据影响非重症新型冠状病毒肺炎 (COVID-19) 患者病毒核酸转阴时长的因素建立一个模型来预测病毒核酸转阴的概率, 从而估计非重症COVID-19患者的隔离时长。
方法
本研究采用多中心回顾性研究方法, 选取浙江省四所医院的135例患者作为训练队列和另一家医院的102名患者作为验证队列。在训练队列中, 使用多因素Cox回归模型确定与病毒核酸转阴时长相关的重要预测因素, 并以此为基础构建一个列线图来预测病毒在第9、13、17和21天转阴的概率。验证队列用于验证列线图, 并通过C指数、曲线下面积 (AUC) 和校准曲线来评估列线图的效能。
结论
训练队列中发现, 基线淋巴细胞绝对计数和淋巴单核细胞比值越高, 病毒的核酸转阴时长越短; 而基线的活化部分凝血酶时间越长, 病毒的核酸转阴时长越长。列线图在训练和验证队列中的C指数分别为0.732和0.703。AUC表现出较好的区分度。校准曲线展示了实际结果和预测之间具有较好的一致性。本研究确定了与病毒核酸转阴时长相关的三个因素, 并构建一个列线图来预测病毒核酸转阴的概率, 这有助于估计每个非重症COVID-19患者的隔离时长, 并控制病毒传播。
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Acknowledgments
This research was supported by the Medical and Health Science and Technology Project of Zhejiang Province, China (No. 2018KY116). We would like to acknowledge Dr. Yuzhen GAO and Dr. Yanzhong WANG (Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China) for their writing assistance and proofreading the article.
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Jun ZHANG and Xinyou XIE designed the study and reviewed the manuscript prior to submission. Shijin YUAN coordinated the work and took the lead in drafting the manuscript and interpreting. Yong PAN and Yan XIA developed the statistical methods. Yong PAN, Jiangnan CHEN, Yan ZHANG, Wei ZHENG, and Xiaoping XU participated in the collection of experimental data. The corresponding author attests that all listed authors met authorship criteria and that no others meeting the criteria have been omitted. All authors have read and approved the final manuscript and, therefore, have full access to all the data in the study and take responsibility for the integrity and security of the data.
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Shijin YUAN, Yong PAN, Yan XIA, Yan ZHANG, Jiangnan CHEN, Wei ZHENG, Xiaoping XU, Xinyou XIE, and Jun ZHANG declare that they have no conflict of interest.
This study was approved by the Institutional Ethics Committee of Sir Run Run Shaw Hospital, Hangzhou, China (No. Scientific Research 20200331-45). All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). Informed consent was waived due to retrospective nature of the study.
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Yuan, S., Pan, Y., Xia, Y. et al. 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. J. Zhejiang Univ. Sci. B 22, 318–329 (2021). https://doi.org/10.1631/jzus.B2000608
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DOI: https://doi.org/10.1631/jzus.B2000608
Key words
- Coronavirus disease-2019 (COVID-19)
- Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
- Duration of viral shedding
- Nomogram