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Urinary SARS-CoV-2 RNA is An Indicator For The Progression and Prognosis of COVID-19 Disease.


ABSTRACT: Background: We aimed to analyse clinical characteristics and find potential factors predicting poor prognosis in patients with coronavirus disease 2019 (COVID-19). Methods: We analyzed the demographic and clinical data of COVID-19 patients and detected SARS-CoV-2 RNA in urine sediments collected from 53 COVID-19 patients enrolled in Renmin Hospital of Wuhan University from January 31, 2020 to February 18, 2020 with qRT-PCR analysis, and then classified those patients based on clinical conditions (severe or non-severe syndrome) and urinary SARS-CoV-2 RNA (U RNA- or U RNA+ ). Results: We found that COVID-19 patients with severe syndrome (severe patients) showed significantly higher positive rate (11 of 23, 47.8%) of urinary SARS-CoV-2 RNA than non-severe patients (4 of 30, 13.3%, p = 0.006). U RNA+ patients or severe U RNA+ subgroup exhibited higher prevalence of inflammation and immune discord, cardiovascular diseases, liver damage and renal disfunction, and higher risk of death than U RNA- patients. To understand the potential mechanisms underlying the viral urine shedding, we performed renal histopathological analysis on postmortems of patients with COVID-19 and found that severe renal vascular endothelium lesion characterized by increase of the expression of thrombomodulin and von Willebrand factor, markers to assess the endothelium dysfunction. We proposed a theoretical and mathematic model to depict the potential factors determining the urine shedding of SARS-CoV-2. Conclusions: This study indicated that urinary SARS-CoV-2 RNA detected in urine specimens can be used to predict the progression and prognosis of COVID-19 severity.

SUBMITTER: Tian M 

PROVIDER: S-EPMC7899468 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Urinary SARS-CoV-2 RNA is An Indicator For The Progression and Prognosis of COVID-19 Disease.

Tian Maoqing M   Zhang Lu L   Zhu Kai K   Shen Bo B   Wang Gang G   Song Yuan Y   Chen Cheng C   Liang Wei W   Guan Yang Y   Ding Guohua G   Lei Tiechi T   Li Xiaogang X   Xie Jingyuan J   Tong Yongqing Y   Wang Huiming H  

Research square 20210218


<b><i>Background:</i></b> We aimed to analyse clinical characteristics and find potential factors predicting poor prognosis in patients with coronavirus disease 2019 (COVID-19). <b><i>Methods:</i></b> We analyzed the demographic and clinical data of COVID-19 patients and detected SARS-CoV-2 RNA in urine sediments collected from 53 COVID-19 patients enrolled in Renmin Hospital of Wuhan University from January 31, 2020 to February 18, 2020 with qRT-PCR analysis, and then classified those patients  ...[more]

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