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COVID-19 康复后 SARS-COV-2 PCR 复阳患者的特征。

Characteristics of patients with SARS-COV-2 PCR re-positivity after recovering from COVID-19.

机构信息

Department of Infectious Diseases, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.

Department of Respiratory Disease, Eighth People's Hospital of Guangzhou, Guangzhou Medical University, Guangzhou, China.

出版信息

Epidemiol Infect. 2023 Feb 17;151:e34. doi: 10.1017/S0950268823000249.

Abstract

The purpose of this study was to analyse the clinical characteristics of patients with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) PCR re-positivity after recovering from coronavirus disease 2019 (COVID-19). Patients ( = 1391) from Guangzhou, China, who had recovered from COVID-19 were recruited between 7 September 2021 and 11 March 2022. Data on epidemiology, symptoms, laboratory test results and treatment were analysed. In this study, 42.7% of recovered patients had re-positive result. Most re-positive patients were asymptomatic, did not have severe comorbidities, and were not contagious. The re-positivity rate was 39%, 46%, 11% and 25% in patients who had received inactivated, mRNA, adenovirus vector and recombinant subunit vaccines, respectively. Seven independent risk factors for testing re-positive were identified, and a predictive model was constructed using these variables. The predictors of re-positivity were COVID-19 vaccination status, previous SARs-CoV-12 infection prior to the most recent episode, renal function, SARS-CoV-2 IgG and IgM antibody levels and white blood cell count. The predictive model could benefit the control of the spread of COVID-19.

摘要

本研究旨在分析从 2019 冠状病毒病(COVID-19)康复后严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)PCR 复阳患者的临床特征。2021 年 9 月 7 日至 2022 年 3 月 11 日,从中国广州招募了已从 COVID-19 中康复的患者(n = 1391)。分析了流行病学、症状、实验室检查结果和治疗数据。在这项研究中,42.7%的康复患者出现了复阳结果。大多数复阳患者无症状,没有严重的合并症,且没有传染性。接种过灭活疫苗、mRNA 疫苗、腺病毒载体疫苗和重组亚单位疫苗的患者的复阳率分别为 39%、46%、11%和 25%。确定了检测复阳的 7 个独立危险因素,并使用这些变量构建了预测模型。复阳的预测因素为 COVID-19 疫苗接种状态、最近一次发病前的 SARS-CoV-12 感染史、肾功能、SARS-CoV-2 IgG 和 IgM 抗体水平以及白细胞计数。该预测模型有助于控制 COVID-19 的传播。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed25/10019929/c479129296c0/S0950268823000249_fig1.jpg

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