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

• Published in: Epidemiology and infection Vol. 151; p. e34
• Main Authors: Hu, Cheng-Yi, Lei, Yi, Tang, Yu-Wen, Cui, Wen-Shuai, Wu, Pei-Lian, Li, Yan-Fang, Zhou, Yan, Li, Xin-Yan, Cui, Hao, Xiao, Lu-Shan, Zhao, Zhu-Xiang
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 17.02.2023
• Subjects: Antibodies; Chi-square test; Comorbidity; Coronaviruses; COVID-19; COVID-19 Testing; COVID-19 Vaccines; Epidemiology; Humans; Immunoglobulin G; Immunoglobulin M; Immunoglobulins; Infections; Laboratories; Laboratory tests; Leukocytes; Mathematical models; mRNA; Original Paper; Patients; Polymerase Chain Reaction; Prediction models; Quarantine; Regression analysis; Rehabilitation; Renal function; Risk factors; SARS-CoV-2; Severe acute respiratory syndrome coronavirus 2; Signs and symptoms; Vaccines; Variables; Viral diseases; COVID-19; Clinical characteristics; SARS-CoV-2 infection; repeat test positivity; predictive model
• ISSN: 0950-2688; 1469-4409
• DOI: 10.1017/S0950268823000249

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 (n = 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.