Developing a multivariable risk prediction model to predict prolonged viral clearance in patients with COVID-19. Issue 4 (April 2021)

• Record Type: Journal Article
• Authors: Liu, Ying; Li, Min; Liu, Dan; Luo, Jian Fei; Li, Nian; Zhang, Xuan; Tang, Xiao Ju; Zhang, Xin; Liu, Jia; Wang, Ji; Wang, Ting; Zhou, Yong Zao; Luo, Wen Xin; Liang, Zong An; Luo, Feng Ming; Li, Wei Min; Wang, Gang
• Is Part Of: Journal of infection. Volume 82:Issue 4(2021)
• Page Start: e20
• Page End: e22
• Publication Date: 2021-04
• Subjects: COVID-19 -- SARS-CoV-2 -- Viral clearance -- Prediction model; Infection -- Periodicals; Bacterial Infections -- Periodicals; Communicable Diseases -- Periodicals; Electronic journals; 616.905
• DOI: 10.1016/j.jinf.2020.12.026
• Languages: English
• ISSNs: 0163-4453

Abstract

Highlights: A multivariable risk prediction model was developed to predict a patient's risk of prolonged SARS-CoV-2 RNA clearance. Six independent risk factors for prolonged duration of viral clearance were found. Estimating these risk factors could promote individual precision therapy and optimizing the use of medical resources.