Selected article for: "developed prediction model and prediction model"

Author: 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
Title: Developing a multivariable risk prediction model to predict prolonged viral clearance in patients with COVID-19
  • Cord-id: g64i23zw
  • Document date: 2020_12_31
  • ID: g64i23zw
    Snippet: • In this study, a multivariable risk prediction model was developed that may help predict a patient's risk of prolonged SARS-CoV-2 RNA clearance. • Time from illness onset to admission, haemoptysis, diarrhea, use of glucocorticoids, leukopenia and elevated alanine transaminase were independent risk factors for prolonged duration of viral clearance; • Estimating these risk factors could promote individual precision therapy and optimizing the use of medical resources.
    Document: • In this study, a multivariable risk prediction model was developed that may help predict a patient's risk of prolonged SARS-CoV-2 RNA clearance. • Time from illness onset to admission, haemoptysis, diarrhea, use of glucocorticoids, leukopenia and elevated alanine transaminase were independent risk factors for prolonged duration of viral clearance; • Estimating these risk factors could promote individual precision therapy and optimizing the use of medical resources.

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