Prediction for the Negative Conversion Probability of Nucleic Acid Testing in Patients with Nonsevere COVID-19 Pneumonia: A Model Based on Retrospective Cohort Study

Facai ZhangLong Li


Background: We aimed to screen clinical independent predictive factors for negative conversion of nucleic acid testing and established a predictive nomogram, so as to relieve patients' anxiety and reduce unnecessary repeated nucleic acid testing.Methods: All 70 consecutive patients with nonsevere COVID-19 pneumonia were admitted to the Fangcang shelter hospital in Wuhan from February 12th to March 8th, 2020. We used univariate Kaplan-Meier analysis and univariate and multivariate Cox regression to identify independent predictive factors and refit the predictive model. Area under ROC (AUR), Brier scores and calibration plots were used to assess the performance.Results: diabetes mellitus, gender and lymphocyte were deemed independent predictive factors and were incorporated into a Cox proportional hazards model. The AUR and Brier scores of the predictive model at 14 days were 0.694 [0.472; 0.890] and 0.163 [0.109; 0.219] in the internal validation set, respectively. Similarly, the AUR and Brier scores at 21 days were 0.779 [0.505; 0.957] and 0.105 [0.042; 0.175] in the internal validation set.Conclusions: By using the predictive nomogram, the clinicians could inform patients with nonsevere COVID-19 regarding a certain time to pos...Continue Reading

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