AUTHOR=Xu Yu , Ye Wei , Song Qiuyue , Shen Linlin , Liu Yu , Guo Yuhang , Liu Gang , Wu Hongmei , Wang Xia , Sun Xiaorong , Bai Li , Luo Chunmei , Liao Tongquan , Chen Hao , Song Caiping , Huang Chunji , Wu Yazhou , Xu Zhi 

TITLE=Using machine learning models to predict the duration of the recovery of COVID-19 patients hospitalized in Fangcang shelter hospital during the Omicron BA. 2.2 pandemic

JOURNAL=Frontiers in Medicine

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.1001801

DOI=10.3389/fmed.2022.1001801

ISSN=2296-858X

ABSTRACT=Factors that may influence the recovery of patients with confirmed SARS-CoV-2 infection hospitalized in the Fangcang shelter were explored. Machine learning models were constructed to predict the duration of recovery during the Omicron BA. 2.2 pandemic.Of the 13,162 patients in the study, the median duration of recovery was 8 days (interquartile range IQR, 6–10 d), 41.31% recovered within 7 days, and 94.83% recovered within 14 days. Univariate analysis showed that the administrative region, age, cough medicine, comorbidities, diabetes, coronary artery disease (CAD), hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were associated with a duration of recovery within 7 days. Age, gender, vaccination dose, cough medicine, comorbidities, diabetes, CAD, hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were related to a duration of recovery within 14 days. In the multivariable analysis, the receipt of two doses of the vaccination versus unvaccinated (OR = 1.118, 95% CI=1.003–1.248; p = 0.045), receipt of three doses of the vaccination versus unvaccinated (OR=1.114, 95% CI=1.004–1.236; p = 0.043), diabetes (OR = 0.383, 95% CI=0.194–0.749; p = 0.005), CAD (OR = 0.107, 95% CI=0.016–0.421; p = 0.005), hypertension (OR=0.371, 95% CI=0.202–0.674; p=0.001), and ratio of N/IC (OR=3.686, 95% CI=2.939–4.629; p<0.001) were significantly and independently associated with a duration of recovery within 7 days. Gender (OR=0.736, 95% CI=0.63–0.861; p<0.001), age (30–70) (OR=0.738, 95% CI=0.594–0.911; p < 0.001), age (>70) (OR=0.38, 95% CI=0292–0.494; p < 0.001), receipt of three doses of the vaccination versus unvaccinated (OR=1.391, 95% CI=1.12–1.719; p=0.0033), cough medicine (OR=1.509, 95% CI=1.075–2.19; p=0.023), and symptoms (OR=1.619, 95% CI=1.306–2.028; p<0.001) were significantly and independently associated with a duration of recovery within 14 days. The SMOTEEN/RF algorithm performed best, with an accuracy of 90.32%, sensitivity of 92.22%, specificity of 88.31%, F1 score of 90.71%, and AUC of 89.75% for the 7-day recovery prediction; and an accuracy of 93.81%, sensitivity of 93.40%, specificity of 93.81%, F1 score of 93.42%, and AUC of 93.53% for the 14-day recovery prediction.