| Popis: |
COVID-19 is a viral disease that became a pandemic representing a very great challenge worldwide The purpose of this article is to analyze COVID-19 patients' data based on time-to-event analysis and identify the factors that affect the recovery time from COVID-19 The datasets that are used in this study are for cases that are clinically diagnosed and confirmed where the date of onset is recorded in Wuhan and elsewhere in China from Jan 1 to Feb 11, 2020 We used the regression imputation technique to replace the missing dates in the onset-symptoms based on the dates of the report We fitted the Kaplan-Meier estimator and Cox regression model to our data The predictor variables (factors) that we used are age, sex, and onset time to hospitalization The results show that the young age group is better than the old age group in recovering from COVID-19 (the p-value of the log-rank is 0 00012) and at any time 1 9 as many patients in the young age group are having an event (recovery) proportionally to the old age group Also, the results show that there is a non-significant difference between male and female groups in recovering from COVID-19 (the p-value of the log-rank is 0 63) The results also show that the early time to hospitalization group can recover from COVID-19 better than the late time to hospitalization group (the p-value of the log-rank is 0 0052) This study demonstrates the association of recovery time from COVID-19 with age, sex, and time to hospitalization © 2020 ASTES Publishers All rights reserved |
