Survival Evaluation of Hospitalized COVID-19 Patients with Cox Frailty Approach

Introduction:The survival cox analysis is becoming more popular in time-to-event data analysis. When there are unobserved /unmeasured individual factors, then the results of this model may not be dependable. Hence, this study aimed to determine the factors associated with Covid-19 patients' survival time with considering frailty factor. Methods:This study was conducted at 1 of the hospitals in Iran, so that hospitalized patients with COVID-19 were included. Epidemiological, clinical, laboratory, and outcome data on admission were extracted from electronic medical records. Gamma-frailty Cox model was used to identify the effects of the risk factors. Results:A total of 360 patients with COVID-19 enrolled in the study. The median age was 74 years (IQR 61 - 83), 903 (57 center dot 7%) were men, and 661 (42 center dot 3%) were women; the mortality rate was 17%. The Cox frailty model showed that there is at least a latent factor in the model (P = 0.005). Age and platelet count were negatively associated with the length of stay, while red blood cell count was positively associated with the length of stay of patients. Conclusion:The Cox frailty model indicates that in addition to age, the frailty factor is a useful predictor of survival in Covid-19 patients.