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.

Automated summary

This study aimed to investigate the survival time of Covid-19 patients, considering frailty factor. The results showed that 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. The study also found that frailty factor is a useful predictor of survival in Covid-19 patients.