Médecine interne: libre accès
Libre accès

Abstrait

Survival Analysis of COVID-19 Patients using Cox Frailty Model

Elena Battino*

Background: The coronavirus disease 2019 (COVID-19) has been a pandemic and has affected mortality worldwide. The Cox Proportional Hazard (CPH) model is becoming more popular in time to event data analysis. When there are unobserved/unmeasured individual's factors, then the results of the CPH may not be reliable. So, this study aimed to determine the association between frailty and survival time in hospitalized COVID-19 patients.

Methods: This was a Single-center observational study conducted at one of the hospitals in Iran. So that, hospitalized patients with confirmed COVID-19 were included. Epidemiological, clinical, laboratory and outcome data on admission were extracted from electronic medical records. After selecting the most important prognostic risk factors on survival, CPH and gamma-frailty Cox models were used to identify the unadjusted and adjusted effects of the risk factors.

Results: 360 patients with COVID-19 enrolled in the study. The median age was 74 years were men and 42·3% were women, the mortality rate was 17% The results of the CPH model showed that, hypertension, sex, age and smoking status increase the mortality hazard of death due to the covid-19 (P<0.05). Furthermore, the 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.

Conclusions: Both the frailty and CPH model indicate that in addition to age, the frailty factor is a useful predictor of survival in patients with COVID-19 and disease outcomes were better predicted by considering frailty than either age or comorbidity.