Mohammadreza Mirjalili; Mohammadreza Dehghani; Mehdi Raadabadi; Farzan Madadizadeh; Mohammad Sharifyazdi; Hosein Shojaefar; Masoud Sharifi; Mehdi Yavari; Ali Dehghani
Abstract
Background: Considering the high prevalence of COVID-19 in Iran, it is necessary to allocate health resources in response to this pandemic. Due to limitations in the number of hospital beds, analysis of the length of hospital stay in COVID-19 patients may be helpful for decision-making.Methods: This ...
Read More
Background: Considering the high prevalence of COVID-19 in Iran, it is necessary to allocate health resources in response to this pandemic. Due to limitations in the number of hospital beds, analysis of the length of hospital stay in COVID-19 patients may be helpful for decision-making.Methods: This retrospective cohort study (survival study) was conducted through a follow-up of 1465 COVID-19 patients in Yazd Province, Iran. Demographic, diagnostic, and clinical data were collected using the COVID-19 data dashboard of Shahid Sadoughi University of Medical Sciences. The Kaplan-Meier method and Cox regression were used to calculate the survival probability and hazard ratio; the log-rank test was applied to compare survival function according to qualitative variables.Results: The median and mean survival time was 25 days (95% CI: 19.10-30.89 days) and 28.38 days (95% CI: 25.6-31.16 days), respectively. The Survival probability for one week, two weeks, three weeks, four weeks, five weeks, six weeks, and seven weeks and more was 92%, 76%, 57%, 48%, 45%, 33%, and 20%, respectively. There was a significant relationship between survival time and age categories, CT scan results, history of chronic pulmonary disease, history of diabetes, history of cardiovascular disease, and disease severity (P<0.05).Conclusion: According to the results, age, history of cardiovascular and pulmonary diseases, and history of diabetes increased the length of hospital stay. Preventive measures should be followed to prevent COVID-19 infection and manage hospital beds required for efficient treatment of patients.
