Volume 8, Issue 4 (Winter 2023)                   J Health Res Commun 2023, 8(4): 51-59 | Back to browse issues page

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Heidari A, Kabir M J, Khatirnamani Z, Hosseinpour R. Modeling of Hospitalization Time to Recovery of Patients with COVID-19 in Hospitals of Golestan University of Medical Sciences. J Health Res Commun 2023; 8 (4) :51-59
URL: http://jhc.mazums.ac.ir/article-1-792-en.html
MSc Bios tatis tics, Health Management and Social Development Research Center, Golestan University of Medical Sciences, Gorgan, Iran
Abstract:   (726 Views)
Introduction and purpose: The assessment of the length of hospital s tay until recovery of patients with Covid-19 and its related factors in different areas can help manage the treatment process and prepare for the epidemic. This s tudy aimed to model the survival time until the recovery of COVID-19 definite patients.
Methods: This descriptive-analytical s tudy was retrospective. The s tatis tical population included all COVID-19 definite hospitalized in the educational and medical hospitals of Goles tan University of Medical Sciences from 20 February to 20 July 2020. The outcome variable was discharging confirmed cases of Covid-19. All analytical tes ts and charting were performed in R3.6.2 software.
Results: From a total of 3480 confirmed patients, 77.5% recovered, and 22.5% experienced death at the end of the s tudy or were undergoing treatment. The median length of hospitalization in patients was 6 (IQR: 3-10) days. The mean age of all patients was 52.93±19.20 years; 58.2% of patients were over 49 years old, and half of the population were male. Women infected with Covid-19 survived and recovered 1.16 times more than men. Patients with an age group above 49 years of age had more recovery than their counterparts aged under 49 years.
Conclusion: As evidenced by the obtained results, apart from older adults, the prevalence of the disease needs to be evaluated more closely in young people and men, and these people should be monitored and screened frequently.

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Type of Study: Research(Original) | Subject: Biostatistics

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