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. 2021 Jun 10;16(6):e0252389.
doi: 10.1371/journal.pone.0252389. eCollection 2021.

Time to recovery from COVID-19 and its predictors among patients admitted to treatment center of Wollega University Referral Hospital (WURH), Western Ethiopia: Survival analysis of retrospective cohort study

Tadesse Tolossa  1 , Bizuneh Wakuma  2 , Dejene Seyoum Gebre  1 , Emiru Merdassa Atomssa  1 , Motuma Getachew  1 , Getahun Fetensa  2 , Diriba Ayala  3 , Ebisa Turi  1
Affiliations

Time to recovery from COVID-19 and its predictors among patients admitted to treatment center of Wollega University Referral Hospital (WURH), Western Ethiopia: Survival analysis of retrospective cohort study

Tadesse Tolossa et al. PLoS One. .

Abstract

Introduction: Despite its alarming spread throughout the world, no effective drug and vaccine is discovered for COVID-19 so far. According to WHO, the recovery time from COVID-19 was estimated to be 2 weeks for patients with mild infection, and 3 to 6 weeks for those with serious illnesses. A studies regarding the median recovery time and its predictors are limited globally and specifically in Ethiopia. Therefore, the aim of this study was to estimate the median time to recovery from COVID-19 and its predictors among COVID-19 cases admitted to WURH, Western Ethiopian.

Methods: This was a hospital-based retrospective cohort study conducted among 263 adult patients admitted with COVID-19 in WURH treatment center from March 29, 2020 through September 30, 2020. Epidata version 3.2 was used for data entry, and STATA version 14 for analysis. A Cox proportional hazard regression model was fitted to determine factors associated with recovery time. A variable with P-value ≤ 0.25 at bivariable Cox regression analysis were selected for multivariable Cox proportional model. Multivariable Cox regression model with 95% CI and Adjusted Hazard Ratio (AHR) was used to identify a significant predictor of time to recovery from COVID-19 at P-value < 0.05.

Results: The mean age of patient was 36.8 (SD± 10.68) years. At the end of follow up, two hundred twenty seven observations were developed an event (recovered) with median time to recovery of 18 days with IQR of 10-27 days. The overall incidence rate of recovery was of 4.38 per 100 (95% CI: 3.84, 4.99) person-days observations. Being older age (AHR = 1.59, 95% CI: 1.02, 2.49), presence of fever on admission (AHR = 1.78, 95% CI: 1.21, 2.62), and comorbidity (AHR = 0.56, 95% CI, 0.34, 0.90) were found to have statistically significant association with recovery time.

Conclusion and recommendations: In general, the median recovery time of patients with COVID-19 cases was long, and factors such as older age group, presence of fever, and comorbidity was an independent predictors of delayed recovery from COVID-19. Intervention to further reduce recovery time at treatment center has to focus on patients those shows symptoms and with comorbidities.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Treatment outcome among patients admitted with COVID-19 in WURH treatment.
Fig 2
Fig 2. Overall Kaplan-Meier survival probability curve.
Fig 3
Fig 3
(a) Kaplan survival curve for residence and sex. (b) Kaplan survival curve for the presence fever and comorbidity.
Fig 4
Fig 4. Cox Snell residual test for overall adequacy of the model.
See this image and copyright information in PMC

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References

    1. Yin Y. and Wunderink R.G., MERS, SARS and other coronaviruses as causes of pneumonia. Respirology, 2018. 23(2): p. 130–137. doi: 10.1111/resp.13196 - DOI - PMC - PubMed
    1. Huang C., et al.., Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The lancet, 2020. 395(10223): p. 497–506. - PMC - PubMed
    1. Pamuk S., Özkan A., and Polat B., Epidemiology, pathogenesis, diagnosis and management of COVID-19. The Turkish Journal of Ear Nose and Throat, 2020. 30(Supp: 1): p. 1–9.
    1. Jin Y.-H., et al.., A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version). Military Medical Research, 2020. 7(1): p. 1–23. doi: 10.1186/s40779-019-0229-2 - DOI - PMC - PubMed
    1. Organization, W.H., World Health Organization coronavirus disease (COVID-19) dashboard. 2020.