https://orcid.org/0000-0002-8178-6484
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Abstract
Background
Comorbidities and advanced age increase the risk of severe outcomes of COVID-19. In order to shift the possible unfavorable treatment outcome in patients with chronic illnesses, information related to the prevalence of chronic illness and its effect on severity of COVID-19 infection has paramount importance.
Objective
This study was aimed at assessing the prevalence of comorbidities and associated severity among COVID-19 patients admitted to COVID-19 treatment center, eastern Ethiopia.
Methods
An institution-based cross-sectional study design was employed among 422 COVID-19 patients admitted to COVID-19 treatment center, eastern Ethiopia from April 10, 2020, to August 10, 2021. Binary logistic regression was fitted to identify comorbidities and other factors associated with severe clinical outcome, associations were presented with adjusted odds ratios (AORs) and 95% confidence intervals (CIs). In all analyses statistical significance were declared at p-value <0.05.
Results
More than half (52.4%) of the COVID-19 patients were presented with comorbid conditions. One third (34.6%) of the admitted COVID-19 patients were in severe clinical stages. Marital status (AOR=4.56; 95% CI: 1.40, 14.76), hypertension (AOR=2.08; 95% CI: 1.09, 3.97), diabetes mellitus (AOR=3.31; 95%:1.84, 5.98), and cardiovascular diseases (AOR=4.22; 95% CI: 2.18, 8.15) were identified as factors associated with severe clinical stages.
Conclusion
The comorbid conditions such as diabetes, hypertension, and cardiovascular diseases, and marital status were identified as significant predictors of severe outcomes of COVID-19. Therefore, identifying the people with chronic comorbidities as a risk group would help to anticipate and prevent the serious outcomes of COVID-19 infection.
Data Sharing Statement
The datasets used in this study can be available from correspondent author up on reasonable request.
Acknowledgment
The authors are thankful to Hiwot Fana Hospital for an authorization to access the data. The authors are also grateful to data collectors for their genuine effort to bring reliable data and participants for their participation.
Author Contributions
All authors made a significant contribution to the conception, study design, execution, data acquisition, analysis and interpretation. All authors took part in drafting, critically reviewing the article, gave final approval of the version to be published, have agreed on the journal to which the article has been submitted, and agree to be accountable for all aspects of the work.
Disclosure
The authors declare no conflicts of interest in this work.