Dano Gutata1, Zewdie Aderaw Alemu2. 1. Assosa General Hospital, Benishangul Gumuz Regional State Health Bureau, Asosa, Ethiopia. 2. College of Health Sciences Public Health Department, Debre Markos University, Debre Markos, Ethiopia.
Abstract
Background: Most people infected with the SARS-CoV-2 virus experienced mild to moderate respiratory illness and recovered without requiring special treatment. However, some became seriously ill with conditions that require medical attention and intensive care unit (ICU) admission. Severity varies among individuals; this may be due to age differences and the presence of underlying disease conditions. Objective: To identify factors associated with disease severity among COVID19 patients treated at Selgalu treatment center from November 1, 2020, to April 30, 2021. Methods: A case-control study was implemented among patients admitted to Selgalu COVID19 treatment center in October 2021. A 210 (70 severe disease and 140 non-severe diseases), cases (disease severity), and controls (non-severe disease). Data entered to Epi data 4.6, exported to SPSS 25. A Chi-square test with a p-value of <0.05 was used as a statistically significant difference between characteristics of disease severity and non-severity of disease. Multivariable binary logistic regression was used to determine variables associated with disease severity based on an adjusted odds ratio with 95% CI and p-value < 0.05. Results: 210 (70 cases and 140 controls) selected charts in this study. Patients age category between 40-59 [AOR: 5.30 (2.27-12.34)], aged 60 or older [AOR: 3.85 (1.39-10.64)], patients with fever [AOR: 3.98 (1.59-9.96)], fatigue [AOR: 3.14 (1.50-6.54)], and hypertensive patients [AOR: 3.68 (1.53-8.82)] were significantly predictors for COVID19 disease severity after adjusting for other variables. Conclusion: From this study, we conclude that being age 60 or older and 40-59 age groups, having symptoms of fever, fatigue, and underlying comorbid illness hypertension. Were identified a significant predictor of severe COVID-19 disease; despite our limitation of study data highlights the important factors associated with disease severity with covid19 admitted to Selgalu treatment center.
Background: Most people infected with the SARS-CoV-2 virus experienced mild to moderate respiratory illness and recovered without requiring special treatment. However, some became seriously ill with conditions that require medical attention and intensive care unit (ICU) admission. Severity varies among individuals; this may be due to age differences and the presence of underlying disease conditions. Objective: To identify factors associated with disease severity among COVID19 patients treated at Selgalu treatment center from November 1, 2020, to April 30, 2021. Methods: A case-control study was implemented among patients admitted to Selgalu COVID19 treatment center in October 2021. A 210 (70 severe disease and 140 non-severe diseases), cases (disease severity), and controls (non-severe disease). Data entered to Epi data 4.6, exported to SPSS 25. A Chi-square test with a p-value of <0.05 was used as a statistically significant difference between characteristics of disease severity and non-severity of disease. Multivariable binary logistic regression was used to determine variables associated with disease severity based on an adjusted odds ratio with 95% CI and p-value < 0.05. Results: 210 (70 cases and 140 controls) selected charts in this study. Patients age category between 40-59 [AOR: 5.30 (2.27-12.34)], aged 60 or older [AOR: 3.85 (1.39-10.64)], patients with fever [AOR: 3.98 (1.59-9.96)], fatigue [AOR: 3.14 (1.50-6.54)], and hypertensive patients [AOR: 3.68 (1.53-8.82)] were significantly predictors for COVID19 disease severity after adjusting for other variables. Conclusion: From this study, we conclude that being age 60 or older and 40-59 age groups, having symptoms of fever, fatigue, and underlying comorbid illness hypertension. Were identified a significant predictor of severe COVID-19 disease; despite our limitation of study data highlights the important factors associated with disease severity with covid19 admitted to Selgalu treatment center.
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