Incidence and predictors of death from COVID-19 among patients admitted to treatment center of Wollega University Referral Hospital, Western Ethiopia: A retrospective cohort study
<h4>Introduction</h4> Currently, COVID-19 contributes to mortality and morbidity in developed as well as in developing countries since December 2019. However, there is scarcity of evidence regarding the incidence and predictors of death among patients admitted with COVID-19 in developing...
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Public Library of Science (PLoS)
2022-01-01
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Series: | PLoS ONE |
Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328505/?tool=EBI |
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author | Tadesse Tolossa Bizuneh Wakuma Diriba Ayala Dejene Seyoum Getahun Fetensa Ayantu Getahun Diriba Mulisa Emiru Merdassa Atomssa Reta Tsegaye Tesfaye Shibiru Ebisa Turi Lami Bayisa Ginenus Fekadu Balay Bekele Ilili Feyisa |
author_facet | Tadesse Tolossa Bizuneh Wakuma Diriba Ayala Dejene Seyoum Getahun Fetensa Ayantu Getahun Diriba Mulisa Emiru Merdassa Atomssa Reta Tsegaye Tesfaye Shibiru Ebisa Turi Lami Bayisa Ginenus Fekadu Balay Bekele Ilili Feyisa |
author_sort | Tadesse Tolossa |
collection | DOAJ |
description | <h4>Introduction</h4> Currently, COVID-19 contributes to mortality and morbidity in developed as well as in developing countries since December 2019. However, there is scarcity of evidence regarding the incidence and predictors of death among patients admitted with COVID-19 in developing country including Ethiopia, where the numbers of deaths are under-reported. Hence, this study aimed to assess the incidence and predictors of death among patients admitted with COVID-19 in Wollega University Referral Hospital (WURH), western Ethiopia. <h4>Methods</h4> An institution based retrospective cohort study design was conducted among 318 patients admitted with COVID-19 in WURH treatment center. Patients who were tested positive for COVID-19 by using rRT-PCR test and admitted with the diagnosis of severe COVID-19 cases from September 30, 2020 to June 10, 2021 were a source population. Epidata version 3.2 was used for data entry, and STATA version 14 for analysis. A Cox proportional hazard regression analysis was used to determine factors associated with mortality from COVID-19. Multivariable Cox regression model with 95% CI and Adjusted Hazard Ratio (AHR) was used to identify a significant predictor of mortality from COVID-19 at p-value < 0.05. <h4>Results</h4> A total of 318 patients were included in final analysis with mean age of 44 (SD±16.7) years and about two third (67.9%) were males. More than half (55.7%) of patients had no comorbidity on admission. The majority, 259 (81.45%) of patients recovered from COVID-19 and 267 (84%) of patients were censored at the end of follow up. The incidence rate of mortality was 14.1 per/1000 (95%CI: 10.7, 18.5) person days observation. Age ≥ 59 years (AHR: 5.76, 95%CI: 2.58, 12.84), low oxygen saturation (AHR: 2.34, 95% CI: (2.34, 4.17), and delayed presentation (AHR: 5.60, 95%CI: 2.97, 10.56) were independent predictors of mortality among COVID-19 patients. <h4>Conclusion</h4> The mortality rate of COVID-19 pandemic was high in the study area, and most of death was happened during the first 10 days. Being old age, low oxygen saturation and delayed presentation were factors which predict mortality due to COVID-19. Hence, strengthening the health care delivery system to satisfy the need of the patients should get due attention to reduce the incidence of mortality from COVID-19 cases. |
first_indexed | 2024-12-11T16:41:18Z |
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language | English |
last_indexed | 2024-12-11T16:41:18Z |
publishDate | 2022-01-01 |
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spelling | doaj.art-3e2c36b3ead24aa19ec7c6083c8b706e2022-12-22T00:58:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01177Incidence and predictors of death from COVID-19 among patients admitted to treatment center of Wollega University Referral Hospital, Western Ethiopia: A retrospective cohort studyTadesse TolossaBizuneh WakumaDiriba AyalaDejene SeyoumGetahun FetensaAyantu GetahunDiriba MulisaEmiru Merdassa AtomssaReta TsegayeTesfaye ShibiruEbisa TuriLami BayisaGinenus FekaduBalay BekeleIlili Feyisa<h4>Introduction</h4> Currently, COVID-19 contributes to mortality and morbidity in developed as well as in developing countries since December 2019. However, there is scarcity of evidence regarding the incidence and predictors of death among patients admitted with COVID-19 in developing country including Ethiopia, where the numbers of deaths are under-reported. Hence, this study aimed to assess the incidence and predictors of death among patients admitted with COVID-19 in Wollega University Referral Hospital (WURH), western Ethiopia. <h4>Methods</h4> An institution based retrospective cohort study design was conducted among 318 patients admitted with COVID-19 in WURH treatment center. Patients who were tested positive for COVID-19 by using rRT-PCR test and admitted with the diagnosis of severe COVID-19 cases from September 30, 2020 to June 10, 2021 were a source population. Epidata version 3.2 was used for data entry, and STATA version 14 for analysis. A Cox proportional hazard regression analysis was used to determine factors associated with mortality from COVID-19. Multivariable Cox regression model with 95% CI and Adjusted Hazard Ratio (AHR) was used to identify a significant predictor of mortality from COVID-19 at p-value < 0.05. <h4>Results</h4> A total of 318 patients were included in final analysis with mean age of 44 (SD±16.7) years and about two third (67.9%) were males. More than half (55.7%) of patients had no comorbidity on admission. The majority, 259 (81.45%) of patients recovered from COVID-19 and 267 (84%) of patients were censored at the end of follow up. The incidence rate of mortality was 14.1 per/1000 (95%CI: 10.7, 18.5) person days observation. Age ≥ 59 years (AHR: 5.76, 95%CI: 2.58, 12.84), low oxygen saturation (AHR: 2.34, 95% CI: (2.34, 4.17), and delayed presentation (AHR: 5.60, 95%CI: 2.97, 10.56) were independent predictors of mortality among COVID-19 patients. <h4>Conclusion</h4> The mortality rate of COVID-19 pandemic was high in the study area, and most of death was happened during the first 10 days. Being old age, low oxygen saturation and delayed presentation were factors which predict mortality due to COVID-19. Hence, strengthening the health care delivery system to satisfy the need of the patients should get due attention to reduce the incidence of mortality from COVID-19 cases.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328505/?tool=EBI |
spellingShingle | Tadesse Tolossa Bizuneh Wakuma Diriba Ayala Dejene Seyoum Getahun Fetensa Ayantu Getahun Diriba Mulisa Emiru Merdassa Atomssa Reta Tsegaye Tesfaye Shibiru Ebisa Turi Lami Bayisa Ginenus Fekadu Balay Bekele Ilili Feyisa Incidence and predictors of death from COVID-19 among patients admitted to treatment center of Wollega University Referral Hospital, Western Ethiopia: A retrospective cohort study PLoS ONE |
title | Incidence and predictors of death from COVID-19 among patients admitted to treatment center of Wollega University Referral Hospital, Western Ethiopia: A retrospective cohort study |
title_full | Incidence and predictors of death from COVID-19 among patients admitted to treatment center of Wollega University Referral Hospital, Western Ethiopia: A retrospective cohort study |
title_fullStr | Incidence and predictors of death from COVID-19 among patients admitted to treatment center of Wollega University Referral Hospital, Western Ethiopia: A retrospective cohort study |
title_full_unstemmed | Incidence and predictors of death from COVID-19 among patients admitted to treatment center of Wollega University Referral Hospital, Western Ethiopia: A retrospective cohort study |
title_short | Incidence and predictors of death from COVID-19 among patients admitted to treatment center of Wollega University Referral Hospital, Western Ethiopia: A retrospective cohort study |
title_sort | incidence and predictors of death from covid 19 among patients admitted to treatment center of wollega university referral hospital western ethiopia a retrospective cohort study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328505/?tool=EBI |
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