Characteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context

<h4>Background</h4> The COVID-19 pandemic seems to have a different picture in Africa; the first case was identified in the continent after it had already caused a significant loss to the rest of the world and the reported number of cases and mortality rate has been low. Understanding th...

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Autores principales: Tigist W. Leulseged, Ishmael S. Hassen, Endalkachew H. Maru, Wuletaw C. Zewsde, Negat W. Chamiso, Abdi B. Bayisa, Daniel S. Abebe, Birhanu T. Ayele, Kalkidan T. Yegle, Mesay G. Edo, Eyosyas K. Gurara, Dereje D. Damete, Yared A. Tolera
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Publicado: Public Library of Science (PLoS) 2021
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spelling oai:doaj.org-article:7cca4f7d2a2c4af3a65e2b4dcf9425092021-11-18T06:34:43ZCharacteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context1932-6203https://doaj.org/article/7cca4f7d2a2c4af3a65e2b4dcf9425092021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8577729/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4> The COVID-19 pandemic seems to have a different picture in Africa; the first case was identified in the continent after it had already caused a significant loss to the rest of the world and the reported number of cases and mortality rate has been low. Understanding the characteristics and outcome of the pandemic in the African setup is therefore crucial. <h4>Aim</h4> To assess the characteristics and outcome of Patients with COVID-19 and to identify determinants of the disease outcome among patients admitted to Millennium COVID-19 Care Center in Ethiopia. <h4>Methods</h4> A prospective cohort study was conducted among 1345 consecutively admitted RT-PCR confirmed Patients with COVID-19 from July to September, 2020. Frequency tables, KM plots, median survival times and Log-rank test were used to describe the data and compare survival distribution between groups. Cox proportional hazard survival model was used to identify determinants of time to clinical recovery and the independent variables, where adjusted hazard ratio, P-value and 95% CI for adjusted hazard ratio were used for testing significance and interpretation of results. Binary logistic regression model was used to assess the presence of a statistically significant association between disease outcome and the independent variables, where adjusted odds ratio, P-value and 95% CI for adjusted odds ratio were used for testing significance and interpretation of results. <h4>Results</h4> Among the study population, 71 (5.3%) died, 72 (5.4%) were transferred and the rest 1202 (89.4%) were clinically improved. The median time to clinical recovery was 14 days. On the multivariable Cox proportional hazard model; temperature (AHR = 1.135, 95% CI = 1.011, 1.274, p-value = 0.032), COVID-19 severity (AHR = 0.660, 95% CI = 0.501, 0.869, p-value = 0.003), and cough (AHR = 0.705, 95% CI = 0.519, 0.959, p-value = 0.026) were found to be significant determinants of time to clinical recovery. On the binary logistic regression, the following factors were found to be significantly associated with disease outcome; SPO2 (AOR = 0.302, 95% CI = 0.193, 0.474, p-value = 0.0001), shortness of breath (AOR = 0.354, 95% CI = 0.213, 0.590, p-value = 0.0001) and diabetes mellitus (AOR = 0.549, 95% CI = 0.337, 0.894, p-value = 0.016). <h4>Conclusions</h4> The average duration of time to clinical recovery was 14 days and 89.4% of the patients achieved clinical recovery. The mortality rate of the studied population is lower than reports from other countries including those in Africa. Having severe COVID-19 disease severity and presenting with cough were found to be associated with delayed clinical recovery of the disease. On the other hand, being hyperthermic is associated with shorter disease duration (faster time to clinical recovery). In addition, lower oxygen saturation, subjective complaint of shortness of breath and being diabetic were associated with unfavorable disease outcome. Therefore, patients with these factors should be followed cautiously for a better outcome.Tigist W. LeulsegedIshmael S. HassenEndalkachew H. MaruWuletaw C. ZewsdeNegat W. ChamisoAbdi B. BayisaDaniel S. AbebeBirhanu T. AyeleKalkidan T. YegleMesay G. EdoEyosyas K. GuraraDereje D. DameteYared A. ToleraPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Tigist W. Leulseged
Ishmael S. Hassen
Endalkachew H. Maru
Wuletaw C. Zewsde
Negat W. Chamiso
Abdi B. Bayisa
Daniel S. Abebe
Birhanu T. Ayele
Kalkidan T. Yegle
Mesay G. Edo
Eyosyas K. Gurara
Dereje D. Damete
Yared A. Tolera
Characteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context
description <h4>Background</h4> The COVID-19 pandemic seems to have a different picture in Africa; the first case was identified in the continent after it had already caused a significant loss to the rest of the world and the reported number of cases and mortality rate has been low. Understanding the characteristics and outcome of the pandemic in the African setup is therefore crucial. <h4>Aim</h4> To assess the characteristics and outcome of Patients with COVID-19 and to identify determinants of the disease outcome among patients admitted to Millennium COVID-19 Care Center in Ethiopia. <h4>Methods</h4> A prospective cohort study was conducted among 1345 consecutively admitted RT-PCR confirmed Patients with COVID-19 from July to September, 2020. Frequency tables, KM plots, median survival times and Log-rank test were used to describe the data and compare survival distribution between groups. Cox proportional hazard survival model was used to identify determinants of time to clinical recovery and the independent variables, where adjusted hazard ratio, P-value and 95% CI for adjusted hazard ratio were used for testing significance and interpretation of results. Binary logistic regression model was used to assess the presence of a statistically significant association between disease outcome and the independent variables, where adjusted odds ratio, P-value and 95% CI for adjusted odds ratio were used for testing significance and interpretation of results. <h4>Results</h4> Among the study population, 71 (5.3%) died, 72 (5.4%) were transferred and the rest 1202 (89.4%) were clinically improved. The median time to clinical recovery was 14 days. On the multivariable Cox proportional hazard model; temperature (AHR = 1.135, 95% CI = 1.011, 1.274, p-value = 0.032), COVID-19 severity (AHR = 0.660, 95% CI = 0.501, 0.869, p-value = 0.003), and cough (AHR = 0.705, 95% CI = 0.519, 0.959, p-value = 0.026) were found to be significant determinants of time to clinical recovery. On the binary logistic regression, the following factors were found to be significantly associated with disease outcome; SPO2 (AOR = 0.302, 95% CI = 0.193, 0.474, p-value = 0.0001), shortness of breath (AOR = 0.354, 95% CI = 0.213, 0.590, p-value = 0.0001) and diabetes mellitus (AOR = 0.549, 95% CI = 0.337, 0.894, p-value = 0.016). <h4>Conclusions</h4> The average duration of time to clinical recovery was 14 days and 89.4% of the patients achieved clinical recovery. The mortality rate of the studied population is lower than reports from other countries including those in Africa. Having severe COVID-19 disease severity and presenting with cough were found to be associated with delayed clinical recovery of the disease. On the other hand, being hyperthermic is associated with shorter disease duration (faster time to clinical recovery). In addition, lower oxygen saturation, subjective complaint of shortness of breath and being diabetic were associated with unfavorable disease outcome. Therefore, patients with these factors should be followed cautiously for a better outcome.
format article
author Tigist W. Leulseged
Ishmael S. Hassen
Endalkachew H. Maru
Wuletaw C. Zewsde
Negat W. Chamiso
Abdi B. Bayisa
Daniel S. Abebe
Birhanu T. Ayele
Kalkidan T. Yegle
Mesay G. Edo
Eyosyas K. Gurara
Dereje D. Damete
Yared A. Tolera
author_facet Tigist W. Leulseged
Ishmael S. Hassen
Endalkachew H. Maru
Wuletaw C. Zewsde
Negat W. Chamiso
Abdi B. Bayisa
Daniel S. Abebe
Birhanu T. Ayele
Kalkidan T. Yegle
Mesay G. Edo
Eyosyas K. Gurara
Dereje D. Damete
Yared A. Tolera
author_sort Tigist W. Leulseged
title Characteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context
title_short Characteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context
title_full Characteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context
title_fullStr Characteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context
title_full_unstemmed Characteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context
title_sort characteristics and outcome profile of hospitalized african patients with covid-19: the ethiopian context
publisher Public Library of Science (PLoS)
publishDate 2021
url https://doaj.org/article/7cca4f7d2a2c4af3a65e2b4dcf942509
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