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Characterization and determinant factors of critical illness and in-hospital mortality of COVID-19 patients: A retrospective cohort of 1,792 patients in Kenya
Limited data is available on the coronavirus disease 2019 (COVID-19), critical illness rate, and in-hospital mortality in the African setting. This study investigates determinants of critical illness and in-hospital mortality among COVID-19 patients in Kenya. We conducted a retrospective cohort stud...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Chinese Medical Association Publishing House. Published by Elsevier BV.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9236624/ https://www.ncbi.nlm.nih.gov/pubmed/35782165 http://dx.doi.org/10.1016/j.bsheal.2022.06.002 |
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author | Elijah, Isinta M Amsalu, Endawoke Jian, Xuening Cao, Mingyang Mibei, Eric K Kerosi, Danvas O Mwatsahu, Francis G Wang, Wei Onyangore, Faith Wang, Youxin |
author_facet | Elijah, Isinta M Amsalu, Endawoke Jian, Xuening Cao, Mingyang Mibei, Eric K Kerosi, Danvas O Mwatsahu, Francis G Wang, Wei Onyangore, Faith Wang, Youxin |
author_sort | Elijah, Isinta M |
collection | PubMed |
description | Limited data is available on the coronavirus disease 2019 (COVID-19), critical illness rate, and in-hospital mortality in the African setting. This study investigates determinants of critical illness and in-hospital mortality among COVID-19 patients in Kenya. We conducted a retrospective cohort study at Kenyatta National Hospital (KNH) in Kenya. Multivariate logistic regression and Cox proportional hazard regression were employed to determine predictor factors for intensive care unit (ICU) admission and in-hospital mortality, respectively. In addition, the Kaplan-Meier model was used to compare the survival times using log-rank tests. As a result, 346 (19.3%) COVID-19 patients were admitted to ICU, and 271 (15.1%) died. The majority of those admitted to the hospital were male, 1,137 (63.4%) and asymptomatic, 1,357 (75.7%). The most prevalent clinical features were shortness of breath, fever, and dry cough. In addition, older age, male, health status, patient on oxygen (O(2)), oxygen saturation levels (SPO(2)), headache, dry cough, comorbidities, obesity, cardiovascular diseases (CVDs), diabetes, chronic lung disease (CLD), and malignancy/cancer can predicate the risk of ICU admission, with an area under the receiver operating characteristic curve (AUC-ROC) of 0.90 (95% confidence interval [CI]: 0.88–0.92). Survival analysis indicated 271 (15.1%) patients died and identified older age, male, headache, shortness of breath, health status, patient on oxygen, SPO(2), headache, comorbidity, CVDs, diabetes, CLD, malignancy/cancer, and smoking as risk factors for mortality (AUC-ROC: 0.90, 95% CI: 0.89–0.91). This is the first attempt to explore predictors for ICU admission and hospital mortality among COVID-19 patients in Kenya. |
format | Online Article Text |
id | pubmed-9236624 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Chinese Medical Association Publishing House. Published by Elsevier BV. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92366242022-06-28 Characterization and determinant factors of critical illness and in-hospital mortality of COVID-19 patients: A retrospective cohort of 1,792 patients in Kenya Elijah, Isinta M Amsalu, Endawoke Jian, Xuening Cao, Mingyang Mibei, Eric K Kerosi, Danvas O Mwatsahu, Francis G Wang, Wei Onyangore, Faith Wang, Youxin Biosaf Health Article Limited data is available on the coronavirus disease 2019 (COVID-19), critical illness rate, and in-hospital mortality in the African setting. This study investigates determinants of critical illness and in-hospital mortality among COVID-19 patients in Kenya. We conducted a retrospective cohort study at Kenyatta National Hospital (KNH) in Kenya. Multivariate logistic regression and Cox proportional hazard regression were employed to determine predictor factors for intensive care unit (ICU) admission and in-hospital mortality, respectively. In addition, the Kaplan-Meier model was used to compare the survival times using log-rank tests. As a result, 346 (19.3%) COVID-19 patients were admitted to ICU, and 271 (15.1%) died. The majority of those admitted to the hospital were male, 1,137 (63.4%) and asymptomatic, 1,357 (75.7%). The most prevalent clinical features were shortness of breath, fever, and dry cough. In addition, older age, male, health status, patient on oxygen (O(2)), oxygen saturation levels (SPO(2)), headache, dry cough, comorbidities, obesity, cardiovascular diseases (CVDs), diabetes, chronic lung disease (CLD), and malignancy/cancer can predicate the risk of ICU admission, with an area under the receiver operating characteristic curve (AUC-ROC) of 0.90 (95% confidence interval [CI]: 0.88–0.92). Survival analysis indicated 271 (15.1%) patients died and identified older age, male, headache, shortness of breath, health status, patient on oxygen, SPO(2), headache, comorbidity, CVDs, diabetes, CLD, malignancy/cancer, and smoking as risk factors for mortality (AUC-ROC: 0.90, 95% CI: 0.89–0.91). This is the first attempt to explore predictors for ICU admission and hospital mortality among COVID-19 patients in Kenya. Chinese Medical Association Publishing House. Published by Elsevier BV. 2022-10 2022-06-27 /pmc/articles/PMC9236624/ /pubmed/35782165 http://dx.doi.org/10.1016/j.bsheal.2022.06.002 Text en © 2022 Chinese Medical Association Publishing House. Published by Elsevier BV. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Elijah, Isinta M Amsalu, Endawoke Jian, Xuening Cao, Mingyang Mibei, Eric K Kerosi, Danvas O Mwatsahu, Francis G Wang, Wei Onyangore, Faith Wang, Youxin Characterization and determinant factors of critical illness and in-hospital mortality of COVID-19 patients: A retrospective cohort of 1,792 patients in Kenya |
title | Characterization and determinant factors of critical illness and in-hospital mortality of COVID-19 patients: A retrospective cohort of 1,792 patients in Kenya |
title_full | Characterization and determinant factors of critical illness and in-hospital mortality of COVID-19 patients: A retrospective cohort of 1,792 patients in Kenya |
title_fullStr | Characterization and determinant factors of critical illness and in-hospital mortality of COVID-19 patients: A retrospective cohort of 1,792 patients in Kenya |
title_full_unstemmed | Characterization and determinant factors of critical illness and in-hospital mortality of COVID-19 patients: A retrospective cohort of 1,792 patients in Kenya |
title_short | Characterization and determinant factors of critical illness and in-hospital mortality of COVID-19 patients: A retrospective cohort of 1,792 patients in Kenya |
title_sort | characterization and determinant factors of critical illness and in-hospital mortality of covid-19 patients: a retrospective cohort of 1,792 patients in kenya |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9236624/ https://www.ncbi.nlm.nih.gov/pubmed/35782165 http://dx.doi.org/10.1016/j.bsheal.2022.06.002 |
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