Your browser doesn't support javascript.
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.
  • Elijah IM; Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China.
  • Amsalu E; Armauer Hansen Research Institute, Ministry of Health, Addis Ababa 1005, Ethiopia.
  • Jian X; Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China.
  • Cao M; Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China.
  • Mibei EK; University of Kabianga, School of Health Sciences, Kericho 2030-20200, Kenya.
  • Kerosi DO; Medical Genetics Laboratory, School of Life Science, Central South University, Changsha 410083, China.
  • Mwatsahu FG; Department of Environmental Health and Disease Control, School of Public Health, Jomo Kenyatta University of Agriculture and Technology, Nairobi 62000 - 00200, Kenya.
  • Wang W; Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China.
  • Onyangore F; Centre for Precision Medicine, Edith Cowan University, Perth WA 6027, Australia.
  • Wang Y; University of Kabianga, School of Health Sciences, Kericho 2030-20200, Kenya.
Biosaf Health ; 4(5): 330-338, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-1906819
ABSTRACT
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 (O2), oxygen saturation levels (SPO2), 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, SPO2, 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.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study Language: English Journal: Biosaf Health Year: 2022 Document Type: Article Affiliation country: J.bsheal.2022.06.002

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study Language: English Journal: Biosaf Health Year: 2022 Document Type: Article Affiliation country: J.bsheal.2022.06.002