Clinical Course and Factors Associated With Hospital Admission and Mortality among Sars-Cov 2 Patients within Nairobi Metropolitan Area.

This study aims to investigate the clinical course and factors associated with hospital admission and mortality among SARS-CoV-2 patients within the Nairobi Metropolitan Area. The study utilizes a multicenter retrospective cohort design, collecting clinical characteristics and laboratory parameters of hospitalized patients from March 2020 to May 2022. Data analysis includes percentages, frequencies, chi-square tests, Kaplan-Meier analysis, pairwise comparisons, and multivariate regression models. Ethical considerations are observed throughout the research process. The study findings highlight significant associations between comorbidities, such as hypertension, and increased mortality risk due to COVID-19. Symptoms including fever, cough, dyspnea, chest pain, sore throat, and loss of smell/taste are also identified as predictors of mortality. Abnormal laboratory parameters, such as oxygen saturation, procalcitonin, glucose levels, serum creatinine, and gamma-glutamyl transpeptidase, are associated with mortality. However, demographic factors and certain vital signs do not exhibit significant associations. Recommendations based on this study suggest increased monitoring and management of comorbidities, early identification and management of symptoms, regular monitoring of laboratory parameters, continued research and collaboration, and implementation of preventive measures. Overall, a multidisciplinary approach involving healthcare professionals, researchers, policymakers, and the public is crucial to improve COVID-19 outcomes and reduce mortality rates. Adaptation of strategies based on emerging evidence and resource allocation is essential for effective management of the pandemic.

Multiple Logistic Regression Model for Determinants of Injectable Contraceptive Uptake Among Women of Reproductive Age in Kenya.

Objective: The recent increase in the uptake of injectable contraceptives has occurred at the expense of the other modern contraceptive methods but the knowledge gap still exists on modeling dynamics and determinants associated with the use of the injectable. This study sought to model for injectable contraceptive usage to bridge the knowledge gap on the use of injectable contraceptives among women of childbearing age in Kenya. Materials and methods: Analytical cross-sectional study design was adopted. Secondary data for women collected during the (Performance Monitoring for Action) PMA2020 survey was used. PMA2020 survey used multistage stratified sampling with urban-rural representation. To establish the factors associated with the uptake of injectable contraceptives, a multiple logistic regression model was fitted using Stata version 13 and R version 3.5.3 statistical software. Hosmer-Lemeshow Test statistic was used to evaluate the goodness of model fit in predicting injectable contraceptive usage. Results: Multivariable analysis showed that women with post-primary/vocational levels of education were 54% less likely to use an injectable contraceptive compared to those who had no education at all. Hosmer-Lemeshow (HL) goodness of fit test statistic indicated that the model was a good fit for prediction. Education, marital status, wealth quintile, place of residence and number of births were significant predictors of the injectable contraceptive uptake among women of reproductive age in Kenya. Conclusion: The findings of this study will inform the design of targeted interventions aimed at addressing the increasing demand for injectable devices among women of reproductive age in Kenya.