Utilization of Herbal Medicines among Diabetic Patients Attending Kenyatta National Hospital Outpatient Clinic

Background: World Health Organization has estimated that 70-90 % of Africa’s population still relies on herbal remedies in order to meet their healthcare needs. Although the role of herbal medicines in the management of diabetes is an emerging health issue, use of herb remedies is common among diabetics. Objectives: To evaluate knowledge, perception and describe the pattern of utilization of herbal medicines among diabetic outpatients at Kenyatta National Hospital. Methodology: The study was a tertiary hospital-based cross sectional study. Simple random sampling technique was used to select 251 adult diabetic outpatients who were interviewed. Data was captured into Microsoft Excel computer software and then exported to SPSS version 17.0 for analysis. Descriptive data was analyzed quantitatively and presented in form of charts and tables as appropriate. Statistical significance was determined using Pearson Chi Square at p<0.05. Where numbers of participants were too small, Fishers exact results were used. Results: The prevalence of use of herbal remedies for managing diabetes mellitus was 7.2%. However, the total prevalence of use of herbs among the diabetic outpatients was 39.5% implying that 32.3% of the study participants used herbs for other medical conditions. The commonest herbs used were ginger and Aloe vera used by 50% of the herbal users. Almost half of the herb users did not regard it important to inform the doctor about their use of herbs. The reasons given for use of herbal medicines were varied; the commonest being that herbs could easily be accessed 13 (13.1%) of the herbal users. There was no statistically significant relationship between socio-demographic characteristics and use of herbs (P>0.05). Conclusion: About 40% of diabetic outpatients are in some form of herbal remedy. In addition, 1 out of 5 of diabetic herbal users use them for managing diabetes; commonest herbs being Aloe vera and ginger. Therefore, healthcare workers and researchers should find ways of harmonizing the utilization of herbal and conventional medicines amongst diabetic patients

Prevalence of Opportunistic Infections in HIV-infected adult patients at Kenyatta National Hospital, Kenya

Background: Opportunistic Infections (OIs) constitute the first manifestation of HIV infection, indicating significant immunodeficiency. OIs remain a leading cause of morbidity and mortality in HIV-infected persons. Since most of OIs are readily treatable and preventable, every effort should be made to facilitated their management. However, there is a need to establish local prevalence of OIs and evaluate their management. This would guide in prioritizing resource and support development of suitable management strategies. Objective: The main objective of this study was to establish the prevalence of HIV-related OIs in adult patients. Methodology: A hospital-based cross-sectional study conducted between July and August 2011 at Kenyatta National Hospital –Comprehensive Care Center (KNH-CCC). Adult patients who were HIV positive and attending outpatient clinic at KNH-CCC were included. Information was collected on patients’ demographics, clinical characteristics and presence of new or active OIs. Data was analyzed using Statistical Package for social Sciences (SPSS) version 11.5. Results: The prevalence of opportunistic infections was 14.1 % (95% CI: 10.7-18.5).  Overall, the most commonly reported bacterial infection was pneumonia (6.4%) whereas pulmonary tuberculosis was reported in 3.6% of patients. Significant association was found between a patients’ current OI status and WHO stage when HIV was diagnosed (AOR= 3.79 [95% CI = 1.43 – 10.03], P=0.007) and duration since HIV diagnosis (AOR 3.89 [95% CI= 1.58-9.59], P=0.003.  90% of patients were prescribed Co-trimoxazole as chemoprophylaxis agent. Conclusion: There was a high prevalence of OIs among the HIV/AIDS patients at KNH-CCC. Bacterial Pneumonia and pulmonary tuberculosis were the most commonly observed OIs. Keyword: Prevalence, Opportunistic-Infections, HIV, Patients

Impact of depression on adherence to antiretroviral therapy among HIV/AIDS patients at a Kenyan referral hospital

Background: Kenya is faced with an increasing challenge of co-morbid psychological and social factors among HIV-Infected patients which has had a profound impact on their medication adherence. A major psychosocial factor that is a barrier in adherence is depression associated with HIV. This study aimed at measuring the effect of depression on participants’ own reported adherence to antiretroviral therapy. Objectives: To determine the impact depression has had on adherence to antiretroviral therapy among HIV-infected patients at a Kenyatta Hospital. Methodology: A cross-sectional study design was carried out at Kenyatta National Hospital, Nairobi, Kenya. Three hundred and eighty four (384) HIV infected participants were assessed for HIV related depression and adherence to ART. Levels of HIV related depression and adherence to ART were ascertained. Results: The prevalence of depression was 23.3 %.  The prevalence of mild, moderate and severe depression was 21.2 %, 1.8 % and 0.3 % respectively. The mean non adherence and average mean adherence rate were 27.9 % and 22.4 % respectively. Conclusion: There was a minimal relationship between depression and non-adherence to antiretroviral therapy among adult HIV infected patients. Depression was not statistically significantly associated with adherence to antiretroviral therapy. Key words: Depression, adherence, antiretroviral therap

Sero-surveillance for IgG to SARS-CoV-2 at antenatal care clinics in three Kenyan referral hospitals: Repeated cross-sectional surveys 2020-21.

INTRODUCTION: The high proportion of SARS-CoV-2 infections that have remained undetected presents a challenge to tracking the progress of the pandemic and estimating the extent of population immunity. METHODS: We used residual blood samples from women attending antenatal care services at three hospitals in Kenya between August 2020 and October 2021and a validated IgG ELISA for SARS-Cov-2 spike protein and adjusted the results for assay sensitivity and specificity. We fitted a two-component mixture model as an alternative to the threshold analysis to estimate of the proportion of individuals with past SARS-CoV-2 infection. RESULTS: We estimated seroprevalence in 2,981 women; 706 in Nairobi, 567 in Busia and 1,708 in Kilifi. By October 2021, 13% of participants were vaccinated (at least one dose) in Nairobi, 2% in Busia. Adjusted seroprevalence rose in all sites; from 50% (95%CI 42-58) in August 2020, to 85% (95%CI 78-92) in October 2021 in Nairobi; from 31% (95%CI 25-37) in May 2021 to 71% (95%CI 64-77) in October 2021 in Busia; and from 1% (95% CI 0-3) in September 2020 to 63% (95% CI 56-69) in October 2021 in Kilifi. Mixture modelling, suggests adjusted cross-sectional prevalence estimates are underestimates; seroprevalence in October 2021 could be 74% in Busia and 72% in Kilifi. CONCLUSIONS: There has been substantial, unobserved transmission of SARS-CoV-2 in Nairobi, Busia and Kilifi Counties. Due to the length of time since the beginning of the pandemic, repeated cross-sectional surveys are now difficult to interpret without the use of models to account for antibody waning

Stan code and input data for estimating adjusted seroprevalence.

Stan code and input data for estimating adjusted seroprevalence. Document supports "Sero-surveillance for IgG to SARS-CoV-2 at antenatal care clinics in three Kenyan referral hospitals: Repeated cross-sectional surveys 2020–21"

Sero-surveillance for IgG to SARS-CoV-2 at antenatal care clinics in three Kenyan referral hospitals: Repeated cross-sectional surveys 2020-21.

IntroductionThe high proportion of SARS-CoV-2 infections that have remained undetected presents a challenge to tracking the progress of the pandemic and estimating the extent of population immunity.MethodsWe used residual blood samples from women attending antenatal care services at three hospitals in Kenya between August 2020 and October 2021and a validated IgG ELISA for SARS-Cov-2 spike protein and adjusted the results for assay sensitivity and specificity. We fitted a two-component mixture model as an alternative to the threshold analysis to estimate of the proportion of individuals with past SARS-CoV-2 infection.ResultsWe estimated seroprevalence in 2,981 women; 706 in Nairobi, 567 in Busia and 1,708 in Kilifi. By October 2021, 13% of participants were vaccinated (at least one dose) in Nairobi, 2% in Busia. Adjusted seroprevalence rose in all sites; from 50% (95%CI 42-58) in August 2020, to 85% (95%CI 78-92) in October 2021 in Nairobi; from 31% (95%CI 25-37) in May 2021 to 71% (95%CI 64-77) in October 2021 in Busia; and from 1% (95% CI 0-3) in September 2020 to 63% (95% CI 56-69) in October 2021 in Kilifi. Mixture modelling, suggests adjusted cross-sectional prevalence estimates are underestimates; seroprevalence in October 2021 could be 74% in Busia and 72% in Kilifi.ConclusionsThere has been substantial, unobserved transmission of SARS-CoV-2 in Nairobi, Busia and Kilifi Counties. Due to the length of time since the beginning of the pandemic, repeated cross-sectional surveys are now difficult to interpret without the use of models to account for antibody waning

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Zika is an emerging virus whose rapid spread is of great public health concern. Knowledge about transmission remains incomplete, especially concerning potential transmission in geographic areas in which it has not yet been introduced. To identify unknown vectors of Zika, we developed a data-driven model linking vector species and the Zika virus via vector-virus trait combinations that confer a propensity toward associations in an ecological network connecting flaviviruses and their mosquito vectors. Our model predicts that thirty-five species may be able to transmit the virus, seven of which are found in the continental United States, including Culex quinquefasciatus and Cx. pipiens. We suggest that empirical studies prioritize these species to confirm predictions of vector competence, enabling the correct identification of populations at risk for transmission within the United States. DOI: http://dx.doi.org/10.7554/eLife.22053.00