Awoke Seyoum

Bio: Awoke Seyoum is an academic researcher from Bahir Dar University. The author has contributed to research in topics: Tuberculosis & Repeated measures design. The author has an hindex of 2, co-authored 4 publications receiving 41 citations.

Prevalence and risk factors of type-2 diabetes mellitus in Ethiopia: systematic review and meta-analysis

Abstract: Diabetes mellitus (DM) is a public health problem in developing as well as developed nations. DM leads to many complications that are associated with higher morbidity and mortality worldwide. Therefore, the current study was planned to assess the prevalence and risk factors of type-2 DM in Ethiopian population. Six electronic databases such as: PubMed, Scopus, Hinari, Web of science, Google Scholar, and African Journals Online were searched for studies published in English up December 30, 2020. Newcastle–Ottawa Scale was used for quality assessment of the included studies. The data was extracted by Microsoft excel and analyzed through Stata version 16 software. The random effect meta-regression analysis was computed at 95% CI to assess the pooled prevalence and risk factors of type-2 DM. Forty observational studies were included in this systematic review and meta-analysis. The pooled prevalence of DM in Ethiopia was 6.5% (95% CI (5.8, 7.3)). The sub-group analysis revealed that the highest prevalence of DM was found in Dire Dawa city administration (14%), and the lowest prevalence was observed in Tigray region (2%). The pooled prevalence of DM was higher (8%) in studies conducted in health facility. Factors like: Age ≥ 40 years ((Adjusted Odds Ratio (AOR): 1.91 (95% CI: 1.05, 3.49)), Illiterate (AOR: 2.74 (95% CI: 1.18, 6.34)), Cigarette smoking (AOR: 1.97 (95% CI: 1.17, 3.32)), Body mass index (BMI) ≥ 25 kg/m2 (AOR: 2.01 (95 CI: 1.46, 2.27)), family history of DM (AOR: 6.14 (95% CI: 2.80, 13.46)), history of hypertension (AOR: 3.00 (95% CI: 1.13, 7.95)) and physical inactivity (AOR: 5.79 (95% CI: 2.12, 15.77)) were significantly associated with type-2 DM in Ethiopian population. In this review, the prevalence of type-2 DM was high. Factors like: Older age, illiteracy, cigarette smoking, MBI ≥ 25, family history of DM, history of hypertension and physical inactivity were an identified risk factors of type-2 DM. Therefore, health education and promotion will be warranted. Further, large scale prospective studies will be recommended to address possible risk factors of type-2 DM in Ethiopian population.

Joint longitudinal data analysis in detecting determinants of CD4 cell count change and adherence to highly active antiretroviral therapy at Felege Hiwot Teaching and Specialized Hospital, North-west Ethiopia (Amhara Region).

Abstract: Adherence and CD4 cell count change measure the progression of the disease in HIV patients after the commencement of HAART. Lack of information about associated factors on adherence to HAART and CD4 cell count reduction is a challenge for the improvement of cells in HIV positive adults. The main objective of adopting joint modeling was to compare separate and joint models of longitudinal repeated measures in identifying long-term predictors of the two longitudinal outcomes: CD4 cell count and adherence to HAART. A longitudinal retrospective cohort study was conducted to examine the joint predictors of CD4 cell count change and adherence to HAART among HIV adult patients enrolled in the first 10 months of the year 2008 and followed-up to June 2012. Joint model was employed to determine joint predictors of two longitudinal response variables over time. Furthermore, the generalized linear mixed effect model had been used for specification of the marginal distribution, conditional to correlated random effect. A total of 792 adult HIV patients were studied to analyze the longitudinal joint model study. The result from this investigation revealed that age, weight, baseline CD4 cell count, ownership of cell phone, visiting times, marital status, residence area and level of disclosure of the disease to family members had significantly affected both outcomes. From the two-way interactions, time * owner of cell phone, time * sex, age * sex, age * level of education as well as time * level of education were significant for CD4 cell count change in the longitudinal data analysis. The multivariate joint model with linear predictor indicates that CD4 cell count change was positively correlated (p ≤ 0.0001) with adherence to HAART. Hence, as adherence to HAART increased, CD4 cell count also increased; and those patients who had significant CD4 cell count change at each visiting time had been encouraged to be good adherents. Joint model analysis was more parsimonious as compared to separate analysis, as it reduces type I error and subject-specific analysis improved its model fit. The joint model operates multivariate analysis simultaneously; and it has great power in parameter estimation. Developing joint model helps validate the observed correlation between the outcomes that have emerged from the association of intercepts. There should be a special attention and intervention for HIV positive adults, especially for those who had poor adherence and with low CD4 cell count change. The intervention may be important for pre-treatment counseling and awareness creation. The study also identified a group of patients who were with maximum risk of CD4 cell count change. It is suggested that this group of patients needs high intervention for counseling.

Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region)

Abstract: CD4 cells are a type of white blood cells that plays a significant role in protecting humans from infectious diseases. Lack of information on associated factors on CD4 cell count reduction is an obstacle for improvement of cells in HIV positive adults. Therefore, the main objective of this study was to investigate baseline factors that could affect initial CD4 cell count change after highly active antiretroviral therapy had been given to adult patients in North West Ethiopia. A retrospective cross-sectional study was conducted among 792 HIV positive adult patients who already started antiretroviral therapy for 1 month of therapy. A Chi square test of association was used to assess of predictor covariates on the variable of interest. Data was secondary source and modeled using generalized linear models, especially Quasi-Poisson regression. The patients’ CD4 cell count changed within a month ranged from 0 to 109 cells/mm3 with a mean of 15.9 cells/mm3 and standard deviation 18.44 cells/mm3. The first month CD4 cell count change was significantly affected by poor adherence to highly active antiretroviral therapy (aRR = 0.506, P value = 2e−16), fair adherence (aRR = 0.592, P value = 0.0120), initial CD4 cell count (aRR = 1.0212, P value = 1.54e−15), low household income (aRR = 0.63, P value = 0.671e−14), middle income (aRR = 0.74, P value = 0.629e−12), patients without cell phone (aRR = 0.67, P value = 0.615e−16), WHO stage 2 (aRR = 0.91, P value = 0.0078), WHO stage 3 (aRR = 0.91, P value = 0.0058), WHO stage 4 (0876, P value = 0.0214), age (aRR = 0.987, P value = 0.000) and weight (aRR = 1.0216, P value = 3.98e−14). Adherence to antiretroviral therapy, initial CD4 cell count, household income, WHO stages, age, weight and owner of cell phone played a major role for the variation of CD4 cell count in our data. Hence, we recommend a close follow-up of patients to adhere the prescribed medication for achievements of CD4 cell count change progression.

Joint Modeling in Detecting Predictors of CD4 Cell Count and Status of Tuberculosis Among People Living with HIV/AIDS Under HAART at Felege Hiwot Teaching and Specialized Hospital, North-West Ethiopia.

Abstract: Background Globally, for individuals infected with HIV, the presence of other infections including TB tends to increase the rate of HIV replication. Of the 8.8 million TB cases worldwide, an estimated 1.1 million (13%) were found to be co-infected with HIV. This research was conducted with the objective to identify potential predictors for the status of TB and CD4 cell count under PLWHIV at Felege Hiwot Specialized Hospital, North-west Ethiopia. Methods A retrospective repeated measurement was taken from a sample of 226 HIV patients. Separate and joint models were conducted for data analysis of CD4 cell count and TB status of people living with HIV. Results The descriptive statistics indicated that among the HIV patients receiving HAART, 26.6% had additional TB. AIDS clinical stage, weight, and hemoglobin level had a significant positive association with CD4 cell count, but a negative association with TB status. Weight and CD4 cell count have a negative relationship with the event of HIV/TB co-infection. Hence, the expected number of CD4 cell count of HIV patients who were co-infected with TB was decreased by 2.34 as compared to people living with HIV without TB. As visiting times of patients to hospitals for treatment increased by one unit, the odds of being co-infected with TB was decreased by 0.05, and the expected number of CD4 cell count was increased by 0.2. As patients' age increased by one year, the expected number of CD4 cell count was decreased by 0.025 cells per/mm3. Conclusion Having lower CD4 cell count, lower weight, late WHO clinical stage, being non-adherent, having opportunistic infection, having lower hemoglobin, being ambulatory and bedridden were associated with a higher risk of co-infection of HIV/TB and were indicators of progression of the disease.

The impacts of medication shortages on patient outcomes: A scoping review

Abstract: Background In recent years, medication shortages have become a growing worldwide issue. This scoping review aimed to systematically synthesise the literature to report on the economic, clinical, and humanistic impacts of medication shortages on patient outcomes. Methods Medline, Embase, Global Health, PsycINFO and International Pharmaceutical Abstracts were searched using the two key concepts of medicine shortage and patient outcomes. Articles were limited to the English language, human studies and there were no limits to the year of publication. Manuscripts included contained information regarding the shortage of a scheduled medication and had gathered data regarding the economic, clinical, and/or humanistic outcomes of drug shortages on human patients. Findings We found that drug shortages were predominantly reported to have adverse economic, clinical and humanistic outcomes to patients. Patients were more commonly reported to have increased out of pocket costs, rates of drug errors, adverse events, mortality, and complaints during times of shortage. There were also reports of equivalent and improved patient outcomes in some cases. Conclusions The results of this review provide valuable insights into the impact drug shortages have on patient outcomes. The majority of studies reported medication shortages resulted in negative patient clinical, economic and humanistic outcomes.

Detecting space-time clusters of COVID-19 in Brazil: mortality, inequality, socioeconomic vulnerability, and the relative risk of the disease in Brazilian municipalities.

Abstract: The first case of COVID-19 in South America occurred in Brazil on February 25, 2020. By July 20, 2020, there were 2,118,646 confirmed cases and 80,120 confirmed deaths. To assist with the development of preventive measures and targeted interventions to combat the pandemic in Brazil, we present a geographic study to detect "active" and "emerging" space-time clusters of COVID-19. We document the relationship between relative risk of COVID-19 and mortality, inequality, socioeconomic vulnerability variables. We used the prospective space-time scan statistic to detect daily COVID-19 clusters and examine the relative risk between February 25-June 7, 2020, and February 25-July 20, 2020, in 5570 Brazilian municipalities. We apply a Generalized Linear Model (GLM) to assess whether mortality rate, GINI index, and social inequality are predictors for the relative risk of each cluster. We detected 7 "active" clusters in the first time period, being one in the north, two in the northeast, two in the southeast, one in the south, and one in the capital of Brazil. In the second period, we found 9 clusters with RR > 1 located in all Brazilian regions. The results obtained through the GLM showed that there is a significant positive correlation between the predictor variables in relation to the relative risk of COVID-19. Given the presence of spatial autocorrelation in the GLM residuals, a spatial lag model was conducted that revealed that spatial effects, and both GINI index and mortality rate were strong predictors in the increase in COVID-19 relative risk in Brazil. Our research can be utilized to improve COVID-19 response and planning in all Brazilian states. The results from this study are particularly salient to public health, as they can guide targeted intervention measures, lowering the magnitude and spread of COVID-19. They can also improve resource allocation such as tests and vaccines (when available) by informing key public health officials about the highest risk areas of COVID-19.

Joint longitudinal data analysis in detecting determinants of CD4 cell count change and adherence to highly active antiretroviral therapy at Felege Hiwot Teaching and Specialized Hospital, North-west Ethiopia (Amhara Region).

Abstract: Adherence and CD4 cell count change measure the progression of the disease in HIV patients after the commencement of HAART. Lack of information about associated factors on adherence to HAART and CD4 cell count reduction is a challenge for the improvement of cells in HIV positive adults. The main objective of adopting joint modeling was to compare separate and joint models of longitudinal repeated measures in identifying long-term predictors of the two longitudinal outcomes: CD4 cell count and adherence to HAART. A longitudinal retrospective cohort study was conducted to examine the joint predictors of CD4 cell count change and adherence to HAART among HIV adult patients enrolled in the first 10 months of the year 2008 and followed-up to June 2012. Joint model was employed to determine joint predictors of two longitudinal response variables over time. Furthermore, the generalized linear mixed effect model had been used for specification of the marginal distribution, conditional to correlated random effect. A total of 792 adult HIV patients were studied to analyze the longitudinal joint model study. The result from this investigation revealed that age, weight, baseline CD4 cell count, ownership of cell phone, visiting times, marital status, residence area and level of disclosure of the disease to family members had significantly affected both outcomes. From the two-way interactions, time * owner of cell phone, time * sex, age * sex, age * level of education as well as time * level of education were significant for CD4 cell count change in the longitudinal data analysis. The multivariate joint model with linear predictor indicates that CD4 cell count change was positively correlated (p ≤ 0.0001) with adherence to HAART. Hence, as adherence to HAART increased, CD4 cell count also increased; and those patients who had significant CD4 cell count change at each visiting time had been encouraged to be good adherents. Joint model analysis was more parsimonious as compared to separate analysis, as it reduces type I error and subject-specific analysis improved its model fit. The joint model operates multivariate analysis simultaneously; and it has great power in parameter estimation. Developing joint model helps validate the observed correlation between the outcomes that have emerged from the association of intercepts. There should be a special attention and intervention for HIV positive adults, especially for those who had poor adherence and with low CD4 cell count change. The intervention may be important for pre-treatment counseling and awareness creation. The study also identified a group of patients who were with maximum risk of CD4 cell count change. It is suggested that this group of patients needs high intervention for counseling.

Frequency of HIV status disclosure, associated factors and outcomes among HIV positive pregnant women at Mbarara Regional Referral Hospital, southwestern Uganda.

Abstract: Introduction Positive HIV results disclosure plays a significant role in the successful prevention and care of HIV infected patients. It provides significant social and health benefits to the individual and the community. Non-disclosure is one of the contextual factors driving the HIV epidemic in Uganda. Study objectives: to determine the frequency of HIV disclosure, associated factors and disclosure outcomes among HIV positive pregnant women at Mbarara Hospital, southwestern Uganda. Methods A cross-sectional study using quantitative and qualitative methods among a group of HIV positive pregnant women attending antenatal clinic was done and consecutive sampling conducted. Results The total participant recruitment was 103, of which 88 (85.4%) had disclosed their serostatus with 57% disclosure to their partners. About 80% had disclosed within less than 2 months of testing HIV positive. Reasons for disclosure included their partners having disclosed to them (27.3%), caring partners (27.3%) and encouragement by health workers (25.0%). Following disclosure, 74%) were comforted and 6.8% were verbally abused. Reasons for non-disclosure were fear of abandonment (33.3%), being beaten (33.3%) and loss of financial and emotional support (13.3%). The factors associated with disclosure were age 26-35 years (OR 3.9, 95% CI 1.03-15.16), primary education (OR 3.53, 95%CI 1.10-11.307) and urban dwelling (OR 4.22, 95% CI 1.27-14.01). Conclusion Participants disclosed mainly to their partners and were comforted and many of them were encouraged by the health workers. There is need to optimize disclosure merits to enable increased participation in treatment and support programs.

Socioeconomic and Demographic Statuses as Determinants of Adherence to Antiretroviral Treatment in HIV Infected Patients: A Systematic Review of the Literature.

Abstract: Background Socioeconomic and demographic statuses are associated with adherence to the treatment of patients with several chronic diseases. However, there is a controversy regarding their impact on adherence among HIV/AIDS patients. Thus, we performed a systematic review of the evidence regarding the association of socioeconomic and demographic statuses with adherence to antiretroviral therapy (ART) among HIV/AIDS patients. Methods The PubMed database was used to search and identify studies concerning about socioeconomic and demographic statuses and HIV/AIDS patients. Data were collected on the association between adherence to ART and varies determinants factors of socioeconomic (income, education, and employment/occupation) and socio-demographic (sex and age). Findings From 393 potentially-relevant articles initially identified, 35 original studies were reviewed in detail, which contained data that were helpful in evaluating the association between socioeconomic/ demographic statuses and adherence to ART among HIV patients. Two original research study has specifically focused on the possible association between socioeconomic status and adherence to ART. Income, level of education, and employment/occupational status were significantly and positively associated with the level of adherence in 7 studies (36.8%), 7 studies (28.0%), and 4 studies (23.5%) respectively out of 19, 25, and 17 studies reviewed. Sex (being male), and age (per year increasing) were significantly and positively associated with the level of adherence in 5 studies (14.3%), and 9 studies (25.7%) respectively out of 35 studies reviewed. However, the determinant of socioeconomic and demographic statuses was not found to be significantly associated with adherence in studies related to income 9(47.4%), education 17(68.0%), employment/ occupational 10(58.8%), sex 27(77.1%), and age 25(71.4%). Conclusion The majority of the reviewed studies reported that there is no association between socio- demographic and economic variables and adherence to therapy. Whereas, some studies show that age of HIV patients (per year increasing) and sex (being male) were positively associated with adherence to ART. Among socio-economic factors, the available evidence does not provide conclusive support for the existence of a clear association with adherence to ART among HIV patients. There seems to be a positive trend between socioeconomic factors and adherence to ART in some of the reviewed studies.