Hepatitis B vaccination status among patients with end-stage kidney disease on haemodialysis in Ethiopia: a multi-center cross-sectional study.

BACKGROUND: Chronic kidney disease patients, especially those on hemodialysis, are at increased risk of developing hepatitis B virus (HBV) infection. Guidelines suggest that all patients with chronic kidney disease patients should be vaccinated against HBV, but these guidelines are sub-optimally implemented. Notably, there is a lack of studies in Ethiopia examining the hepatitis B vaccination status among patients with end-stage renal disease. OBJECTIVE: To assess the vaccination status of hepatitis B and associated factors among people with end-stage renal disease who were on hemodialysis. METHODS: A multi-center cross-sectional observational study was conducted in six randomly selected dialysis centers in Ethiopia, from May 2023 to September 2023. Logistic regression analysis was used to evaluate factors associated with vaccination status. A person is considered to be vaccinated against hepatitis B if he/ she has taken at least one dose of HBV. Vaccination status was determined by patient's recall and verification from medical record. RESULTS: Only 16% of patients with end-stage renal disease on hemodialysis were vaccinated against hepatitis B virus (16.6%; with CI = 12.18, 21.83), of which 30% had received one dose, 57.5% had two doses, 12.5% had three doses, and only five had a booster dose. Post-secondary education (AOR = 5.47; 95% CI = 1.41, 21.2; P < 0.014) and dialysis for more than three years (AOR = 19.75; 95% CI = 4.06, 96.1; P < 0.001) were significant factors associated with having received hepatitis B vaccination. CONCLUSION: Only a small minority of Ethiopian hemodialysis patients have received hepatitis B vaccination. The level of education of patients and the duration of time on dialysis were significant associated factors that affected the vaccination status of patients with end-stage renal disease. So, strong intervention is needed according to the identified factors to raise the vaccination status of patients.

A retrospective analysis of the clinical profile and factors associated with mortality and poor hospital outcomes in adult Guillain-Barre syndrome patients.

Guillain-Barré syndrome (GBS) is an acute autoimmune polyneuropathy with substantial geographic variations in demography, antecedent events, clinical manifestations, electrophysiological sub-types, diagnostic findings, treatment modalities, and prognostic indicators. However, there is limited contemporary data on GBS patient profiles and prognostic factors from low-resource settings like Ethiopia. The objective of this study is to investigate the clinical profile, factors associated with mortality, and hospital outcomes among GBS patients admitted to Tikur Anbessa Specialized Hospital (TASH) in Addis Ababa, Ethiopia. A retrospective cross-sectional study was conducted among 60 GBS patients admitted to TASH from January 2018 to December 2022. Data on demographics, clinical features, treatments, complications, and outcomes were extracted from medical records. Bivariate and multivariate logistic regression analyses identified factors associated with mortality and poor hospital outcomes. The cohort had a mean age of 28.5 years, with 76.7% aged 14-34 years. Males comprised 61.7% of cases. Ascending paralysis (76.7%) was the predominant presentation. Absent or reduced reflexes were seen in 91.7% of patients. The most common antecedent event was gastroenteritis (26.7%), followed by upper respiratory tract infection (URTI) (15%) and vaccination (11.7%). The mean interval from symptom onset to hospital presentation was 8.77 days, and the peak symptom severity was 4.47 days. The axonal variant (75.5%) was the most common subtype, followed by the demyelinating variant (24.5%). Intravenous immunoglobulin was administered to 41.7% of patients. Respiratory failure requiring invasive mechanical ventilator (MV) support occurred in 26.7% of cases. The mortality rate was 10%, with mechanical ventilation being the only factor significantly associated with mortality (95% CI 2.067-184.858; P < 0.010). At discharge, 55% had a good outcome, and 45% had a poor outcome, according to the Hughes Functional Disability Scale (HFDS). Mechanical ventilation (AOR 0.024, 95% CI 0.001-0.607) and a GBS disability score > 3 (AOR 0.106, 95% CI 0.024-0.467) were factors significantly associated with poor hospital outcomes. GBS in this cohort primarily affected individuals of young age, commonly preceded by gastroenteritis and characterized by a high frequency of the axonal variant. Mechanical ventilation was found to be significantly linked to mortality. Alongside mechanical ventilation requirements, severe disability upon presentation emerged as a crucial determinant of poor outcomes upon discharge, underscoring the importance of early identification of high-risk patients and prompt interventions.

Factors Associated with COVID-19 Severity Among Kidney Transplant and Non-Kidney Transplant Patients at St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia.

Background: The COVID-19 epidemic is a rapidly shifting situation that has resulted in significant regulatory reforms and widespread initiatives to deal with the initial crisis and its effects. The COVID-19 pandemic has had a significant impact on transplantation activities. The COVID-19 pandemic has caused various important challenges in the kidney transplant industry. Objective: To identify the factors influencing COVID-19 severity in kidney transplant and non-kidney transplant patients at St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia. Methods: A comparative cross-sectional study was conducted. This study included 364 patients (182 kidney transplants and 182 non-kidney transplants). A systematic random sampling was used to select the respondents. Professional nurses collected data for this study using a data extraction tools. Data were analyzed by using SPSS version 25 software. A multivariable logistic regression analysis was performed to identify the association between independent variables and COVID-19 severity with adjusted odds ratio (AOR), and 95% CI for AOR and P-value for testing significance. Results: This study included 364 patients. Off the total, 34.1% developed severe COVID-19. In Multivariable logistic regression analysis, patients with 60 years and above age groups (AOR = 4.73; 95% CI: 1.86, 12.02), aged 40-59 years (AOR = 2.70; 95% CI: 1.17, 6.22), chest congestion (AOR = 4.49; 95% CI: 2.37, 8.50), history of muscle or body aches (AOR = 0.47; 95% CI: 0.22, 0.99) shortness of breath (AOR = 3.03; 95% CI: 1.36, 6.74), changed or lost sense of taste or smell (AOR = 2.77; 95% CI: 1.34, 5.71), and muscle pain (AOR = 3.05; 95% CI: 1.40, 6.65) were significant variables associated with COVID-19 severity after adjusting for other variables. Conclusion: The study revealed that 34.1% of patients had severe COVID-19. The majority of these patients underwent non-kidney transplants. Age groups and symptoms, such as chest congestion, shortness of breath, changed or lost sense of taste or smell, and muscle pain, were significant predictors of COVID-19 disease severity.

Classification of imbalanced data using machine learning algorithms to predict the risk of renal graft failures in Ethiopia.

INTRODUCTION: The prevalence of end-stage renal disease has raised the need for renal replacement therapy over recent decades. Even though a kidney transplant offers an improved quality of life and lower cost of care than dialysis, graft failure is possible after transplantation. Hence, this study aimed to predict the risk of graft failure among post-transplant recipients in Ethiopia using the selected machine learning prediction models. METHODOLOGY: The data was extracted from the retrospective cohort of kidney transplant recipients at the Ethiopian National Kidney Transplantation Center from September 2015 to February 2022. In response to the imbalanced nature of the data, we performed hyperparameter tuning, probability threshold moving, tree-based ensemble learning, stacking ensemble learning, and probability calibrations to improve the prediction results. Merit-based selected probabilistic (logistic regression, naive Bayes, and artificial neural network) and tree-based ensemble (random forest, bagged tree, and stochastic gradient boosting) models were applied. Model comparison was performed in terms of discrimination and calibration performance. The best-performing model was then used to predict the risk of graft failure. RESULTS: A total of 278 completed cases were analyzed, with 21 graft failures and 3 events per predictor. Of these, 74.8% are male, and 25.2% are female, with a median age of 37. From the comparison of models at the individual level, the bagged tree and random forest have top and equal discrimination performance (AUC-ROC = 0.84). In contrast, the random forest has the best calibration performance (brier score = 0.045). Under testing the individual model as a meta-learner for stacking ensemble learning, the result of stochastic gradient boosting as a meta-learner has the top discrimination (AUC-ROC = 0.88) and calibration (brier score = 0.048) performance. Regarding feature importance, chronic rejection, blood urea nitrogen, number of post-transplant admissions, phosphorus level, acute rejection, and urological complications are the top predictors of graft failure. CONCLUSIONS: Bagging, boosting, and stacking, with probability calibration, are good choices for clinical risk predictions working on imbalanced data. The data-driven probability threshold is more beneficial than the natural threshold of 0.5 to improve the prediction result from imbalanced data. Integrating various techniques in a systematic framework is a smart strategy to improve prediction results from imbalanced data. It is recommended for clinical experts in kidney transplantation to use the final calibrated model as a decision support system to predict the risk of graft failure for individual patients.

Prevalence of cytopenias in both HAART and HAART naïve HIV infected adult patients in Ethiopia: a cross sectional study.

BACKGROUND: In individuals infected with HIV, hematological abnormalities are common and are associated with increased risk of disease progression and death. However, the profile of hematological abnormalities in HIV infected adult patients is not known in Ethiopia. Thus, the aim of this study was to assess the hematological manifestations of HIV infection and to identify the factors associated with cytopenias in both HAART and HAART naïve HIV infected adult patients in Ethiopia. METHOD: We conducted a cross-sectional quantitative study of HIV-infected adult patients attending the ART follow-up clinic of Jimma University Specialized Hospital in Jimma, Ethiopia, from July 2012 to September 2012. We used a structured questionnaire to collect socio-demographic and clinical information. After interviewing, 4 ml of venous blood was drawn from each study subject for hematologic and immunologic parameters. RESULT: The prevalence of anemia, leucopenia, thrombocytopenia and lymphopenia among the study individuals were 51.5%, 13%, 11.1% and 5% respectively. Presence of opportunistic infection (p = 0.001), use of CPT (p = 0.04) and CD4 count < 200 cells/µl (p = 0.002) were associated with an increased risk of anemia. CONCLUSION: Hematologic abnormalities were common in HIV infected adult patients. Of the cytopenias anemia was the most common. Use of CPT was independently associated with increased risk of anemia and leucopenia. Therefore, large scale and longitudinal studies, giving emphasis on the association of CPT and cytopenia, are recommended to strengthen and explore the problem in depth.