Browsing by Author "Eustasius Musenge"
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Item Corrigendum Predicting Colorectal Cancer Recurrence and Patient Survival Using Supervised Machine Learning Approach A South African PopulationBased Study Frontiers in Public Health 2021 9 694306 103389fpubh2021694306Okechinyere Achilonu; June Fabian; Brandon Bebington; Elvira Singh; Gideon Nimako; M. J. C. Eijkemans; Eustasius MusengeItem Digital delivery of behavioural activation therapy to overcome depression and facilitate social and economic transitions of adolescents in South Africa (the DoBAt study): protocol for a pilot randomised controlled trial(2022-12-05) Bianca D Moffett; Julia R Pozuelo; Alastair van Heerden; Heather A O'Mahen; Michelle Craske; Tholene Sodi; Crick Lund; Kate Orkin; Emma J Kilford; Sarah-Jayne Blakemore; Mahreen Mahmud; Eustasius Musenge; Meghan Davis; Zamakhanya Makhanya; Tlangelani Baloyi; Daniel Mahlangu; Gabriele Chierchia; Sophie L Fielmann; F Xavier Gómez-Olivé; Imraan Valodia; Stephen Tollman; Kathleen Kahn; Alan SteinIntroduction Scalable psychological treatments to address depression among adolescents are urgently needed. This is particularly relevant to low-income and middle-income countries where 90% of the world’s adolescents live. While digital delivery of behavioural activation (BA) presents a promising solution, its feasibility, acceptability and effectiveness among adolescents in an African context remain to be shown. Methods and analysis This study is a two-arm singleblind individual-level randomised controlled pilot trial to assess the feasibility, acceptability and initial efficacy of digitally delivered BA therapy among adolescents with depression. The intervention has been coproduced with adolescents at the study site. The study is based in the rural northeast of South Africa in the Bushbuckridge subdistrict of Mpumalanga province. A total of 200 adolescents with symptoms of mild to moderately severe depression on the Patient Health Questionnaire Adolescent Version will be recruited (1:1 allocation ratio). The treatment group will receive BA therapy via a smartphone application (the Kuamsha app) supported by trained peer mentors. The control group will receive an enhanced standard of care. The feasibility and acceptability of the intervention will be evaluated using a mixed methods design, and signals of the initial efficacy of the intervention in reducing symptoms of depression will be determined on an intention-to-treat basis. Secondary objectives are to pilot a range of cognitive, mental health, risky behaviour and socioeconomic measures; and to collect descriptive data on the feasibility of trial procedures to inform the development of a further larger trial.Item Effect of a Mentor Mother Programme on retention of mother-baby pairs in HIV care: A secondary analysis of programme data in UgandaJude Igumbor; Joseph Ouma; Kennedy Otwombe; Eustasius Musenge; Felix Anyanwu; Tariro Basera; M Mbule; E Scheepers; K SchmitzItem A machine learning approach towards assessing consistency and reproducibility an application to graft survival across three kidney transplantation erasOkechinyere Achilonu; G Obaido; B Ogbuokiri; K Aruleba; Eustasius Musenge; June FabianItem Measurement of kidney function in Malawi, South Africa, and Uganda: a multicentre cohort study(2022) June Fabian; Robert Kalyesubula; Joseph Mkandawire; Christian Holm Hansen; Dorothea Nitsch; Eustasius Musenge; Wisdom P Nakanga; Josephine E Prynn; Gavin Dreyer; Tracy Snyman; Billy Ssebunnya; Michele Ramsay; Liam Smeeth; Stephen Tollman; Saraladevi Naicker; Amelia Crampin; Robert Newton; Jaya A George; Laurie TomlinsonBackground The burden of kidney disease in many African countries is unknown. Equations used to estimate kidney function from serum creatinine have limited regional validation. We sought to determine the most accurate way to measure kidney function and thus estimate the prevalence of impaired kidney function in African populations. Methods We measured serum creatinine, cystatin C, and glomerular filtration rate (GFR) using the slope-intercept method for iohexol plasma clearance (mGFR) in population cohorts from Malawi, Uganda, and South Africa. We compared performance of creatinine and cystatin C-based estimating equations to mGFR, modelled and validated a new creatinine-based equation, and developed a multiple imputation model trained on the mGFR sample using age, sex, and creatinine as the variables to predict the population prevalence of impaired kidney function in west, east, and southern Africa. Findings Of 3025 people who underwent measured GFR testing (Malawi n=1020, South Africa n=986, and Uganda n=1019), we analysed data for 2578 participants who had complete data and adequate quality measurements. Among 2578 included participants, creatinine-based equations overestimated kidney function compared with mGFR, worsened by use of ethnicity coefficients. The greatest bias occurred at low kidney function, such that the proportion with GFR of less than 60 mL/min per 1·73 m² either directly measured or estimated by cystatin C was more than double that estimated from creatinine. A new creatinine-based equation did not outperform existing equations, and no equation, including the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2021 race-neutral equation, estimated GFR within plus or minus 30% of mGFR for 75% or more of the participants. Using a model to impute kidney function based on mGFR, the estimated prevalence of impaired kidney function was more than two-times higher than creatinine-based estimates in populations across six countries in Africa. Interpretation Estimating GFR using serum creatinine substantially underestimates the individual and populationlevel burden of impaired kidney function in Africa with implications for understanding disease progression and complications, clinical care, and service provision. Scalable and affordable ways to accurately identify impaired kidney function in Africa are urgently needed.Item Pancreatic cancer mortality in South Africa A casecontrol studyMandlakayise Nhleko; Ijeoma Edoka; Eustasius MusengeItem Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processingMichael Mapundu; Chodziwadziwa Kabudula; Eustasius Musenge; V Olago; Turgay Celik