Browsing by Author "Byaruhanga, Emmanuel"

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    Biomass fuel as a risk factor for esophageal squamous cell carcinoma: a systematic review and meta-analysis
    (Environmental Health, 2019) Okello, Samson; Akello, Suzan Joan; Dwomoh, Emmanuel; Byaruhanga, Emmanuel; Opio, Christopher Kenneth; Zhang, Ruyang; Corey, Kathleen E.; Muyindike, Winnie R.; Ocama, Ponsiano; Christiani, David D.
    The link between use of solid biomass fuel (wood, charcoal, coal, dung, and crop residues) for cooking and/or heating and esophageal squamous cell carcinoma (ESCC) is inconclusive. Objective: We systematically reviewed the literature and performed a meta-analysis to determine whether cooking fuel type influences esophageal squamous cell carcinoma. Methods: We searched MEDLINE, EMBASE, Web of Knowledge and Cochrane Database of Systematic Reviews for studies investigating cooking fuel and ESCC from 2000 until March 2019. We performed random effects meta-analysis stratified by the continent, World Bank’s country income classifications and fuel type and calculated pooled odds ratios and 95% CIs for the risk of esophageal squamous cell carcinoma in biomass fuel users compared with non-users. Results: Our analysis included 16 studies (all case-control) with 16,189 participants (5233 cases and 10,956 controls) that compared risk of ESCC among those using nonsolid fuels and biomass fuels. We found use of biomass fuel was associated with Esophageal squamous cell carcinoma with a pooled odds ratio (OR) 3.02 (95% CI 2.22, 4.11, heterogeneity (I2) = 79%). In sub-group analyses by continent, Africa (OR 3.35, 95%CI 2.34, 4.80, I2 = 73.4%) and Asia (OR 3.08, 95%CI 1.27, 7.43, I2 = 81.7%) had the highest odds of ESCC. Use of wood as fuel had the highest odds of 3.90, 95% CI 2.25, 6.77, I2 = 63.5%). No significant publication bias was detected. Conclusions: Biomass fuel is associated with increased risk of Esophageal squamous cell carcinoma. Biomass fuel status should be considered in the risk assessment for Esophageal squamous cell carcinoma.
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    Isolation of Genetically Diverse Marburg Viruses from Egyptian Fruit Bats
    (PLoS pathogens, 2009) Towner, Jonathan S.; Amman, Brian R.; Sealy, Tara K.; Carroll, Serena A. Reeder; Comer, James A.; Kemp, Alan; Swanepoel, Robert; Paddock, Christopher D.; Balinandi, Stephen; Khristova, Marina L.; Formenty, Pierre B. H.; Albarino, Cesar G.; Miller, David M.; Reed, Zachary D.; Kayiwa, John T.; Mills, James N.; Cannon, Deborah L.; Greer, Patricia W.; Byaruhanga, Emmanuel; Farnon, Eileen C.; Atimnedi, Patrick; Okware, Samuel; Mbidde, Edward Katongole; Downing, Robert; Tappero, Jordan W.; Zaki, Sherif R.; Ksiazek, Thomas G.; Nichol, Stuart T.; Rollin, Pierre E.
    In July and September 2007, miners working in Kitaka Cave, Uganda, were diagnosed with Marburg hemorrhagic fever. The likely source of infection in the cave was Egyptian fruit bats (Rousettus aegyptiacus) based on detection of Marburg virus RNA in 31/611 (5.1%) bats, virus-specific antibody in bat sera, and isolation of genetically diverse virus from bat tissues. The virus isolates were collected nine months apart, demonstrating long-term virus circulation. The bat colony was estimated to be over 100,000 animals using mark and re-capture methods, predicting the presence of over 5,000 virus-infected bats. The genetically diverse virus genome sequences from bats and miners closely matched. These data indicate common Egyptian fruit bats can represent a major natural reservoir and source of Marburg virus with potential for spillover into humans.
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    Post-discharge mortality among children under 5 years admitted with suspected sepsis in Uganda: a prospective multi-site study
    (medRxiv, 2023) Wiens, Matthew O.; Kumbakumba, Elias; Sherine, Sheila Oyella; Byaruhanga, Emmanuel; Barigye, Celestine
    Substantial mortality occurs after hospital discharge in children under 5 years old with suspected sepsis. A better understanding of its epidemiology is needed for effective interventions aimed at reducing child mortality in resource limited settings.
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    Prediction models for post-discharge mortality among under-five children with suspected sepsis in Uganda: A multicohort analysis
    (Public Library of Science, 2024-05) Wiens, Matthew O; Nguyen, Vuong; Bone, Jeffrey N.; Kumbakumba, Elias; Businge, Stephen; Tagoola, Abner; Sherine, Sheila Oyella; Byaruhanga, Emmanuel; Ssemwanga, Edward; Barigye, Celestine; Nsungwa, Jesca; Olaro, Charles; Ansermino, J. Mark; Kissoon, Niranjan; Singer, Joel; Larson, Charles P.; Lavoie, Pascal M; Dunsmuir, Dustin; Moschovis, Peter P.; Novakowski, Stefanie; Komugisha, Clare; Tayebwa, Mellon; Mwesigwa, Douglas; Knappett, Martina; West, Nicholas; Mugisha, Nathan Kenya; Kabakyenga, Jerome
    In many low-income countries, over five percent of hospitalized children die following hospital discharge. The lack of available tools to identify those at risk of post-discharge mortality has limited the ability to make progress towards improving outcomes. We aimed to develop algorithms designed to predict post-discharge mortality among children admitted with suspected sepsis. Four prospective cohort studies of children in two age groups (0–6 and 6–60 months) were conducted between 2012–2021 in six Ugandan hospitals. Prediction models were derived for six-months post-discharge mortality, based on candidate predictors collected at admission, each with a maximum of eight variables, and internally validated using 10-fold cross-validation. 8,810 children were enrolled: 470 (5.3%) died in hospital; 257 (7.7%) and 233 (4.8%) post-discharge deaths occurred in the 0-6-month and 6-60-month age groups, respectively. The primary models had an area under the receiver operating characteristic curve (AUROC) of 0.77 (95%CI 0.74–0.80) for 0-6-month-olds and 0.75 (95%CI 0.72–0.79) for 6-60-month-olds; mean AUROCs among the 10 cross-validation folds were 0.75 and 0.73, respectively. Calibration across risk strata was good: Brier scores were 0.07 and 0.04, respectively. The most important variables included anthropometry and oxygen saturation. Additional variables included: illness duration, jaundice-age interaction, and a bulging fontanelle among 0-6-month-olds; and prior admissions, coma score, temperature, age-respiratory rate interaction, and HIV status among 6-60-month-olds. Simple prediction models at admission with suspected sepsis can identify children at risk of post-discharge mortality. Further external validation is recommended for different contexts. Models can be digitally integrated into existing processes to improve peri-discharge care as children transition from the hospital to the community.