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dc.contributor.authorAsiimwe, Stephen B.
dc.contributor.authorKanyesigye, Michael
dc.contributor.authorBwana, Bosco
dc.contributor.authorOkello, Samson
dc.contributor.authorMuyindike, Winnie
dc.date.accessioned2022-02-26T08:00:54Z
dc.date.available2022-02-26T08:00:54Z
dc.date.issued2016
dc.identifier.citationAsiimwe, S. B., Kanyesigye, M., Bwana, B., Okello, S., & Muyindike, W. (2015). Predictors of dropout from care among HIV-infected patients initiating antiretroviral therapy at a public sector HIV treatment clinic in sub-Saharan Africa. BMC infectious diseases, 16(1), 1-10.en_US
dc.identifier.urihttp://ir.must.ac.ug/xmlui/handle/123456789/1580
dc.description.abstractBackground: In sub-Saharan Africa (SSA), antiretroviral therapy (ART) can prolong life for HIV-infected patients. However, patients initiating ART, especially in routine treatment programs, commonly dropout from care either due to death or loss to follow-up. Methods: In a cohort of HIV-infected patients initiating ART at a public sector clinic in Uganda, we assessed predictors of dropout from care (a composite outcome combining death and loss to follow-up). From a large set of socio-demographic, clinical, and laboratory variables routinely collected atART initiation, we selected those predicting dropout at P <0.1 in unadjusted analyses for inclusion into a multivariable proportional hazards regression model. We then used a stepwise backward selection procedure to identify variables which independently predicted dropout at P <0.05. Results: Data from 5,057 patients were analyzed. The median age was 33 years (IQR 28 to 40) and 27.4 % had CD4+ T-cell counts <100 cells/μL at ART initiation. The median duration of follow-up was 24 months (IQR = 14 to 42, maximum follow-up = 64 months). Overall dropout was 26.9 % (established cumulative mortality = 2.3 %, loss to follow-up = 24.6 %), 5.6 % were transferred to other service providers, and 67.5 % were retained in care. A diagnosis of Kaposi’s sarcoma (hazard ratio (HR) = 3.3, 95 % CI 2.5 to 4.5); HIV-associated dementia (HR = 2.6, 95 % CI 1.5 to 4.6); history of cryptococcosis (HR = 2.2, 95 % CI 1.4 to 3.3); and reduced hemoglobin concentration (<11 g/dl versus ≥13.8 g/dl (HR = 1.9, 95 % CI 1.6 to 2.2) were strong predictors of dropout. Other independent predictors of dropout were: year of ART initiation; weight loss ≥10 %; reduced total lymphocyte count; chronic diarrhea; male sex; young age (≤28 years); and marital status. Conclusions: Among HIV-infected patients initiating ART at a public sector clinic in SSA, biological factors that usually predict death were especially predictive of dropout. As most of the dropouts were lost to follow-up, this observation suggests that many losses to follow-up may have died. Future studies are needed to identify appropriate interventions that may improve both individual-level patient outcomes and outcome ascertainment among HIV-infected ART initiators in this setting.en_US
dc.language.isoen_USen_US
dc.publisherBMC Infectious Diseasesen_US
dc.subjectHIV treatmenten_US
dc.subjectDropouten_US
dc.subjectLoss to follow-upen_US
dc.subjectAntiretroviral therapyen_US
dc.subjectSub-Saharan Africaen_US
dc.subjectPredictorsen_US
dc.titlePredictors of dropout from care among HIV-infected patients initiating antiretroviral therapy at a public sector HIV treatment clinic in sub-Saharan Africaen_US
dc.typeArticleen_US


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