Trends in clinical characteristics and outcomes of Pre-ART care at a large HIV clinic in Nairobi, Kenya: a retrospective cohort study. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Mecha, Jared; Kubo, Elizabeth; Nganga, Lucy; Muiruri, Peter; Njagi, Lilian; Mutisya, Immaculate; Odionyi, Justine; Ilovi, Syokau; Wambui, Mary; Githu, Christopher; Ngethe, Richard; Obimbo, Elizabeth; Ngumi, Zipporah
• Is Part Of: AIDS research and therapy. Volume 13:Issue 1(2016)
• Page Start: 1
• Page End: 11
• Publication Date: 2016-12
• Subjects: HIV -- Pre-ART -- Attrition -- Loss to follow up -- Predictors -- Risk factors -- Nairobi -- Kenya; AIDS (Disease) -- Periodicals; 616.9792005
• DOI: 10.1186/s12981-016-0122-y
• Languages: English
• ISSNs: 1742-6405

Abstract

Abstract Background The success of antiretroviral therapy in resource-scarce settings is an illustration that complex healthcare interventions can be successfully delivered even in fragile health systems. Documenting the success factors in the scale-up of HIV care and treatment in resource constrained settings will enable health systems to prepare for changing population health needs. This study describes changing demographic and clinical characteristics of adult pre-ART cohorts, and identifies predictors of pre-ART attrition at a large urban HIV clinic in Nairobi, Kenya. Methods We conducted a retrospective cohort analysis of data on HIV infected adults (≥15 years) enrolling in pre-ART care between January 2004 and September 2015. Attrition (loss to program) was defined as those who died or were lost to follow-up (having no contact with the facility for at least 6 months). We used Kaplan-Meier survival analysis to determine time to event for the different modes of transition, and Cox proportional hazards models to determine predictors of pre-ART attrition. Results Over the 12 years of observation, there were increases in the proportions of young people (age 15 to 24 years); and patients presenting with early disease (by WHO clinical stage and higher median CD4 cell counts), p = 0.0001 for trend. Independent predictors of attrition included: aHR (95% CI): male gender 1.98 (1.69–2.33), p = 0.0001; age 20–24 years 1.80 (1.37–2.37), p = 0.0001), or 25–34 years 1.22 (1.01–1.47), p = 0.0364; marital status single 1.55 (1.29–1.86), p = 0.0001) or divorced 1.41(1.02–1.95), p = 0.0370; urban residency 1.83 (1.40–2.38), p = 0.0001; CD4 count of 0–100 cells/µl 1.63 (1.003–2.658), p = 0.0486 or CD4 count >500 cells/µl 2.14(1.46–3.14), p = 0.0001. Conclusions In order to optimize the impact of HIV prevention, care and treatment in resource scarce settings, there is an urgent need to implement prevention and treatment interventions targeting young people and patients entering care with severe immunosuppression (CD4 cell counts <100 cells/µl). Additionally, care and treatment programmes should strengthen inter-facility referrals and linkages to improve care coordination and prevent leakages in the HIV care continuum.