Objective: To determine the effectiveness of the Metropolitan Atlanta community adolescent rapid testing initiative (MACARTI) intervention relative to standard of care (SOC), in achieving early diagnosis, linkage, and retention among HIV-infected youth ages 18-24 years.
Design: MACARTI was a pilot single-center, prospective, nonrandomized study.
Methods: MACARTI combined nontraditional venue HIV testing, motivational interviewing, and case management. We collected demographic, clinical variables and calculated linkage and appointment adherence rates. We obtained SOC data from an adolescent HIV clinic. Longitudinal data were analyzed using inverse propensity treatment-weighted linear growth models; medians, interquartile ranges (IQR), means, and 95% confidence intervals are provided.
Results: MACARTI screened 435 participants and identified 49 (11.3%) HIV infections. The SOC arm enrolled 49 new HIV-infected individuals. The 98 participants, (49 in each arm) were: 85% men; 91% Black; mean age = 21 years (SD : 1.8). Overall, 63% were linked within 3 months of diagnosis; linkage was higher for MACARTI compared to SOC (96 vs. 57%, P < 0.001). Median linkage time for MACARTI participants compared to SOC was 0.39 (IQR : 0.20-0.72) vs. 1.77 (IQR : 1.12-12.65) months (P < 0.001). MACARTI appointment adherence was higher than SOC (86.1 vs. 77.2%, P = 0.018). In weight-adjusted models, mean CD4 T-cell counts increased and mean HIV-1 RNA levels decreased in both arms over 12 months, but the differences were more pronounced in the MACARTI arm.
Conclusion: MACARTI successfully identified and linked HIV-infected youth in Atlanta, USA. MACARTI may serve as an effective linkage and care model for clinics serving HIV-infected youth.
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http://dx.doi.org/10.1097/QAD.0000000000001512 | DOI Listing |
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5Department of Medicine, Medical College of Georgia at Augusta University, Augusta, GA.
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Infectious Diseases Institute (IDI), College of Health Sciences, Makerere University, Kampala, Uganda.
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Statistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Clin Biomech (Bristol)
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