Community-based ART distribution system can effectively facilitate long-term program retention and low-rates of death and virologic failure in rural Uganda
Bibliographic record
Abstract
BACKGROUND: Community-drug distribution point is a care model for stable patients in the community designed to make ART delivery more efficient for the health system and provide appropriate support to encourage long-term retention of patients. We examined program retention among ART program participants in rural Uganda, which has used a community-based distribution model of ART delivery since 2004. METHODS: We analyzed data of all patients >18 years who initiated ART in Jinja, Ugandan site of The AIDS Support Organization between January 1, 2004 and July 31, 2009. Participants attended clinic or outreach visits every 2-3 months and had CD4 cell counts measured every 6 months. Retention to care was defined as any patient with at least one visit in the 6 months before June 1, 2013. We then identified participants with at least one visit in the 6 months before June 1, 2013 and examined associations with mortality and lost-to-follow-up (LTFU). Participants with >4 years of follow up during August, 2012 to May, 2013 had viral load conducted, since no routine viral load testing was available. RESULTS: A total of 3345 participants began ART during 2004-2009. The median time on ART in June 2013 was 5.69 years. A total of 1335 (40 %) were residents of Jinja district and 2005 (60 %) resided in outlying districts. Of these, 2322 (69 %) were retained in care, 577 (17 %) died, 161 (5 %) transferred out and 285 (9 %) were LTFU. Factors associated with mortality or LTFU included male gender, [Adjusted Hazard Ratio (AHR) = 1.56; 95 % CI 1.28-1.9], CD4 cell count <50 cells/μL (AHR = 4.09; 95 % CI 3.13-5.36) or 50-199 cells/μL (AHR = 1.86; 95 % CI 1.46-2.37); ART initiation and WHO stages 3 (AHR = 1.35; 95 % CI 1.1-1.66) or 4 (AHR = 1.74; 95 % CI 1.23-2.45). Residence outside of Jinja district was not associated with mortality/LTFU (p value = 0.562). Of 870 participants who had VL tests, 756 (87 %) had VLs <50 copies/mL. CONCLUSION: Community-based ART distribution systems can effectively mitigate the barriers to program retention and result in good rates of virologic suppression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".