Retention on antiretroviral therapy during Universal Test and Treat implementation in Zomba district, Malawi: a retrospective cohort study
Bibliographic record
Abstract
INTRODUCTION: Since June 2016, the national HIV programme in Malawi has adopted Universal Test and Treat (UTT) guidelines requiring that all persons who test HIV positive will be referred to start antiretroviral therapy (ART). Although there is strong evidence from clinical trials that early initiation of ART leads to reduced morbidity and mortality, the impact of UTT on retention on ART in real-life programmatic settings in Africa is not yet known. METHODS: We conducted a retrospective cohort study in Zomba district, Malawi to compare ART outcomes of patients who initiated ART under 2016 UTT guidelines and those who started ART prior to rollout of UTT (pre-UTT). We analysed data from 32 rural and urban health facilities of various sizes. Cox proportional hazards modelling was used to determine the independent risk factors of attrition from ART at 12 months. All analyses were adjusted for clustering by health facility using a robust standard errors approach. RESULTS: Among 1492 patients (mean age 34.4 years, 933 (63%) female) who initiated ART during the study period, 501 were enrolled in the pre-UTT cohort and 911 during UTT. At 12 months, retention on ART in the UTT cohort was higher than in the pre-UTT cohort 83.0% (95% confidence interval (CI): 81.0% to 85.0%) versus 76.2% (95% CI 73.9% to 78.5%). Adolescents, aged 10 to 19 years (adjusted hazard ratio (aHR) 1.53; 95% CI 1.01 to 2.32), and women who were pregnant or breastfeeding at ART initiation (aHR 1.87; 95% CI 1.30 to 2.38) were at higher risk of attrition in the combined pre-UTT and UTT cohort. CONCLUSIONS: Retention on ART was nearly 6% higher after UTT introduction. Young adults and women who were pregnant or breastfeeding at the start of ART were at increased risk of attrition, emphasizing the need for targeted interventions for these groups to achieve the 90-90-90 UNAIDS targets in the UTT era.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".