Children and adolescents on anti-retroviral therapy in Bulawayo, Zimbabwe: How many are virally suppressed by month six?
Bibliographic record
Abstract
Background: Zimbabwe is one of the countries in sub-Saharan Africa disproportionately affected by human immunodeficiency virus. In the “treat all” era, we assessed the gaps in routine viral load (VL) monitoring at six months for children (0-9 years) and adolescents (10-19 years) newly initiated on anti-retroviral therapy (ART) from January 2017 to September 2018 at a large tertiary hospital in Bulawayo. Methods: In this cohort study using secondary data, we considered first VL done within six to nine months of starting therapy as ‘undergoing VL test at six months’. We classified repeat VL≥1000 copies/ml despite enhanced adherence counselling as virally unsuppressed. Results: Of 295 patients initiated on ART, 196 (66%) were children and 99 (34%) adolescents. A total 244 (83%) underwent VL test at six months, with 161 (54%) virally suppressed, 52 (18%) unsuppressed and 82 (28%) with unknown status (due to losses in the cascade). Switch to second line was seen in 35% (18/52). When compared to children, adolescents were less likely to undergo a VL test at six months (73% versus 88%, p=0.002) and more likely to have an unknown VL status (40% versus 22%, p=0.001). Conclusion: At six months of ART, viral suppression was low and losses in the cascade high.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".