Low Prevalence of Detectable HIV Plasma Viremia in Patients Treated With Antiretroviral Therapy in Burkina Faso and Mali
Bibliographic record
Abstract
BACKGROUND: Sub-Saharan Africa has seen dramatic increases in the numbers of people treated with antiretroviral therapy (ART). Although standard ART regimens are now universally applied, viral load measurement is not currently part of standard monitoring protocols in sub-Saharan Africa. METHODS: We describe the prevalence of inadequate virological response (IVR) to ART (viral load >or= 500 copies/mL) and identify factors associated with this outcome in 606 HIV-positive patients treated for at least 6 months. Recruitment took place in 7 hospitals and community-based sites in Bamako and Ouagadougou, and information was collected using medical charts and interviews. RESULTS: The overall prevalence of IVR in treatment-naive patients was 12.3% and 24.4% for pretreated patients. There were no differences in rates of IVR according to ART delivery sites and time on treatment. Patients living farther away [odds ratio (OR) = 2.48; 95% confidence interval (CI) 1.40 to 4.39], those on protease inhibitor or nucleoside reverse transcriptase inhibitor regimens (OR = 3.23; 95% CI 1.79 to 5.82) and those reporting treatment interruptions (OR = 2.36; 95% CI 1.35 to 4.15), had increased odds of IVR. Immune suppression (OR = 3.32, 95% CI 1.94 to 5.70) and poor self-rated health (OR = 2.00; 95% CI 1.17 to 3.41) were also associated with IVR. CONCLUSIONS: Sufficient expertise and dedication exist in public hospital and community-based programs to achieve rates of treatment success comparable to better-resourced settings.
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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 | 0.004 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".