Virological failure among people living with HIV receiving second-line antiretroviral therapy in Pune, India
Bibliographic record
Abstract
BACKGROUND: The number of people receiving second-line antiretroviral therapy (ART) has increased as global access to ART has expanded. Data on the burden and factors associated with second-line ART virologic failure (VF) from India remain limited. METHODS: We conducted cross-sectional viral load (VL) testing among adults (≥ 18 years) who were registered at a publicly funded ART center in western India between 2014 and 2015 and had received second-line ART for at least 6 months. Sociodemographic and clinical characteristics were abstracted from routinely collected programmatic data. Logistic regression evaluated factors associated with VF (defined as VL > 1000 copies/mL). RESULTS: , p < 0.0001), lower weight at first-line failure (49 vs 52 kg, p = 0.003), were more likely to have an opportunistic infection (17% vs 3%, p < 0.0001) and less likely to have optimal ART adherence (71% vs 87%, p = 0.005). In multivariable analysis, VF was associated with opportunistic infection (aOR, 4.84; 95% CI, 1.77-13.24), lower CD4 count (aOR 4.15; 95% CI, 1.98-8.71) and lower weight at first-line failure (aOR, 2.67; 95% CI, 1.33-5.34). CONCLUSIONS: We found second-line VF in about a sixth of participants in our setting, which was associated with nearly fivefold increased odds in the context of opportunistic infection. Weight could be a useful clinical indicator for second-line VF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".