Factors associated with virologic failure in HIV patients on antiretroviral therapy.
Bibliographic record
Abstract
OBJECTIVE: To determine the factors associated with virologic failure n HIV patients on antiretroviral treatment treated in a Colombian health institution. METHOD: This was a cross-sectional observational retrospective analytical study of HIV patients receiving antiretroviral treatment between 2007‑2020. Sociodemographic, pharmacological and clinical variables were collected, including viral load, adherence, and the medication possession ratio. For statistical analysis, crude and adjusted odds ratios and confidence intervals were obtained. RESULTS: In a population of 5,406 patients, the proportion of virologic failure was 16.7%. Moreover, in the adjusted model, an association was found between virologic failure and time on treatment greater than one year, medication possession ratio under 80%, failure to claim medications from the pharmacy due to dose omission or discontinuation, adherence under 85%, CD4 count under 500, total cholesterol levels above 201 mg/dL, high density lipoproteins under 39 mg/dL and presence of mycosis. CONCLUSIONS: In our cohort of HIV patients, short treatment periods, CD4 counts under 200, a low medication possession ratio, failure to timely claim medications from the pharmacy due to omission or discontinuation, and a lower degree of adherence were factors related to virologic failure.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".