Palatability, adherence and prescribing patterns of antiretroviral drugs for children with human immunodeficiency virus infection in Canada
Bibliographic record
Abstract
PURPOSE: To assess the impact of perceived palatability of antiretroviral drugs on adherence to therapy of children infected by human immunodeficiency virus and on prescribing patterns by their caring physicians. DESIGN: Two arms--retrospective chart review and a cross-sectional survey. SETTING: Tertiary-care pediatric human immunodeficiency virus clinic during a 17-year period. PARTICIPANTS: Children with human immunodeficiency virus infection and physicians actively caring for children with human immunodeficiency virus infection in seven provinces in Canada were surveyed regarding their perception of the palatability of 8-liquid and 15 non-liquid antiretroviral medications and its effect on drug selection. MAIN OUTCOME MEASURE: Effect of taste preferences of antiretroviral drugs on adherence to treatment by infected children and on drug selection by their caring physicians. RESULTS: Forty of 119 children (34%) refused at least once to an antiretroviral medication. In 5%, treatment was discontinued because of poor palatability. Ritonavir was the least palatable drug (50% of children; p = 0.01). Ritonavir use (OR 4.80 [95%CI 1.34-17.20]) and male gender (OR 7.25 [95%CI 2.30-22.90]) were independent predictors of drug discontinuation because of poor taste. Physicians also perceived liquid ritonavir as the least palatable (p = 0.01) and the most likely to be discontinued (p = 0.01). However, they commonly prescribed it as first-line therapy (p = 0.06). CONCLUSIONS: A third of children infected with human immunodeficiency virus fail to adhere to their treatment because of poor drug taste. Physicians are aware of that, but this does not prevent them from selecting the least palatable drugs as first-line therapy.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".