Study of natural product adverse events in adult HIV‐infected patients in Canada
Bibliographic record
Abstract
INTRODUCTION: Many individuals living with HIV use natural health products (NHPs) in an effort to decrease medication side effects and to enhance overall well-being. METHODS: An active surveillance study of adult patients (≥ 18 years) with HIV was conducted between 2012 and 2014 to detect prescription drug and NHP use and associated adverse events (AEs) in the last month. RESULTS: Of the 167 participants, 85 (50.9%) took prescription medications only, three (1.8%) took NHPs only, 75 (44.9%) took NHPs and prescription medications concurrently, and four (2.4%) took neither. Patients who used both prescription drugs and NHPs concurrently were more than three times more likely to experience an AE compared with those who used prescription drugs only (OR, P = 0.003, 95% CI: 1.47-6.91). CONCLUSIONS: Increased AEs are reported in patients with HIV who combine NHPs and prescription medications, and no serious AEs were reported. Active surveillance was found to be feasible in this clinical setting.
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".