Poor Adherence with Hypolipidemic Drugs: A Lost Opportunity
Bibliographic record
Abstract
All articles assessing adherence to hypolipidemic drugs were reviewed and categorized by patient population (clinical trial, unselected) and reported as rates of nonadherence and discontinuation. Overall, levels of discontinuation reported in clinical trials (6-31%) and lipid clinics (2-38%) are similar, with unselected populations consistently reporting higher rates (15-78%). Rates of nonadherence in clinical trials and lipid clinics also are comparable, with unselected populations having the highest rates. Across all settings, rates of discontinuation and nonadherence are consistently reported to be poorer with resins and niacin than with hydroxy-6-methylglutamate coenzyme A reductase inhibitors. Adherence to hypolipidemic agents appears to decrease in parallel with level of follow-up. Data evaluating mechanisms of poor adherence are limited. While the search for new, efficacious therapies must continue, efforts focused on improving adherence to proven therapy may have a greater overall impact on health than any single new agent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".