Effect of Instructions on the Use of HMG-CoA Reductase Inhibitors (Statins) on Patient Compliance:-Information on Rhabdomyolysis Provided by Pharmacists Working at Pharmacy Outlets-
Bibliographic record
Abstract
Concern about rhabdomyolysis,an adverse effect of 3-hydroxy-3-methylglutaryl (HMG)-CoA reductase inhibitors (statins),is considered to be a cause of poor compliance among patients taking them.In this study,we investigated the effect on drug compliance of providing patients with information on rhabdomyolysis as well as problems in the methods by which pharmacists and physicians provide such information.We conducted a questionnaire survey of pharmacists working at pharmacy outlets between September and October 2006,in which they were asked about patients expressing concern with respect to rhabdomyolysis,reduced compliance in patients due to such concern and other factors that adversely affected patient compliance.We received responses from 187 pharmacists which showed that many pharmacists had been asked questions about rhabdomyolysis by patients who were extremely worried about it.They also indicated that 2 factors causing concern about rhabdomyolysis and reducing drug compliance were“Patient ignorance concerning adverse effects”and“Pharmacist failure to provide adequate information on adverse effects”.These results suggest that it is important for pharmacists to effectively address patient concerns about adverse effects and provide them with information in an appropriate manner in order to reduce patient anxiety concerning medication.
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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 | 0.006 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".