Prescription et délivrance raisonnées des IPP : patients, médecins et pharmaciens sont-ils prêts ?
Bibliographic record
Abstract
The rational prescription and dispensing of PPIs is a major public health issue. Nearly a quarter of the French population was concerned in 2019 by the prescription of PPIs. These latter drugs are prescribed unnecessarily in 80% (source HAS) of cases of co-prescription of a PPI with an NSAID. However, PPIs can have serious side effects when taken over the long term.To explore these bibliographical results and identify courses of action for a more rational use of PPIs, I conducted a study to obtain the vision of the three people most involved in the prescription of a PPI: the patient, the doctor and pharmacist.The main result obtained is that each of these actors holds a share of responsibility in this overconsumption of PPIs and that they each have a role to play in the deprescription of PPIs.The pharmacist could play a key role in this collective approach, both for informing the patient about the adverse effects and the conditions for taking these drugs and for triggering a reflection on the part of the patient with his doctor when the treatment is prolonged beyond the initial duration of 8 weeks.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".