Les antipsychotiques injectables à action prolongée: Avis d'experts de l'Association des médecins psychiatres du Québec
Bibliographic record
Abstract
OBJECTIVE: To present points of agreement and disagreement about antipsychotics. Since the appearance of 2nd generation long-acting antipsychotics (LAA), and given the high frequency of noncompliance with antipsychotics in psychotic disorders, LAAs have attracted more interest in psychiatric literature. However,their use is suboptimal, globally, and is also subject to significant national disparities. ln this context,the Association des médecins psychiatres du Québec (AMPQ) has asked for a review of the evidence concerning LAA efficiency and tolerance, and has called for consensual c1inical reflection on the benefits and obstacles of prescribing them, as weil as potential solutions, including administrative and judiciary dimensions. METHODS: The AMPQ established an expert committee, from 4 Quebec universities, which was responsible for preparing the review paper. The committee intended to appropriately provide c1inicians with the different aspects of LAA use. The committee produced a qualitative and selective review. RESULTS: Mean LAA prescription rates observed in Canada are around 6% and data to confirm this are scarce. A 15% to 25% rate could be suggested. CONCLUSION: The committee has submitted the Quebec long-acting antipsychotic algorithm (QAAPAPLE, derived from the French acronym) as a result of the consensus reached by the 4 university psychiatry departments.
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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 | 0.035 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".