Traitement du gain de poids associé aux antipsychotiques au moyen de la metformine et d’une intervention sur les habitudes de vie
Bibliographic record
Abstract
Patients : Au total, 128 patients âges entre 18 et 45 ans ont participe a l’etude. Pour etre inclus, les patients devaient presenter un premier episode de schizophrenie diagnostique selon les criteres du Diagnostic and Statistical Manual of Mental Disorders – Fourth Edition (DSM-IV). Dans la premiere annee de traitement avec un des antipsychotiques cibles, soit la clozapine, l’olanzapine, la risperidone ou le sulpiride, les patients devaient presenter un gain de poids de plus de 10 %. Ils devaient avoir obtenu leur conge de l’hopital ou avoir ete suivis en clinique externe dans les 12 mois precedant leur inclusion dans l’etude afi n que leur poids et leur traitement antipsychotique soient clairement decrits. Ils devaient montrer une amelioration stable de leurs symptomes, soit un score egal ou inferieur a 60 points sur l’echelle Positive and Negative Symptom Scale (PANSS) et prendre un seul antipsychotique a une dose n’ayant pas ete modifi ee de plus de 25 % dans les trois mois precedant leur inclusion dans l’etude. Les auteurs ont utilise un gain de poids de plus de 10 % comme critere de selection, puisqu’un gain de poids de cette ampleur est souvent considere comme excessif. Les patients etaient places sous la supervision d’un parent ou d’un soignant qui surveillaient et decrivaient l’apport alimentaire, les activites physiques et la prise quotidienne du medicament en vue de determiner le degre d’observance au traitement.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".