Original Research Risk of Weight Gain Associated with Antipsychotic Treatment: Results From the Canadian National Outcomes Measurement Study in Schizophrenia
Why this work is in the frame
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Bibliographic record
Abstract
Background: Antipsychotic-induced weight gain occurs in a substantial percentage of treated persons. There re-mains a paucity of naturalistic data that describe relative weight-gain liability with the available novel atypical antipsychotics (NAPs). This investigation describes comparative NAP-induced weight gain in a prospective naturalistic cohort of persons with schizophrenia and related psychotic disorders. Methods: The Canadian National Outcomes Measurement Study in Schizophrenia (CNOMSS) is an ongoing prospective, longitudinal, naturalistic study involving 32 academic and community sites across Canada. Persons with DSM-IV–defined schizophrenia, schizophreniform or schizoaffective disorder, and psychosis not otherwise specified were consecutively enrolled. The overarching objectives of this initiative were to collect and compare global effectiveness, tolerability, safety, and humanistic outcomes in persons receiving commercially available NAPs in Canada. This analysis reports only weight change with the respective NAPs. Other outcomes were re-ported in separate companion papers. Results: A spectrum of weight-gain liability was noted with quetiapine (QUE) (mean 7.55 kg, SD 9.20; P = 0.28), olanzapine (OLZ) (mean 3.72 kg, SD 0.56; P = 0.15), and risperidone (RIS) (mean 1.62 kg, SD 7.72; P = 0.43). Categorically defined weight gain (that is, over 7 % of baseline weight) was observed in 55.6 % of QUE pa-tients, 24.1 % of OLZ patients, and 23.7 % of RIS patients. Adjusting for demographic and disease-specific con-
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.068 | 0.090 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it