Weight change by baseline BMI from three-year observational data: findings from the Worldwide Schizophrenia Outpatient Health Outcomes Database
Bibliographic record
Abstract
The aim was to explore weight and body mass index (BMI) changes by baseline BMI in patients completing three years of monotherapy with various first- and second-generation antipsychotics in a large cohort in a post hoc analysis of three-year observational data. Data were analyzed by antipsychotic and three baseline BMI bands: underweight/normal weight (BMI <25 kg/m²), overweight (25-30 kg/m²) and obese (>30 kg/m²). Baseline BMI was associated with subsequent weight change irrespective of the antipsychotic given. Specifically, a smaller proportion of patients gained ≥7% baseline bodyweight, and a greater proportion of patients lost ≥7% baseline bodyweight with increasing baseline BMI. For olanzapine (the antipsychotic associated with highest mean weight gain in the total drug cohort), the percentage of patients gaining ≥7% baseline weight was 45% (95% CI: 43-48) in the underweight/normal weight BMI cohort and 20% (95% CI: 15-27) in the obese BMI cohort; 7% (95% CI: 6-8) of the underweight/normal cohort and 19% (95% CI: 13-27) of the obese cohort lost ≥7% baseline weight. BMI has an association with the likelihood of weight gain or loss and should be considered in analyses of antipsychotic weight change.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".