Course and predictors of weight gain in people with first-episode psychosis treated with olanzapine or haloperidol
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Substantial weight gain is common with many atypical antipsychotics. AIMS: To evaluate the extent, time course and predictors of weight gain and its effect on study retention among people with first-episode psychosis treated with olanzapine or haloperidol. METHOD: Survival analysis assessed time to potentially clinically significant weight gain (> or =7%) and the effect of weight gain on study retention. Weight gain during the 2-year study was summarised using last-observation-carried-forward (LOCF), observed cases and study completion approaches. RESULTS: After 2 years of treatment, LOCF mean weight gain was 10.2 kg (s.d.=10.1) for olanzapine (n=131) and 4.0 kg (s.d.=7.3) for haloperidol (n=132); observed cases mean weight gain was 15.4 kg (s.d.=10.0) for olanzapine and 7.5 kg (s.d.=9.2) for haloperidol. Change in body mass index was significantly predicted only by treatment group (P < 0.0001). CONCLUSIONS: Olanzapine was associated with significantly greater weight gain than haloperidol, with both leading to greater weight gain than previously described.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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