Metformin for Prevention of Weight Gain and Insulin Resistance with Olanzapine: A Double-Blind Placebo-Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To assess whether metformin prevents body weight gain (BWG) and metabolic dysfunction in patients with schizophrenia who are treated with olanzapine. METHOD: Forty patients taking olanzapine (10 mg daily) were randomly allocated to a metformin (n = 20; 850 to 1700 mg daily) or placebo (n = 20) group in a 14-week double-blind study. Waist circumference (WC), BWG, body mass index (BMI) fasting glucose, insulin, and lipids were evaluated at baseline and at Weeks 7 and 14 of treatment. RESULTS: At Week 14, BWG (kg) was similar in the metformin group (5.5 kg) and the placebo group (6.3 kg), P = 0.4. There were no differences between the changes in BMI, WC, glucose, insulin, insulin resistance index (HOMA-IR), and plasma lipid levels observed in the treatment group and the placebo group; however, glucose levels decreased significantly after metformin administration (P = 0.02). The HOMA-IR decreased significantly in both groups, but 3 subjects from the placebo group developed fasting glucose levels greater than 5 mmol/L. After taking metformin, triglyceride levels increased, but the cholesterol profile improved significantly. CONCLUSIONS: Metformin did not prevent olanzapine-induced BWG. While some lipid parameters worsened during placebo, the HOMA-IR improved in both the placebo and the metformin groups. Carbohydrate metabolism impairment was not systematically observed during short-term olanzapine administration.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".