Effects of Metformin on Spatial and Verbal Memory in Children with ASD and Overweight Associated with Atypical Antipsychotic Use
Bibliographic record
Abstract
OBJECTIVES: Studies in humans and rodents suggest that metformin, a medicine typically used to treat type 2 diabetes, may have beneficial effects on memory. We sought to determine whether metformin improved spatial or verbal memory in children with autism spectrum disorder (ASD) and overweight associated with atypical antipsychotic use. METHODS: ) concentrate on spatial and verbal memory in 51 youth with ASD, ages 6 through 17 years, who were taking atypical antipsychotic medications, had gained significant weight, and were enrolled in a trial of metformin for weight management. Phase 1 was a 16-week, randomized, double-blind, placebo-controlled, parallel-group comparison of metformin (500-850 mg given twice a day) versus placebo. During Phase 2, all participants took open-label metformin from week 17 through week 32. We assessed spatial and verbal memory using the Neuropsychological Assessment 2nd Edition (NEPSY-II) and a modified children's verbal learning task. RESULTS: No measures differed between participants randomized to metformin versus placebo, at either 16 or 32 weeks, after adjustment for multiple comparisons. Sixteen-week change in memory for spatial location on the NEPSY-II was nominally better among participants randomized to placebo. However, patterns of treatment response across all measures revealed no systematic differences in performance, suggesting that metformin had no effect on spatial or verbal memory in these children. CONCLUSIONS: Although further study is needed to support these null effects, the overall impression is that metformin does not affect memory in overweight youth with ASD who were taking atypical antipsychotic medications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".