Cumulative exposure to ADHD medication is inversely related to hippocampus subregional volume in children
Bibliographic record
Abstract
BACKGROUND: Although there is some evidence for a normalization of brain structure following exposure to ADHD medication, literature on the effects of duration and dose of continued use on the brain is scarce. Here, we investigated the association between cumulative exposure to medication (range 1 week to 4.69 years) and cortical structures and subcortical volumes in a clinical sample of children with ADHD taking medication (n = 109). To the best of our knowledge, this is the first structural MRI study investigating the effects of cumulative exposure to medication on subregional volumes in children treated for ADHD. METHODS: Cumulative exposure to ADHD medication (CEM) was defined as the product of duration on medication (days) and dose (mg/day), yielding the area under the curve (total mg). Cortical thickness and surface area measurements (CIVET-1.1.12), and subcortical volumes in 51 regions (MAGeT-Brain) were analyzed using general linear modelling. RESULTS: Significant effects of CEM were found in two subregions of the left hippocampus, the CA1 (df = 95; q = 0.003) and the strata radiatum/lacunosum/moleculare (df = 95; q = 0.003). Specifically, higher CEM was associated with smaller volumes within these subregions. No effects of medication exposure were detected on cortical thickness or surface area. CONCLUSIONS: Although this study is cross-sectional, the results found within this sample of children show that prolonged ADHD medication use at higher doses is significantly associated with smaller hippocampus volumes in specific subregions. More research is required to determine whether these results are reproduced in other samples of children of ADHD, and further, whether these are beneficial or off-target effects of the medication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".