Stimulant Withdrawal in a Child with Autism Spectrum Disorder and ADHD - A Case Report.
Bibliographic record
Abstract
OBJECTIVE: To consider whether the concepts of tolerance and withdrawal to stimulant medications apply to a preadolescent female, affected by autism spectrum disorder (ASD) and treated for associated attention-deficit/hyperactivity disorder (ADHD). METHODS: We describe the case history and review scientific English language literature pertaining to acute withdrawal effects associated with methylphenidate and amphetamine derivatives in children. RESULTS: An 11-year-old female with ASD and ADHD referred to our clinic experienced vomiting, headaches, and light sensitivity following abrupt discontinuation of methylphenidate; she subsequently presented with migraines and marked malaise immediately after a dose reduction in lisdexamfetamine. Evidence supports the notion that ADHD symptoms in children with ASD can be effectively treated with methylphenidate; however, beneficial effects are less robust relative to children with a primary ADHD diagnosis. Children affected by ASD are also more susceptible to adverse effects. Literature on withdrawal from stimulants in children is limited to case studies; in contrast, in the adult population more information is available, especially in adults with substance abuse disorders. Adults experiencing stimulant withdrawal often experience depression, fatigue, changes in appetite, and insomnia or hypersomnia. CONCLUSIONS: We argue that tolerance to stimulants was conceivably developing in this young female, and consequently discontinuation of methylphenidate and dose reduction of lisdexamfetamine resulted in withdrawal symptoms. Children with ASD are more sensitive to stimulant medications and we wonder whether this extends to an increased sensitivity to developing tolerance to stimulant medication. Clinicians ought to be vigilant about the emergence of symptomology suggestive of withdrawal phenomena following stimulant discontinuation.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".