Clonidine and methylphenidate were effective for attention deficit hyperactivity disorder in children with comorbid tics
Bibliographic record
Abstract
TherapeuticsSeptember 1, 2002Clonidine and methylphenidate were effective for attention deficit hyperactivity disorder in children with comorbid ticsJ. Goldberg, MBJ. Goldberg, MBMcMaster University, Hamilton, Ontario, Canada (J.G.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/ACPJC-2002-137-2-070 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareFacebookTwitterLinkedInRedditEmail Source CitationThe Tourette’s Syndrome Study Group. Treatment of ADHD in children with tics. A randomized controlled trial. Neurology. 2002 Feb 26;58:527-36. https://pubmed.ncbi.nlm.nih.gov/11865128References1 Gadow KD, Sverd J, Sprafkin J, Nolan EE, Grossman S. Long-term methylphenidate therapy in children with comorbid attention-deficit hyperactivity disorder and chronic multiple tic disorder. Arch Gen Psychiatry. 1999;56:330-6. [PMID: 10197827] Google Scholar2 Castellanos FX, Giedd JN, Elia J, et al. Controlled stimulant treatment of ADHD and comorbid Tourette’s syndrome: effects of stimulant and dose. J Am Acad Child Adolesc Psychiatry. 1997;36:589-96. [PMID: 9136492] Google Scholar3 Swanson JM, Flockhart D, Udrea D, et al. Clonidine in the treatment of ADFHD: questions about safety and efficacy. J Adolesc Psychopharmacol. 1995;5:301-4. [PMID: 9136492] Google Scholar Author, Article, and Disclosure InformationAffiliations: McMaster University, Hamilton, Ontario, Canada (J.G.) PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails September 1, 2002Volume 137, Issue 2Page: 70 ePublished: 9 March 2020 Issue Published: September 1, 2002 Copyright & PermissionsCopyright © 2002 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.009 | 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".