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Record W3080202693 · doi:10.1111/jcpp.13305

Practitioner Review: Pharmacological treatment of attention‐deficit/hyperactivity disorder symptoms in children and youth with autism spectrum disorder: a systematic review and meta‐analysis

2020· review· en· W3080202693 on OpenAlexafffund
Rebecca Rodrigues, Meng‐Chuan Lai, Daniel Gorman, Evdokia Anagnostou, Péter Szatmári, Kelly K. Anderson, Stephanie H. Ameis

Bibliographic record

VenueJournal of Child Psychology and Psychiatry · 2020
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoHolland Bloorview Kids Rehabilitation HospitalCentre for Addiction and Mental HealthWestern University
FundersCanadian Institutes of Health Research
KeywordsMethylphenidateAtomoxetineAttention deficit hyperactivity disorderAutism spectrum disorderPsychologyPsychiatryModafinilImpulsivityStrictly standardized mean differenceRandomized controlled trialClinical psychologyMedicineAutismInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Clinically significant attention-deficit/hyperactivity disorder (ADHD) symptoms are common and impairing in children and youth with autism spectrum disorder(ASD). The aim of this systematic review and meta-analysis was to (a) evaluate the efficacy and safety of pharmacotherapy for the treatment of ADHD symptoms in ASD and (b) distil findings for clinical translation. METHODS: We searched electronic databases and clinical trial registries (1992 onwards). We selected randomized controlled trials conducted in participants <25 years of age, diagnosed with ASD that evaluated ADHD outcomes (hyperactivity/impulsivity and inattention) following treatment with stimulants (methylphenidate or amphetamines), atomoxetine, alpha-2 adrenergic receptor agonists, antipsychotics, tricyclic antidepressants, bupropion, modafinil, venlafaxine, or a combination, in comparison with placebo, any of the listed medications, or behavioral therapies. Data were pooled using a random-effects model. RESULTS: Twenty-five studies (4 methylphenidate, 4 atomoxetine, 1 guanfacine, 14 antipsychotic, 1 venlafaxine, and 1 tianeptine) were included. Methylphenidate reduced hyperactivity (parent-rated: standardized mean difference [SMD] = -.63, 95%CI = -.95,-.30; teacher-rated: SMD = -.81, 95%CI = -1.43,-.19) and inattention (parent-rated: SMD = -.36, 95%CI = -.64,-.07; teacher-rated: SMD = -.30, 95%CI = -.49,-.11). Atomoxetine reduced inattention (parent-rated: SMD = -.54, 95%CI = -.98,-.09; teacher/investigator-rated: SMD = -0.38, 95%CI = -0.75, -0.01) and parent-rated hyperactivity (parent-rated: SMD = -.49, 95%CI = -.76,-.23; teacher-rated: SMD = -.43, 95%CI = -.92, .06). Indirect evidence for significant reductions in hyperactivity with second-generation antipsychotics was also found. Quality of evidence for all interventions was low/very low. Methylphenidate was associated with a nonsignificant elevated risk of dropout due to adverse events. CONCLUSIONS: Direct pooled evidence supports the efficacy and tolerability of methylphenidate or atomoxetine for treatment of ADHD symptoms in children and youth with ASD. The current review highlights the efficacy of standard ADHD pharmacotherapy for treatment of ADHD symptoms in children and youth with ASD. Consideration of the benefits weighed against the limitations of safety/efficacy data and lack of data evaluating long-term continuation is undertaken to help guide clinical decision-making regarding treatment of co-occurring ADHD symptoms in children and youth with ASD.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.525
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0090.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.364
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations96
Published2020
Admission routes2
Has abstractyes

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