Clinical Practice Pathways for Evaluation and Medication Choice for Attention-Deficit/Hyperactivity Disorder Symptoms in Autism Spectrum Disorders
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Hyperactivity, impulsivity, and inattention (referred to as "ADHD [attention-deficit/hyperactivity disorder] symptoms") occur in 41% to 78% of children with autism spectrum disorders (ASDs). These symptoms often affect quality of life, interfering with learning or interventions that target primary ASD symptoms. This practice pathway describes the guidelines for evaluation and treatment of children and adolescents with ASD and comorbid ADHD symptoms. METHODS: Current research in this area is limited, and, therefore, these recommendations are based on a systematic literature review and expert consensus in the Autism Speaks Autism Treatment Network Psychopharmacology Committee. RESULTS: The recommended practice pathway includes the Symptom Evaluation Pathway for systematic assessment of ADHD symptoms across settings; examination for comorbid sleep, medical, or psychiatric comorbidities that may contribute to symptoms; and evaluation of behavioral interventions that may ameliorate these symptoms. For children for whom medication is being considered to target the ADHD symptoms, the medication choice pathway provides guidance on the selection of the appropriate agent based on a review of available research, assessment of specific advantages and disadvantages of each agent, and dosing considerations. CONCLUSIONS: These recommendations provide a framework for primary care providers treating children who have ASD and ADHD symptoms. Our systematic review of the current evidence indicates the need for more randomized controlled trials of the medications for ADHD symptoms in ASD. There will also be a need for studies of the effectiveness of these practice pathways in the future.
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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 | 0.071 | 0.236 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".