Clonidine as a Treatment of Behavioural Disturbances in Autism Spectrum Disorder: A Systematic Literature Review.
Bibliographic record
Abstract
BACKGROUND: Agitation and aggression are commonly cited reasons for psychiatry consultation for individuals diagnosed with autism spectrum disorder (ASD). While risperidone and aripiprazole do not carry Health Canada approval for management of ASD-associated irritability, both are used for this indication but are not universally effective and carry substantial risk of adverse effects. This necessitates use of off-label medications to assist in management of behavioral dysregulation. Clonidine, an alpha-2 receptor agonist, is approved in Canada for treatment of hypertension. The evidence base also supports its use for attention deficit/hyperactivity disorder (ADHD) and for tics in Tourette's disorder. This review focuses on examining the literature regarding clonidine as a treatment of challenging behaviours in the ASD population. METHOD: Systematic search of MEDLINE, EMBASE, and PsycINFO databases resulted in 540 unique records. Ten publications were relevant to this review. RESULTS: Two cross-over studies, one open-label case series, and seven case reports were identified. One of two controlled studies suggested benefit from clonidine versus placebo. Caregivers typically noted improvement in behaviour with clonidine versus baseline. Clonidine was generally well-tolerated. Sedation was the most consistently reported adverse effect. Despite being an anti-hypertensive medication, few discontinued clonidine due to hypotension or bradycardia. CONCLUSION: Clonidine has a limited evidence base for use in the management of behavioural problems in patients with ASD. Most evidence originates from case reports. Given the paucity of pharmacological options for addressing challenging behaviours in ASD patients, a clonidine trial may be an appropriate and cost-effective pharmaceutical option for this population.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".