PSYCHOPHARMACOLOGY. Review of the Pharmacotherapy of Irritability of Autism
Bibliographic record
Abstract
Objective: To review the randomized controlled trial data regarding pharmacotherapy of irritability of autism. Method: A literature review was conducted using the MEDLine search terms: ‘autism ’ OR ‘autism spectrum disorder’ with the following limits: Randomized Controlled Trials (RCTs), human trials, English language. Additional articles were identified from reference information. Trials involving nutritional supplements, hormones or drugs not approved by either Health Canada or the US Food and Drug Administration (FDA) were excluded from analysis. Results: Twenty-three RCTs that met criteria were identified. The greatest number of RCTs involved risperidone, with six of seven placebo-controlled risperidone trials reporting statistically significant improvements on the primary outcome measure. Two aripiprazole RCTs and one olanzapine RCT reported statistically significant improvement in primary outcome measures. Haloperidol was superior to both clomipramine and placebo in a head-to-head crossover trial, while risperidone was superior to haloperidol for treatment of behavioural symptoms in a separate head-to-head trial. Clonidine, methylphenidate, valproate and levocarnitine monotherapy were superior to placebo in single RCTs, while adjunctive treatments cyproheptadine, pentoxifylline and topiramate were superior to placebo in small studies when given in combination with an antipsychotic. Adverse events from RCTs were summarized, including weight gain and metabolic effects, if available. Conclusion: The bulk of positive RCT evidence for the pharmacotherapy of irritability of autism pertains to FDA approved antipsychotics
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".