Atypical Antipsychotics for Irritability in Pediatric Autism: A Systematic Review and Network Meta-Analysis
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Bibliographic record
Abstract
OBJECTIVE: Irritability is common in pediatric autism spectrum disorder (ASD) patients. This can have major implications in child development, receptivity to behavioral therapy, as well as child and caregiver well-being. A systematic review and network meta-analysis were conducted to assess the efficacy and safety of atypical antipsychotics in treating irritability in these patients. METHODS: Studies were identified from Medline, Embase, and PsycINFO from inception to March 2018. The clinical trials database was reviewed. Studies were included if they were a double-blind, randomized controlled trial utilizing the Aberrant Behavior Checklist Irritability (ABC-I) to measure the efficacy of atypical antipsychotic monotherapy. Data extraction was carried out following the Preferred Reporting Items for Systematic Reviews and Meta-analyses for network meta-analysis guidelines. The main outcome was the reduction in irritability score using the ABC-I subscale from baseline. RESULTS: Eight trials comparing four interventions-risperidone, aripiprazole, lurasidone, and placebo in 878 patients, were included. Both risperidone and aripiprazole had significantly reduced ABC-I scores than placebo. Estimates of mean differences (95% credible intervals) were risperidone, -6.89 (-11.14, -2.54); aripiprazole, -6.62 (-10.88, -2.22); and lurasidone, -1.61 (-9.50, 6.23). Both risperidone and aripiprazole had similar safety. There were only eight studies included in the analysis, however, sample sizes were not small. Variance in reporting of adverse effects limited the quality of safety analysis. CONCLUSION: Risperidone and aripiprazole were the two best drugs, with comparable efficacy and safety in pediatric ASD patients. These two medications could be beneficial in improving irritability in these patients.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it