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Record W4391124873 · doi:10.1186/s13229-024-00585-6

Pharmacological and non-pharmacological interventions for irritability in autism spectrum disorder: a systematic review and meta-analysis with the GRADE assessment

2024· review· en· W4391124873 on OpenAlexaff
Hangnyoung Choi, Jae Han Kim, Hee Sang Yang, Jong Yeob Kim, Samuele Cortese, Lee Smith, Ai Koyanagi, Elena Dragioti, Joaquim Raduà, Paolo Fusar‐Poli, Jae Il Shin, Keun‐Ah Cheon, Marco Solmi

Bibliographic record

VenueMolecular Autism · 2024
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Center for Mental Health
KeywordsIrritabilityMedicinePsychological interventionMeta-analysisRisperidonePlaceboRandomized controlled trialAutism spectrum disorderAripiprazoleMEDLINEPsychiatryClinical psychologyAutismInternal medicinePhysical therapyAlternative medicineAnxietySchizophrenia (object-oriented programming)Pathology

Abstract

fetched live from OpenAlex

BACKGROUND: Numerous interventions for irritability in autism spectrum disorder (ASD) have been investigated. We aimed to appraise the magnitude of pharmacological and non-pharmacological interventions for irritability in ASD without any restrictions in terms of eligible interventions. METHODS: We systematically searched PubMed/MEDLINE, Scopus, and Web of Science until April 15, 2023. We included randomized controlled trials (RCTs) with a parallel design that examined the efficacy of interventions for the treatment of irritability in patients of any age with ASD without any restrictions in terms of eligible interventions. We performed a random-effects meta-analysis by pooling effect sizes as Hedges' g. We classified assessed interventions as follows: pharmacological monotherapy, risperidone plus adjuvant therapy versus risperidone monotherapy, non-pharmacological intervention, and dietary intervention. We utilized the Cochrane tool to evaluate the risk of bias in each study and the GRADE approach to assess the certainty of evidence for each meta-analyzed intervention. RESULTS: Out of 5640 references, we identified 60 eligible articles with 45 different kinds of interventions, including 3531 participants, of which 80.9% were males (mean age [SD] = 8.79 [3.85]). For pharmacological monotherapy, risperidone (Hedges' g - 0.857, 95% CI - 1.263 to - 0.451, certainty of evidence: high) and aripiprazole (Hedges' g - 0.559, 95% CI - 0.767 to - 0.351, certainty of evidence: high) outperformed placebo. Among the non-pharmacological interventions, parent training (Hedges' g - 0.893, 95% CI - 1.184 to - 0.602, certainty of evidence: moderate) showed a significant result. None of the meta-analyzed interventions yielded significant effects among risperidone + adjuvant therapy and dietary supplementation. However, several novel molecules in augmentation to risperidone outperformed risperidone monotherapy, yet from one RCT each. LIMITATIONS: First, various tools have been utilized to measure the irritability in ASD, which may contribute to the heterogeneity of the outcomes. Second, meta-analyses for each intervention included only a small number of studies and participants. CONCLUSIONS: Only risperidone, aripiprazole among pharmacological interventions, and parent training among non-pharmacological interventions can be recommended for irritability in ASD. As an augmentation to risperidone, several novel treatments show promising effects, but further RCTs are needed to replicate findings. Trial registration PROSPERO, CRD42021243965.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.038
metaresearch head score (Gemma)0.096
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.038
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.096
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0310.068
Bibliometrics0.0190.015
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0040.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.127
GPT teacher head0.454
Teacher spread0.327 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations32
Published2024
Admission routes1
Has abstractyes

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