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Record W2947538070 · doi:10.1093/pch/pxz066.097

98 Monitoring the Safety of Second Generation Antipsychotics in Children and Adolescents with Autism Spectrum Disorder

2019· article· en· W2947538070 on OpenAlexaboutno aff
Jillian Filliter, Mikayla Kerr, Sarah Shea, Isabel M. Smith, Jillian MacCuspie, Ann Hawkins, Theresa Fraboni

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
Fundersnot available
KeywordsIrritabilityMedicineAutism spectrum disorderPopulationPsychiatryAutismPediatricsClinical psychologyCognition

Abstract

fetched live from OpenAlex

Approximately 17.5% of youth with autism spectrum disorder (ASD) are treated with second-generation antipsychotics (SGAs). While SGAs have been found to reduce irritability and associated behaviours in youth with ASD, a range of side effects has been reported. Therefore, careful monitoring of youth taking these medications is imperative. However, as the core and associated symptoms of ASD can make medical procedures challenging, monitoring the safety of SGAs may be particularly difficult in this population. To date, there has been little investigation of how closely physicians monitor SGA side effects in youth with ASD or the barriers that they face in doing so. To begin to understand physicians’ current practices in SGA monitoring and the challenges of monitoring SGAs in youth with ASD. An online questionnaire that was completed by 31 specialist physicians serving children and adolescents with ASD in one region of Canada. Our survey examined physicians’ reports of ordering vs. completion of monitoring tasks recommended by the Canadian Alliance for Monitoring Effectiveness and Safety of Antipsychotic Medications in Children, as well as their perceptions of factors relevant to SGA safety monitoring in youth with ASD. Of the monitoring tasks queried, physicians were most likely to measure height, weight, and blood pressure at baseline and as part of ongoing follow-up. Waist circumference measurements and electrocardiograms (ECGs) were the monitoring tasks least often carried out at both time points. Fasting and non-fasting bloodwork were frequently not ordered at baseline, but were somewhat more likely to be ordered at follow-up. Neurological exams were attempted more often at baseline than at follow-up. As expected, physicians indicated that ECG and bloodwork were the procedures that youth with ASD have the most difficulty completing successfully. When asked their perspectives on factors that impede completion of these procedures, physicians identified youth distress, activity level, and refusal, as well as family anticipatory anxiety, previous failed attempts, and competing commitments, as the most significant barriers. Our results indicate inconsistent physician practices in ordering/completing SGA various monitoring tasks at baseline and follow-up. Further, our findings suggest that many youth with ASD struggle to complete successfully the medical procedures required for thorough SGA monitoring. Additional research aimed at supporting physicians in their monitoring of SGAs and youth with ASD and their families in successfully completing associated monitoring tasks is indicated.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.271
Teacher spread0.258 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2019
Admission routes1
Has abstractyes

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