MétaCan
Menu
← Back to cohort
Record W2804246040 · doi:10.1093/pch/pxy054.087

MANAGEMENT OF CHILDREN AND YOUTH WITH NEURODEVELOPMENTAL DISORDERS (NDDS) IN COMMUNITY SETTINGS PRIOR TO REFERRAL TO A TERTIARY PSYCHOPHARMACOLOGY CLINIC

2018· article· en· W2804246040 on OpenAlexaboutno aff
Imaan Kara, Melanie Penner

Bibliographic record

VenuePaediatrics & Child Health · 2018
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIrritabilityMedical prescriptionPediatricsPsychiatryAutism spectrum disorderSpectrum disorderAutismCognition

Abstract

fetched live from OpenAlex

Abstract BACKGROUND The use of second-generation antipsychotic (SGA) medications to alleviate irritability and aggression in children with autism spectrum disorder (ASD) has increased in the past decade. Although efficacious, SGAs are associated with cardiometabolic and neurologic risks. In 2011, the Canadian Alliance for Monitoring Effectiveness and Safety of Antipsychotics in Children (CAMESA) published a set of SGA monitoring guidelines to minimize these adverse effects (AEs). OBJECTIVES Primary: To determine how the introduction of the CAMESA Guidelines has impacted the frequency of clinical and laboratory investigations to monitor for AEs in children/youth with NDDs treated with SGAs. Secondary: (1) Describe the sample of children/youth referred to a tertiary psychopharmacology clinic; (2) Determine SGA prescription rates and treatment duration. DESIGN/METHODS A retrospective chart review was undertaken to compare rates of clinical monitoring of children/youth with NDDs treated with SGAs and referred to a tertiary psychopharmacology clinic before (2008- 2011) and after (2013–2016) publication of the CAMESA Guidelines. Children treated with SGAs were divided into three categories based on reports of clinical monitoring: (1) Any investigations complete, (2) No investigations complete, and (3) Not specified. A Fischer’s exact test was used to detect a statistically significant change in monitoring rates between the two time periods. Thoroughness of monitoring by CAMESA standards was also assessed. Descriptive statistics were used to address secondary objectives. RESULTS A total of 285 charts were reviewed (n=135 pre-CAMESA, n=150 post-CAMESA). The average age of children referred to the psychopharmacology clinic was 10.4 years (range 2–18 years), with ASD as the most prevalent diagnosis amongst the population. The most common reasons for referral were aggression and hyperactivity/impulsivity. Forty-one percent of referred children had been prescribed an SGA before arriving at the clinic, and the median duration of treatment was 17 months at the time of the first clinic visit. There is a nonsignificant difference (p=0.62) in the proportion of children on SGAs (n=48 pre-CAMESA, n=70 post-CAMESA) being monitored for AEs before and after publication of the guidelines. Monitoring rates pre- and post-CAMESA were 35% and 44%, respectively. Of the children monitored, only 33% in the pre-CAMESA period and 63% in the post-CAMESA period underwent comprehensive investigations. This again represents a nonsignificant difference (p=0.11) in thoroughness of monitoring between the two time periods. CONCLUSION We aim to provide novel insight into current SGA monitoring practices and emphasize the importance of health risk minimization when prescribing these medications. Given that SGA monitoring rates did not significantly improve after CAMESA guideline publication, and that less than half of children on SGAs underwent monitoring, we have identified a gap in standard of care provision. There is a need to undertake future studies to identify barriers to guideline uptake and implement interventions to address them.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.060
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.343
Teacher spread0.321 · 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venuePaediatrics & Child Health→Same topicAttention Deficit Hyperactivity Disorder→French-language works237,207→