MANAGEMENT OF CHILDREN AND YOUTH WITH NEURODEVELOPMENTAL DISORDERS (NDDS) IN COMMUNITY SETTINGS PRIOR TO REFERRAL TO A TERTIARY PSYCHOPHARMACOLOGY CLINIC
Bibliographic record
Abstract
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.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".