Adherence to Antipsychotic Adverse Effect Monitoring Among a Referred Sample of Children with Intellectual Disabilities
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Despite frequent use of antipsychotic medications to target severe behavioral problems among children with intellectual disabilities (ID), there is little information as to the extent to which adverse effect monitoring is in place for this population. The aim of this pilot study was to determine the extent to which monitoring for adverse effects was documented in health records of a cohort of children with ID who had been prescribed antipsychotic medication. METHODS: Data were available on all children referred to a mental health clinic at a children's hospital in Canada who had ID and behavioral difficulties with intake appointments between September 1, 2016 and November 30, 2017. Charts of all those on antipsychotic medications were reviewed for a 12-week period to determine the extent to which adverse effect monitoring was documented using the parameters stipulated by the Canadian Alliance for Monitoring Effectiveness and Safety of Antipsychotics in Children (CAMESA), including laboratory, anthropometric, and neurological measures. RESULTS: The database was composed of 47 patients of whom 25 were on antipsychotics (56% boys; mean age 13 [SD 3] years). The most commonly used antipsychotic was risperidone (48%). The extent of adherence to the guidelines was (1) 96% for weight, height, and body mass index; (2) 84% for extrapyramidal symptom screening; (3) 80% for blood pressure; (4) 64% for abdominal girth and liver enzymes; (5) 60% for fasting plasma glucose; and (6) 56% for fasting lipids. Only 20% had all core recommended parameters documented. CONCLUSIONS: There were significant gaps in adverse effect monitoring in this cohort. Examination of variation in larger samples from multiple clinical services are required to determine the extent of this quality care gap. Several barriers to adherence are proposed with suggested solutions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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