0747 Medications Prescribed For Sleep Problems In Children And Adolescents With Psychiatric Disorders.
Bibliographic record
Abstract
Up to 90% of children and adolescents with a psychiatric diagnosis also suffer from sleep disorders, thus worsening their diurnal symptoms. Most of these children are prescribed medications to help them cope with their sleep difficulties. We analyzed the medical files of patients referred to the sleep clinic of a pediatric mental health hospital. The medical charts of 401 patients diagnosed with or being evaluated for a psychiatric disorder and referred to the sleep clinic of a pediatric mental health hospital were reviewed by two judges with full access to the complete hospital file of each patient. The mean age of patients was 8.4 ± 4.7 years and 67% were boys. The most frequent primary diagnoses were Autism Spectrum Disorder (ASD, 39.4%) and Attention Deficit Hyperactivity Disorder (ADHD, 28.7%). A majority of patients (81.2%) was either referred by a pediatrician (42.8%) or a psychiatrist (38.4%). At intake, all diagnoses being combined, 78.5% of patients were taking melatonin, a product available over-the-counter in Canada. Antipsychotics (18.9%), antidepressants (10.7%) and clonidine (also 10.7%) were the most prescribed medications at bedtime. In ASD and ADHD more specifically, antipsychotics were the most prescribed medication at bedtime, with 23.4% and 29.6% of patients, respectively. Melatonin was reported as the most frequent sleep aid taken by patients upon their arrival at the sleep clinic but dosage and timing varied greatly, pointing toward a knowledge gap in parents, prescribers, providers and/or advisors. The use of antipsychotics at bedtime in children and adolescents is alarming, given the fact that there is no published scientific evidence to support their use. Support (If Any)
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".