Prevalence and Patterns of Antipsychotic Use in Youth at the Time of Admission and Discharge From an Inpatient Psychiatric Facility
Bibliographic record
Abstract
The objective of this study was to examine the prevalence and patterns of antipsychotic use in children and adolescents at the time of admission and discharge from a tertiary care inpatient psychiatric facility. This retrospective analysis included all patients 18 years and younger, who were admitted and discharged from a child and adolescent tertiary care inpatient psychiatric facility between May 1, 2008 and December 31, 2009. Data for medications at admission were obtained using a province-wide network that links all pharmacies in British Columbia, Canada to a central set of data systems, whereas data for medications at discharge were obtained using the Department of Pharmacy's (British Columbia Children's Hospital, Vancouver, British Columbia, Canada) inpatient computer database. Apart from antipsychotics, overall drug use included antidepressants, mood stabilizers, benzodiazepines, anticholinergics, stimulants, and sleep medications. Referral and discharge diagnoses were also examined. During the study period, 335 patients were admitted and discharged from the tertiary care inpatient psychiatric facility. Significantly, more patients were prescribed with an antipsychotic at the time of discharge from hospital compared with that of the time when they were admitted to hospital (51.6% vs 30.7%; P < 0.0001). Antidepressants were most often coprescribed with an antipsychotic at admission and discharge (32.0% vs 42.2%, respectively) followed by attention-deficit/hyperactivity disorder medications (22.3% vs 24.9% at admission and discharge, respectively) and anticonvulsants (19.4% vs 19.1% at admission and discharge, respectively). Whether the significant increase in antipsychotic use seen from the time of admission to discharge is solely attributed to clinical worsening or other variables requires further investigation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".