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Record W2050833686 · doi:10.1186/1471-244x-13-198

Prescribing trends of antipsychotics in youth receiving income assistance: results from a retrospective population database study

2013· article· en· W2050833686 on OpenAlexafffundabout
Andrea Murphy, David M. Gardner, Charmaine Cooke, Steve Kisely, Jean Hughes, Stan Kutcher

Bibliographic record

VenueBMC Psychiatry · 2013
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsCapital District Health AuthorityIzaak Walton Killam Health CentreDalhousie University
FundersNova Scotia Health Research Foundation
KeywordsMedical prescriptionRisperidoneNova scotiaMedicinePopulationAntipsychoticPsychiatryMoodRetrospective cohort studyCohortFamily medicineSchizophrenia (object-oriented programming)Environmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Prescribing of antipsychotics (AP) to young people has increased in the last decade internationally. We aimed to characterize AP prescribing in a population of low-income youth in Nova Scotia, Canada. METHODS: We conducted a population database study of AP prescription claims and health services utilization by young people aged 25 years and younger receiving drug benefits through the publicly funded Pharmacare program between October 1, 2000 to September 30, 2007. RESULTS: Four percent (1715/43888) of youth receiving Pharmacare benefits filled AP prescriptions. The use of second generation antipsychotics (SGAs) significantly increased (p < 0.0001) in all age groups except 0-5 year olds, whereas first generation antipsychotic use significantly decreased. Pharmacare beneficiaries aged 21-25 years represented 45.2% of AP users. The majority (66%) of youth filling AP prescriptions had 2 or more psychiatric diagnoses. Most youth (76%) filled prescriptions for only one type of AP during the study period. Psychotic disorders were the most common indication for AP use except with risperidone, in which ADHD was the most likely reason for use. Co-prescribing of psychotropics was prevalent with antidepressants and mood stabilizers prescribed in 42% and 27% of AP users, respectively. General practitioners (GPs) prescribed incident APs most often (72%) followed by psychiatrists (16%). The age- and gender-adjusted rate of death was higher in AP users as compared to the age-matched general population of Nova Scotia. CONCLUSIONS: SGA use increased significantly over seven years in a cohort of 0 to 25 years olds receiving Pharmacare benefits. Off-label use of APs was prevalent with ADHD and other non-psychotic disorders being common reasons for AP use. GPs initiated most AP prescriptions. Co-prescribing of other psychotropics, especially antidepressants and mood stabilizers, was prevalent even in younger age strata. This study raises further questions about AP prescribing in those 25 years of age and under, especially given the range of diagnoses and psychotropic co-prescribing.

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)0.002
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 score0.481
Threshold uncertainty score0.956

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.316
Teacher spread0.277 · 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

Citations29
Published2013
Admission routes3
Has abstractyes

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