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Resource utilization in a Canadian national study of people with schizophrenia and related psychotic disorders

2006· article· en· W2042446691 on OpenAlexaffabout
Lili C. Kopala, G. Smith, Ashok Malla, Rachel Williams, L. Love, D. Talling, Robert Balshaw

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2006
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsQuetiapineOlanzapineRisperidoneSchizophrenia (object-oriented programming)ClozapinePsychiatryAntipsychoticAtypical antipsychoticMedicineIndirect costsPharmacoeconomicsEnvironmental healthIntensive care medicineBusiness

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine how the use of the newer, so called atypical antipsychotic medications, effects the pharmacoeconomic treatment burden of schizophrenia and related conditions and to provide a clear comparison of the costs and risks associated with these atypical drugs. METHOD: In this 2-year, open-label, prospective study, resource utilization (RU) data were collected on 160 patients with these conditions. A comparison between risks and costs was performed by combining the generalized CNOMSS data on both economic factors and risk assessments. RESULTS: The main findings of the study were that the total adjusted 1- and 2-year costs were lowest for quetiapine. Drug acquisition costs were lowest for risperidone for both the 1- and 2-year cohorts. Clozapine use was predictably associated with the highest overall and medication costs at both 1 and 2 years. CONCLUSION: Treatment with risperidone or quetiapine was associated with the lowest overall costs when compared with olanzapine or clozapine.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.589
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.273
Teacher spread0.262 · 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 teacher head, 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

Citations9
Published2006
Admission routes2
Has abstractyes

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