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Record W2276353761 · doi:10.1017/s1092852900025748

Are We Treating Schizophrenia Effectively? Understanding the Primary Outcomes of the CATIE Study

2006· article· en· W2276353761 on OpenAlexaff
William M. Glazer, Robert R. Conley, Leslie Citrome

Bibliographic record

VenueCNS Spectrums · 2006
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsAbbott (Canada)
Fundersnot available
KeywordsQuetiapineOlanzapineZiprasidoneDiscontinuationRisperidoneAntipsychoticMedicineTolerabilityPsychiatryAripiprazoleAtypical antipsychoticPerphenazineSchizophrenia (object-oriented programming)Adverse effectInternal medicine

Abstract

fetched live from OpenAlex

The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study for schizophrenia was designed to independently evaluate the effectiveness of antipsychotic treatment in "real-world" patients. To assess the effectiveness of the conventional antipsychotics compared to the atypicals as well as the differences among the atypicals, patients were randomized to one of four atypical antipsychotics (olanzapine, quetiapine, risperidone, ziprasidone) or a representative conventional antipsychotic (perphenazine). Effectiveness was defined by time to discontinuation and duration of successful treatment. Time to "all-cause" discontinuation reflects both efficacy (ability of a drug to reduce symptoms) and safety/tolerability. Phase I revealed discontinuation rates ranging from 64% for olanzapine to 82% for quetiapine. Differences among the medications may be important in the selection of a drug for a particular patient. Physicians should involve the patient in choosing their medication by inquiring about the patient's past experience with medications and side effects, educating the patient on the risk-benefit ratio, and considering the patient's preference. To demonstrate how results of the CATIE study can contribute to the knowledge of practicing clinicians, this monograph presents a representative clinical case patient and illustrates how the CATIE safety and efficacy data has important implications for the patient.

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 score0.012
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.039
GPT teacher head0.296
Teacher spread0.257 · 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

Citations25
Published2006
Admission routes1
Has abstractyes

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