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Record W2172878202 · doi:10.1192/bjp.177.4.292

Predictive value of pharmacological activity for the relative efficacy of antidepressant drugs

2000· review· en· W2172878202 on OpenAlexaff
Nick Freemantle, Ian Anderson, Philip J. Young

Bibliographic record

VenueThe British Journal of Psychiatry · 2000
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsCentre for Advancing Health Outcomes
Fundersnot available
KeywordsAntidepressantPredictive valueMedicineValue (mathematics)PharmacologyPsychologyPsychiatryInternal medicineMathematicsStatisticsAnxiety

Abstract

fetched live from OpenAlex

BACKGROUND: There is uncertainty about the contribution of specific pharmacological properties to the efficacy of antidepressants. AIMS: To assess whether specific pharmacological characteristics of alternative antidepressants resulted in altered efficacy compared to that of selective serotonin reuptake inhibitors in the treatment of major depression. METHOD: Meta-regression analysis of randomised trials that compare treatment with a selective serotonin reuptake inhibitor and an alternative antidepressant. RESULTS: One-hundred-and-five randomised trials were included. None of the factors identified a priori predicted a statistically significant improvement in outcome across the trials. CONCLUSIONS: This analysis does not provide evidence that antidepressants acting at more than one pharmacological site differ in efficacy from drugs selective for serotonin reuptake in the treatment of major depression.

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)0.068
metaresearch head score (Gemma)0.268
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.068
Threshold uncertainty score0.358

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.268
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.016
Bibliometrics0.0060.006
Science and technology studies0.0000.002
Scholarly communication0.0030.003
Open science0.0030.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.033
GPT teacher head0.362
Teacher spread0.329 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations106
Published2000
Admission routes1
Has abstractyes

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