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Record W2759644066 · doi:10.1177/1179559x17731801

Brexpiprazole in the Treatment of Major Depressive Disorder

2017· article· en· W2759644066 on OpenAlexafffund
Maryam I. Al Shirawi, Nicole E. Edgar, Sidney H. Kennedy

Bibliographic record

VenueClinical Medicine Insights Therapeutics · 2017
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health NetworkSt. Michael's Hospital
FundersOntario Brain InstituteMassachusetts General Hospital
KeywordsPartial agonistAripiprazolePsycINFOMajor depressive disorderAdjunctive treatmentAntipsychoticAntidepressantMedicineMeta-analysisPsychologyAtypical antipsychoticPsychiatryPsychotherapistMEDLINESchizophrenia (object-oriented programming)AgonistInternal medicineAnxietyMoodReceptor

Abstract

fetched live from OpenAlex

Brexpiprazole, a novel atypical antipsychotic agent, has recently been approved as an adjunctive treatment for major depressive disorder (MDD) when monotherapy only provides a partial response. The mechanism of action is likely related to its partial agonist activity at D 2 and 5-HT 1A receptors, as well as potent 5-HT 2A antagonist effects. The purpose of this systematic review is to provide a detailed overview available evidence on its role in treating MDD, based on all clinical publications in the English language between January 1, 2014 and April 30, 2017 identified from PubMed, Google Scholar, Scopus, Web of Science, PsycINFO, and ClinicalTrials.gov . Two primary pivotal trials are reviewed in detail and a further 10 supporting reviews and open-label studies are discussed. Brexpiprazole is compared with aripiprazole according to pharmacologic and clinical activities. Overall, this appears to be a useful antidepressant adjunctive therapy with a favorable side effect profile and comparable efficacy with existing agents.

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 score0.303
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.131
GPT teacher head0.440
Teacher spread0.309 · 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

Citations11
Published2017
Admission routes2
Has abstractyes

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