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Record W2098097322 · doi:10.1517/14656566.2014.923403

Desvenlafaxine for the treatment of major depressive disorder

2014· review· en· W2098097322 on OpenAlexaff
Susan G. Kornstein, Roger S. McIntyre, Michael E. Thase, Matthieu Boucher

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2014
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsPfizer (Canada)University of Toronto
Fundersnot available
KeywordsTolerabilityMajor depressive disorderAntidepressantMedicinePsychiatryPlaceboPopulationReuptake inhibitorClinical trialInternal medicineOncologyPharmacologyAdverse effectMoodAlternative medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Major depressive disorder (MDD) is a chronic and debilitating condition often characterized by inadequate treatment. Notwithstanding the availability of more than a dozen first-line agents across disparate classes (e.g., selective serotonin reuptake inhibitors), the majority of individuals with MDD do not achieve and sustain a recovered state. A substantial percentage of MDD patients require a treatment change due to poor efficacy or tolerability. AREAS COVERED: This review focuses on recent (≤ 5 years) literature describing the pharmacokinetics, efficacy, and tolerability of desvenlafaxine , one of the more recently approved antidepressant drugs. Published papers identified via PubMed search and congress presentations were included. Results from short-term, placebo-controlled, MDD trials and randomized withdrawal trials, as well as post hoc analyses in patient subgroups, are reviewed. EXPERT OPINION: Desvenlafaxine has been shown to be an effective antidepressant with a favorable safety and tolerability profile in the general MDD population and in important patient subgroups. It has several notable differences from other serotonin-norepinephrine reuptake inhibitors, and those differences suggest populations in which it may have the most clinical benefit.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
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 head0.088
GPT teacher head0.457
Teacher spread0.369 · 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.

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

Citations18
Published2014
Admission routes1
Has abstractyes

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