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Record W2011509564 · doi:10.2147/tcrm.2007.3.1.59

Venlafaxine extended release (XR) in the treatment of panic disorder

2007· article· en· W2011509564 on OpenAlexaff
Kevin Kjernisted, Diane McIntosh

Bibliographic record

VenueTherapeutics and Clinical Risk Management · 2007
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVenlafaxinePanic disorderMedicineParoxetinePlaceboPanicAntidepressantInternal medicinePsychiatryAnxiety

Abstract

fetched live from OpenAlex

Panic disorder is a chronic, recurrent illness, with a lifetime prevalence of about 5%. It is associated with substantial functional impairment, and studies suggest that treatment with medication alone (and no instruction in exposure to feared and avoided situations) is less than optimal. In fact, 40%-90% of patients in long-term follow-up studies in the late 1980s and early 1990s, treated with antidepressants or high potency benzodiazepines alone, remained somewhat symptomatic. Venlafaxine extended release (XR) was effective and well tolerated in both the short-term and long-term treatment of panic disorder. In 12-week trials, venlafaxine XR was significantly more effective than placebo in achieving a panic-free state (54%-70% vs 34%-48%, p</=0.05), and was as effective as paroxetine. In addition, venlafaxine XR has been shown to produce significantly higher response and remission rates than placebo. Relapse rates were significantly reduced with ongoing venlafaxine XR treatment compared to switching to placebo (22% vs 50%, p</=0.001), in a 6 month study. Importantly, venlafaxine XR significantly improved patient quality of life and functioning, and was generally well tolerated.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.063
GPT teacher head0.425
Teacher spread0.362 · 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 designNon-randomized trial
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

Citations24
Published2007
Admission routes1
Has abstractyes

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