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Record W4237287906 · doi:10.5489/cuaj.19

Evolving therapeutic strategies for premature ejaculation: The search for on-demand treatment – topical versus systemic

2012· article· en· W4237287906 on OpenAlexaffvenue
Álvaro Morales

Bibliographic record

VenueCanadian Urological Association Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsPremature ejaculationMedicineSexual medicinePlaceboEjaculationSexual dysfunctionAdverse effectPharmacotherapyConcomitantInternal medicinePsychologyPsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

Premature ejaculation (PE) is a common sexual dysfunction affecting20% to 30% of men worldwide. Definitions of PE vary, but itis typically characterized by short intravaginal ejaculatory latencytime (IELT) with concomitant sexual dissatisfaction and distress.PE may be lifelong or acquired, but its etiology remains unclear.Treatment of PE typically involves pharmacotherapy, particularlywhen lifelong. Although there are numerous reports on the offlabeluse of selective serotonin reuptake inhibitors (SSRIs) andother compounds, only 2 treatments have been evaluated in randomizedcontrolled phase 3 clinical trials: PSD502 and dapoxetine(SSRI). Both significantly improved IELT and patient-reportedoutcome domains of ejaculatory control, sexual satisfaction, anddistress as measured by the index of premature ejaculation (IPE),compared with placebo. They constitute the focus of this review.Evidence demonstrated that PSD502, dapoxetine and other SSRIsall significantly improve the symptoms of PE. Systemic use of SSRIspresents risks associated with the known pharmacology of thisclass. PSD502 allows for topical on-demand treatment appliedapplied immediately before intercourse, and is not associated withsystemic adverse events.

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)0.001
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 score0.277
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.081
GPT teacher head0.320
Teacher spread0.239 · 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

Citations1
Published2012
Admission routes2
Has abstractyes

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