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Record W2749603546 · doi:10.1016/j.jsxm.2017.06.013

Delayed Ejaculation and Associated Complaints: Relationship to Ejaculation Times and Serum Testosterone Levels

2017· article· en· W2749603546 on OpenAlexaboutno aff
Abraham Morgentaler, Paula Polzer, Stanley E. Althof, Alexander Bolyakov, Craig F. Donatucci, Ankur B. Patel, Shehzad Basaria

Bibliographic record

VenueThe Journal of Sexual Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsnot available
FundersEli Lilly and Company
KeywordsEjaculationPremature ejaculationTestosterone (patch)MedicineOrgasmSexual dysfunctionSexual functionInternal medicineUrologyGynecologyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Although delayed ejaculation (DE) is typically characterized as a persistently longer than anticipated or desired time to ejaculation (or orgasm) during sexual activity, a timing-based definition of DE and its association with serum testosterone has not been established in a large cohort. AIM: To examine in an observational study estimated intravaginal ejaculatory latency time (IELT) and masturbatory ejaculation latency time (MELT) in men self-reporting DE, assess the association of IELT and MELT with serum testosterone levels, and determine whether correlation with demographic and sexual parameters exist. METHODS: Men who resided in the United States, Canada, and Mexico were enrolled from 2011 to 2013. Self-estimated IELT and MELT were captured using an Ejaculatory Function Screening Questionnaire in a sample of 988 men screened for possible inclusion in a randomized clinical trial assessing testosterone replacement therapy for ejaculatory dysfunction (EjD) and who self-reported the presence or absence of DE and symptoms of hypogonadism. Additional comorbid EjDs (ie, anejaculation, perceived decrease in ejaculate volume, and decreased force of ejaculation) were recorded. Men with premature ejaculation were excluded from this analysis. IELT and MELT were compared between men self-reporting DE and men without DE. The associations of IELT and MELT with serum testosterone were measured. OUTCOMES: IELT, MELT, and total testosterone levels. RESULTS: Sixty-two percent of screened men self-reported DE with or without comorbid EjDs; 38% did not report DE but did report at least one of the other EjDs. Estimated median IELTs were 20.0 minutes for DE vs 15 minutes for no DE (P < .001). Estimated median MELTs were 15.0 minutes for DE vs 8.0 minutes for no DE (P < .001). Ejaculation time was not associated with serum testosterone levels. Younger men and those with less severe erectile dysfunction had longer IELTs and MELTs. CLINICAL IMPLICATIONS: Estimated ejaculation times during vaginal intercourse and/or masturbation were not associated with serum testosterone levels in this study; thus, routine androgen evaluation is not indicated in these men. STRENGTHS AND LIMITATIONS: This large systematic analysis attempted to objectively assess the ejaculation latency in men with self-reported DE. Limitations were that ejaculation time estimates were self-reported and were queried only once; the questionnaire did not distinguish between failure to achieve orgasm and ejaculation; and assessment of DE was limited to heterosexual vaginal intercourse and masturbation. CONCLUSION: IELT and MELT were longer in men with DE, and there was no association of ejaculation times with serum testosterone levels in this study population. Morgentaler A, Polzer P, Althof S, et al. Delayed Ejaculation and Associated Complaints: Relationship to Ejaculation Times and Serum Testosterone Levels. J Sex Med 2017;14:1116-1124.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.122
GPT teacher head0.359
Teacher spread0.237 · 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 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

Citations24
Published2017
Admission routes1
Has abstractyes

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