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Record W2605334635 · doi:10.1016/j.juro.2017.02.692

PD13-04 RESULTS OF A NORTH AMERICAN SURVEY ON THE CHARACTERISTICS OF MEN BEING ASSESSED IN MALE INFERTILITY CLINICS: THE ANDROLOGY RESEARCH CONSORTIUM

2017· article· en· W2605334635 on OpenAlexaboutno aff
Keith Jarvi, Susan Lau, Kirk Lo, Ethan D. Grober, J.C. Trussell, James M. Hotaling, Thomas J. Walsh, Peter N. Kolettis, Victor Chow, Arma Zin, Marc Goldstein, Aaron Spitz, Marc Anthony Fischer, Scott I. Zeitlin, Eugene Fuchs, Mary K. Samplaski, Jay Sandlow, Robert E. Brannigan, Ed Ko, Tung-Chin Hsieh, James Smith

Bibliographic record

VenueThe Journal of Urology · 2017
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsChinMedicineClassicsPsychoanalysisHistoryPsychology

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyInfertility: Epidemiology & Evaluation I1 Apr 2017PD13-04 RESULTS OF A NORTH AMERICAN SURVEY ON THE CHARACTERISTICS OF MEN BEING ASSESSED IN MALE INFERTILITY CLINICS: THE ANDROLOGY RESEARCH CONSORTIUM Keith Jarvi, Susan Lau, Kirk Lo, Ethan Grober, J Trussell, James Hotaling, Thomas Walsh, Peter Kolettis, Victor Chow, Arma Zin, Marc Goldstein, Aaron Spitz, Marc Fischer, Scott Zeitlin, Eugene Fuchs, Mary Samplaski, Jay Sandlow, Robert Brannigan, Ed Ko, Tung-Chin Hsieh, and James Smith Keith JarviKeith Jarvi More articles by this author , Susan LauSusan Lau More articles by this author , Kirk LoKirk Lo More articles by this author , Ethan GroberEthan Grober More articles by this author , J TrussellJ Trussell More articles by this author , James HotalingJames Hotaling More articles by this author , Thomas WalshThomas Walsh More articles by this author , Peter KolettisPeter Kolettis More articles by this author , Victor ChowVictor Chow More articles by this author , Arma ZinArma Zin More articles by this author , Marc GoldsteinMarc Goldstein More articles by this author , Aaron SpitzAaron Spitz More articles by this author , Marc FischerMarc Fischer More articles by this author , Scott ZeitlinScott Zeitlin More articles by this author , Eugene FuchsEugene Fuchs More articles by this author , Mary SamplaskiMary Samplaski More articles by this author , Jay SandlowJay Sandlow More articles by this author , Robert BranniganRobert Brannigan More articles by this author , Ed KoEd Ko More articles by this author , Tung-Chin HsiehTung-Chin Hsieh More articles by this author , and James SmithJames Smith More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.692AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The Andrology Research Consortium was established by the Society for the Study of Male Reproduction, a specialty section of the American Urological Association, to characterize men presenting for infertility investigation. METHODS A standardized questionnaire capturing information about the infertile couples’ demographics, reproductive history, previous fertility investigations, lifestyle factors and use of medications was completed by patients in 19 different clinics treating men with infertility across North America. RESULTS A total of 2506 men completed the questionnaires. The mean age of the men and their female partners was 38 +/- 7 (SD) and 34 +/- 5 years old, respectively. 1505/2421 (62%) were referred by a reproductive endocrinologist and 524/2421 (22%) by their PCP. Of the 812 who answered this question, 688 (85%) reported that they were told that they had an abnormal sperm test. Prior to the consultation with the male infertility clinic, 274/2023 (14%) reported having used Intra-uterine insemination (IUI) with another 168/2168 (7.7%) reported the use of in-vitro fertilization (IVF) or intracytoplasmic sperm insertion (ICSI) therapy to treat the infertility. Only 31/274 (11%) of the couples who had undergone IUIs and 17/168 (10%) of those using IVF/ICSI reported a previous male fertility investigation. Potentially reversible causes of male infertility like use of medications and smoking were relatively common. Overall, 35/2384 (1.5%) men reporting using propecia and 74/2218 (3.3%) using testosterone. This data was skewed by the results from the University of Toronto where patients reported far lower use of propecia (1/1274) or testosterone (7/1274). Excluding the University of Toronto results, 34/1110 (3.1%) and 67/944 (7.1%) of the men reported using propecia and/or testosterone, respectively. While uncommon, 2 men reported that they had used IUI or IVF while remaining on propecia or testosterone. The testosterone was prescribed principally by PCPs, but many of the men reported that they obtained testosterone from non-physicians. In total, 352/2034 (17.3%) reported smoking. CONCLUSIONS Most men presenting to our male infertility clinics are referred from reproductive endocrinologists with abnormal sperm test results. Among couples who had previously been treated with advanced reproductive technologies like IUI, IVF or ICSI, only 11% had been referred to a urologist prior to the therapies. We identified a number of potentially reversible causes for the male sub-fertility in this group supporting the idea that more urology is needed, not less. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e272 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Keith Jarvi More articles by this author Susan Lau More articles by this author Kirk Lo More articles by this author Ethan Grober More articles by this author J Trussell More articles by this author James Hotaling More articles by this author Thomas Walsh More articles by this author Peter Kolettis More articles by this author Victor Chow More articles by this author Arma Zin More articles by this author Marc Goldstein More articles by this author Aaron Spitz More articles by this author Marc Fischer More articles by this author Scott Zeitlin More articles by this author Eugene Fuchs More articles by this author Mary Samplaski More articles by this author Jay Sandlow More articles by this author Robert Brannigan More articles by this author Ed Ko More articles by this author Tung-Chin Hsieh More articles by this author James Smith More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

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)0.003
metaresearch head score (Gemma)0.012
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: none
Teacher disagreement score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.008
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.004

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 head0.143
GPT teacher head0.434
Teacher spread0.291 · 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".

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Citations1
Published2017
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