2018 ERECTILE DYSFUNCTION, HYPOANDROGENISM AND HYPOGONADAL SYMPTOMS ARE FREQUENTLY FOUND IN MEN WITH INFERTILITY
Bibliographic record
Abstract
You have accessJournal of UrologyInfertility: Physiology, Pathophysiology, Basic Research1 Apr 20112018 ERECTILE DYSFUNCTION, HYPOANDROGENISM AND HYPOGONADAL SYMPTOMS ARE FREQUENTLY FOUND IN MEN WITH INFERTILITY Raj Satkunasivam, Brendan Mullen, Kirk Lo, Ethan Grober, and Keith Jarvi Raj SatkunasivamRaj Satkunasivam Toronto, Canada More articles by this author , Brendan MullenBrendan Mullen Toronto, Canada More articles by this author , Kirk LoKirk Lo Toronto, Canada More articles by this author , Ethan GroberEthan Grober Toronto, Canada More articles by this author , and Keith JarviKeith Jarvi Toronto, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2011.02.2246AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES We have previously shown that hypogonadal symptoms and erectile dysfunction (ED) are common in the population of infertile men (O'Brien et. al, J Urol 2005). We sought to examine these findings in a larger cohort and look at demographic and biochemical predictors of ED. METHODS We prospectively collected demographic data and administered the Androgen Deficiency in the Aging Male (ADAM) and Sexual Health Inventory for Men (SHIM) questionnaires to men presenting for evaluation of infertility between July 1995 and April 2010. As part of routine work up, most infertile men underwent serum hormone evaluation for total testosterone (T), estradiol (E), luteinizing hormone (LH) and follicle-stimulating hormone (FSH). In our analysis of 2783 men, we excluded all those under the age of 18 and those with pre-existing significant ED (penile prosthesis, post-radical prostatectomy). We included only those that had completed the SHIM questionnaire in entirety. All other baseline risk factors were measured, including age, smoking, marijuana use, relevant co-morbidities (diabetes mellitus, hypertension and dyslipidemia) and use of medications which may affect ED (anti-hypertensives, anti-depressants, anti-androgens and anti-histamines). We defined cases (those with ED) as men having a SHIM score <22. Logistic regression modeling was conducted to determine the significance of hormonal markers in predicting ED. RESULTS A total of 2466 men of mean age 36 (range 18–71) completed the questionnaires. The prevalence of ED and those reporting low libido (question #1 of ADAM) was 28.4% and 23.9%, respectively. Hypoandrogenism (total testosterone < 10nMol/L) was found in 31.8% of the men. In our baseline model, age (OR 1.03; 95% CI: 1.02–1.05) and the diagnosis of diabetes mellitus (OR 4.38; 95% CI: 2.56–7.51) were significant predictors of ED. While controlling for self reported low libido, T (OR 0.96; 95% CI: 0.90–1.02), LH (OR 1.11; 95% CI: 0.94–1.30), and FSH (OR 1.0; 95% CI: 0.93–1.07) did not significantly predict ED. CONCLUSIONS In this relatively young group of infertile men both ED and hypoandrogenism were quite prevalent. Interestingly, ED was unrelated to hormone levels. This data shows that ED in most of these younger infertile men is unrelated to testicular or hypothalamic-pituitary dysfunction. © 2011 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 185Issue 4SApril 2011Page: e807 Advertisement Copyright & Permissions© 2011 by American Urological Association Education and Research, Inc.MetricsAuthor Information Raj Satkunasivam Toronto, Canada More articles by this author Brendan Mullen Toronto, Canada More articles by this author Kirk Lo Toronto, Canada More articles by this author Ethan Grober Toronto, Canada More articles by this author Keith Jarvi Toronto, Canada More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".