Baseline Prevalence of Erectile Dysfunction in a Prostate Cancer Screening Population
Bibliographic record
Abstract
INTRODUCTION: Erectile dysfunction (ED) is common in older men and can be worsened by prostate cancer (PCa) treatment. True ED rates before PCa treatment are mandatory, in order to assess the rate of ED attributable to PCa treatment. Data derived from population-based studies or from patients surveyed after PCa diagnosis, as well as just prior to treatment may not represent a valid benchmark, as health profiles of the general population might be different to those undergoing PCa screening or as anxiety may worsen existent ED. AIM: To circumvent these limitations, we assessed the baseline rate of ED in PCa diagnosis-free men participating in a PCa awareness event. METHODS: ED was classified according to the International Index of Erectile Function (IIEF) score as absent (IIEF: 25-30), mild (22-24), mild to moderate (17-21), moderate (11-16), or severe (</=10). Analyses were adjusted according to age and socioeconomic status. MAIN OUTCOME MEASURES: Of 1,273 asymptomatic men who participated in the event, 1,134 (89.1%) completed the IIEF score. RESULTS: Mean age was 57.6 years (range 40-89 years). Of all participating men, 50.0% (N = 566) were potent, 8.8% (N = 100) reported mild, 10.4% (N = 118) mild to moderate, 9.4% (N = 107) moderate, and 21.4% (N = 243) severe ED. Men with ED were significantly older (P < 0.001), had no stable partner (P < 0.001), lower education (P < 0.001), and lower annual income (P < 0.001) than men without ED. CONCLUSIONS: One in two men who participated in this PCa awareness event is affected by ED, independent of PCa diagnosis or treatment. Such high prevalence of baseline ED in a PCa screening cohort suggests that in patients treated for PCa, ED may represent a common disorder already present prior to treatment. Moreover, socioeconomic variables were seen to have an important influence on erectile function in this patient cohort.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".