Correlates of PDE5i Use Among Subjects with Erectile Dysfunction in Two Population-Based Surveys
Bibliographic record
Abstract
INTRODUCTION: Erectile dysfunction (ED) is thought to affect some 150 million men worldwide, but many men with ED symptoms do not seek treatment. Existing surveys suggest that men with severe ED and who report support from their partners are more likely to receive treatment than were others. Less is known, however, concerning the influence of sociomedical factors such as income and body composition on receipt of treatment. AIM: The aim of this study was to determine the importance of socioeconomic status, comorbidities, and body composition on receipt of treatment for ED symptoms. METHODS: We used data on 638 men enrolled in the Boston Area Community Health (BACH) survey reporting ED symptoms and/or treatment for ED as evidenced by phosphodiesterase type 5 inhibitor (PDE5i) use. Logistic regression was employed to assess the relative strength of association between receipt of treatment and socioeconomic factors, body mass index, and medical factors. A replication of these results was then provided via a parallel model using the 2004 follow-up of the Men's Attitudes to Life Events and Sexuality (MALES). MAIN OUTCOME MEASURE: In BACH, ED was deemed present if a subject scored 16 points or fewer on the five-item International Index of Erectile Function or reported PDE5i use. In MALES, presence of ED was indicated by use of a validated single question querying ED severity. RESULTS: Controlling for age, body composition and other factors, increased household income, availability of a sexual partner, and provider diagnosis of high blood pressure were positively associated with treatment seeking via the use of PDE5i therapy in BACH. Results on data available in MALES produced similar results for household income and partner availability. CONCLUSION: These data provide evidence that financial disadvantage may present a barrier to treatment of ED, an increasingly important sentinel marker of the cardiovascular and overall health among aging men.
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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 | 0.002 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".