Incidence of erectile dysfunction among middle-aged and aging sexual minority men living with or without HIV
Bibliographic record
Abstract
Introduction: Erectile dysfunction (ED) has been established as a comorbidity among men living with HIV, but comparisons by HIV serostatus of ED incidence in a longitudinal follow-up cohort of men are lacking. We sought to evaluate the incidence of ED spanning a period of 12 years in a longitudinal cohort of sexual minority men (SMM) living with and without HIV. Methods: We analyzed ED incidence data for 625 participants in the longitudinal Multicenter AIDS Cohort Study from visits spanning October 2006 to April 2019. Results: SMM living with HIV were more likely to have incident ED compared with those living without HIV (rate ratio: 1.41; 95% CI: 1.14-1.75). Older age, current diabetes, cumulative cigarette use, and cumulative antidepressant use were associated with increased incidence of ED in the entire sample. Self-identifying as Hispanic, current diabetes, and cumulative antidepressant use were positively associated with ED incidence among SMM living with HIV. Cumulative cigarette use was positively associated with greater ED incidence only among SMM living without HIV. Discussion: In summary, age (full sample/ with HIV), current diabetes (full sample/with HIV), cumulative cigarette use (full sample/without HIV), and cumulative antidepressant use (full sample/with HIV) were associated with increased ED incidence. Skillful management of diabetes and careful titration of antidepressants, along with smoking cessation practices, are recommended to mitigate ED in this population.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".