The Cumulative Effects of Medication Use, Drug Use, and Smoking on Erectile Dysfunction Among Men Who Have Sex With Men
Bibliographic record
Abstract
Introduction Erectile dysfunction (ED) is highly prevalent among Human Immunodeficiency Virus-seropositive (HIV+) men who have sex with men (MSM). There is a need for additional research to determine the correlates of HIV+ and HIV-seronegative (HIV−) MSM, especially regarding non-antiretroviral medication use. Aims This study examined the prevalence of ED and the socio-demographic, medical conditions, medication use, and substance use correlates of ED among HIV+ and HIV− MSM. Methods A modified version of the International Index of Erectile Function (IIEF) for MSM was self-administered by participants enrolled in the Multicenter AIDS Cohort Study (MACS), an ongoing prospective study of the natural and treated histories of HIV infection among MSM in the United States. The study sample included 1,340 participants, including 612 HIV+ and 728 HIV− men. Poisson regression with robust error variance was used to estimate prevalence ratios of ED in multivariable models in combined (HIV+/−) and separate analyses. Main outcome measure ED was determined by the summed scores of a modified version of the IIEF validated among MSM. Results Twenty-one percent of HIV+ MSM and 16% of HIV− MSM reported ED. Being >55 years of age, Black race, cumulative pack-years of smoking, cumulative antihypertensive use, and cumulative antidepressant use had significant positive associations with the prevalence of ED in the total sample. Among HIV+ men, duration of antihypertensive use and antidepressant use were significantly associated with increasing prevalence of ED. Among HIV− men, being >55 years of age, Black race, and cigarette smoking duration were associated with increased prevalence of ED. Conclusion Predictors of ED may differ by HIV status.. Although smoking cessation and effective medication management may be important as possible treatment strategies for ED among all MSM, there may be a burden on sexual functioning produced by non-HIV medications for HIV+ 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".