Risk of major adverse cardiovascular events in rural vs urban settings among patients with erectile dysfunction: a propensity-weighted retrospective cohort study of 430 621 men
Bibliographic record
Abstract
BACKGROUND: The relationship between erectile dysfunction (ED) and cardiovascular (CV) events has been postulated, with ED being characterized as a potential harbinger of CV disease. Location of residence is another important consideration, as the impact of rural residence has been associated with worse health outcomes. AIM: To investigate whether men from rural settings with ED are associated with a higher risk of major adverse CV events (MACEs). METHODS: A propensity-weighted retrospective cohort study was conducted with provincial health administrative databases. ED was defined as having at least 2 ED prescriptions filled within 1 year. MACE was defined as the first hospitalization for an episode of acute myocardial infarction, heart failure, or stroke that resulted in a hospital visit >24 hours. We classified study groups into ED urban, ED rural, no ED urban, and no ED rural. A multiple logistic regression model was used to determine the propensity score. Stabilized inverse propensity treatment weighting was then applied to the propensity score. OUTCOMES: A Cox proportional hazard model was used to examine our primary outcome of time to a MACE. RESULTS: The median time to a MACE was 2731, 2635, 2441, and 2508 days for ED urban (n = 32 341), ED rural (n = 18 025), no ED rural (n = 146 358), and no ED urban (n = 233 897), respectively. The cohort with ED had a higher proportion of a MACE at 8.94% (n = 4503), as opposed to 4.58% (n = 17 416) for the group without ED. As compared with no ED urban, no ED rural was associated with higher risks of a MACE in stabilized time-varying comodels based on inverse probability treatment weighting (hazard ratio, 1.06-1.08). ED rural was associated with significantly higher risks of a MACE vs no ED rural, with the strength of the effect estimates increasing over time (hazard ratio, 1.10-1.74). CLINICAL IMPLICATIONS: Findings highlight the need for physicians treating patients with ED to address CV risk factors for primary and secondary prevention of CV diseases. STRENGTHS AND LIMITATIONS: This is the most extensive retrospective study demonstrating that ED is an independent risk factor for MACE. Due to limitations in data, we were unable to assess certain comorbidities, including obesity and smoking. CONCLUSIONS: Our study confirms that ED is an independent risk factor for MACE. Rural men had a higher risk of MACE, with an even higher risk among those who reside rurally and are diagnosed with ED.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".