Association of erectile dysfunction and cardiovascular disease: an umbrella review of systematic reviews and meta‐analyses
Bibliographic record
Abstract
OBJECTIVES: To present an overall picture of the evidence regarding the association of erectile dysfunction (ED) with cardiovascular disease (CVD). METHODS: Systematic reviews and meta-analyses that studied the association of ED with any CVD were included in this umbrella review. We did not restrict the population to a particular group or age. PubMed, Embase, the Joanna Briggs Institute (JBI) Database of Systematic Reviews and Implementation Reports, the Cochrane Database of Systematic Reviews, the Database of Abstracts of Reviews of Effects, and the PROSPERO register were searched to find relevant systematic reviews, with or without meta-analyses, from inception to April 2020. The JBI Checklist for Systematic Reviews and Research Syntheses was used for the critical appraisal. Only studies with acceptable quality were included. Two independent reviewers extracted the data using the JBI data extraction tool for qualitative and quantitative data extraction. RESULTS: The summary estimate showed a higher risk of CVD (relative risk [RR] 1.45, 95% confidence interval [CI] 1.36-1.54; P < 0.001), coronary heart disease (RR 1.50, 95% CI 1.37-1.64; P < 0.001), cardiovascular-related mortality (RR 1.50, 95% CI 1.37-1.64; P < 0.001), all-cause mortality (RR 1.25, 95% CI 1.18-1.32; P < 0.001), myocardial infarction (RR 1.55, 95% CI 1.33-1.80; P < 0.001) and stroke (RR 1.36, 95% CI 1.26-1.46; P < 0.001) in patients with ED than in other patients. CONCLUSIONS: Our results confirm that ED is an independent predictor of CVD and their outcomes. ED and CVD are two presentations of the same physiological phenomenon. ED normally precedes symptomatic CVD, providing a window of opportunity for healthcare practitioners to screen and detect high-risk patients early to prevent avoidable morbidity and mortality.
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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 | 0.059 | 0.135 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.017 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".