Association of erectile dysfunction and cardiovascular disease: an umbrella review of systematic reviews and meta‐analyses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it