Vascular Disease and Prostate Cancer: A Conflicting Association
Bibliographic record
Abstract
Background: To date, only a few studies have explored the relationship between vascular disease and Prostate Cancer (PCa), with conflicting results. The Aim of the research was to investigate the association of carotid vascular disease (CVD) or Coronary Artery disease (CAD) with PCa hormone-naive at initial diagnosis. Methods: Retrospective analysis of 266 patients undergoing prostate biopsy at our institution between 2006 and 2009 was conducted. We examined associations of CVD or CAD in 133 patients with PCa diagnosis versus 133 age-matched controls. Men with incomplete data available, history of hormone therapy or chemotherapy, prostate or bladder surgery were excluded. Results: CVD was significantly linked to PCa in all cases versus controls at initial diagnosis of PCa (OR 2.42, p < 0.05). Similarly CAD was significantly related to PCa at initial diagnosis (OR 1.88, p < 0.05). Conclusions: In our study a significant relation was found between vascular damage and PCa hormone-naive at initial diagnosis. Further research should elucidate these associations in larger samples to confirm these relationships and to stabilize future prevention strategies.
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 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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".