Impact of a Mediterranean diet on prevention and management of urologic diseases
Bibliographic record
Abstract
Compared to a Western diet, the Mediterranean diet moves away from red meat and processed foods. Universally regarded as a healthier dietary alternative, the Mediterranean diet has garnered scientific endorsement for its ability to confer an array of compelling benefits. These health benefits encompass not only a lowered incidence of Type 2 diabetes with a reduction in obesity, but also a robust protective effect on cardiovascular health. Extensive literature exists to corroborate these health benefits; however, the impact of a Mediterranean diet on urologic diseases, specifically sexual dysfunction, lower urinary tract symptoms, stone disease, and urologic cancers are not well studied. Understanding how dietary habits may impact these urologic conditions can contribute to improved prevention and treatment strategies.A total of 955 papers from PubMed and Embase were systematically reviewed and screened. After exclusion of disqualified and duplicated studies, 58 studies consisting of randomized controlled trials, cohort studies, cross sectional studies, reviews and other meta-analyses were included in this review. 11 primary studies were related to the impact of a Mediterranean diet on sexual dysfunction, 9 primary studies regarding urinary symptoms, 8 primary studies regarding stone disease, and 9 primary studies regarding urologic cancers. All primary studies included were considered of good quality based on a New-Castle Ottawa scale. The results demonstrate a Mediterranean diet as an effective means to prevent as well as improve erectile dysfunction, nephrolithiasis, lower urinary tract symptoms, and urinary incontinence. The review highlights the need for additional research to study the impact of diet on urologic cancers and other urologic conditions such as premature ejaculation, loss of libido, female sexual dysfunction, and overactive bladder.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".