Prevalence of lower urinary tract symptoms and level of quality of life in men and women with chronic pelvic pain
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to evaluate the prevalence of lower urinary tract symptoms and quality of life in patients with chronic pelvic pain syndrome (CPPS). MATERIALS AND METHODS: The McGill Pain Questionnaire, Dutch Leiden/Leuven Version (MPQ-DLV), Pain Disability Index (PDI), National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI), Interstitial Cystitis Symptom Index (ICSI) and Pelvic Pain and Urinary/Frequency Symptom Scale (PUF) were used, based on their specific properties, to assess the symptoms and impact on the quality of life. Total scores and domains were compared for gender. RESULTS: The studied group (N = 35; 18 male, 17 female) showed a good distribution in gender for age [Mann-Whitney U test (MW-U) p = 0.4] and body mass index (MW-U p = 0.2). The MPQ-DLV showed significantly higher scores for pain in women for Pain Rating Index - Affective (MW-U p = 0.030) and Total (MW-U p = 0.031), and Visual Analogue Scale for Pain - Most (MW-U p = 0.005). Women were less sexually active (PUF-SA) (chi-squared test p = 0.021) and had a significantly higher disability (PDI-T) (MW-U p = 0.005) and MPQ - Quality of Life (MW-U p = 0.003). The urinary symptoms showed similar results for gender (chi-squared test p > 0.05). CONCLUSIONS: A wide variety of symptoms and a negative impact on quality of life were shown. No differences in lower urinary tract symptoms were found between genders. Women were less sexually active than men. Chronic pelvic pain had a significantly higher negative impact on the level of quality of life in women than in men.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".