Lower Urinary Tract Symptoms in a Chronic Pelvic Pain Population
Bibliographic record
Abstract
OBJECTIVES: This study aimed to characterize the prevalence of lower urinary tract symptoms in a chronic pain population. METHODS: In this observational cohort study, patients referred to a female pelvic pain clinic completed several validated questionnaires assessing bladder symptoms, central sensitization, pain symptoms, depression, anxiety, and neuropathic pain. Patients diagnosed as having interstitial cystitis were excluded. Patient demographic characteristics and survey responses were compared across American Urological Association Symptom Index (AUA-SI) severity categories. Multivariable logistic regression was performed to identify independent predictors of moderate-to-severe AUA-SI scores. RESULTS: A total of 177 patients were included in the analysis. American Urological Association Symptom Index data showed that 48.8% of patients had mild, 31.2% had moderate, and 20.0% had severe symptoms. Patients reporting moderate or severe AUA-SI scores had higher mean Central Sensitization Inventory (CSI) scores (46.7 ± 16.0 vs 32.9 ± 13.8, P < 0.0001), McGill scores (median, 25 [interquartile range, 16-38] vs 13 [5-27]; P = 0.0003), Patient-Reported Outcomes Measurement Information System depression T-scores (median, 53.9 [interquartile range, 46.2-61.6] vs 51.2 [37.1-55.3]; P = 0.009), Pelvic Pain and Urgency/Frequency Symptoms Scale scores (18.4 ± 6.2 vs 12.5 ± 5.4, P < 0.0001), and Self-Administered Leeds Assessment of Neuropathic Symptoms and Signs scores (median, 10.5 [interquartile range, 3.0-16.5] vs 6.0 [1.0-12.0]; P = 0.02). The odds of moderate-to-severe AUA-SI symptoms were higher with a positive PUF and CSI score and were lower with a diagnosis of vestibular pain. CONCLUSIONS: There is a high prevalence of lower urinary tract symptoms among patients with chronic pelvic pain. Vestibulodynia was associated with lower odds of bladder symptoms. High PUF and CSI scores were significantly associated with moderate-to-severe bladder symptoms.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".