Sexual Pain Disorders, Vestibulodynia, and Recurrent Cystitis: The Evil Trio
Bibliographic record
Abstract
Abstract Sexual pain/penetration disorders are often comorbid with recurrent/post-coital cystitis and spontaneous or provoked vestibulodynia or vulvar pain. The figures vary from 34.7–60%, UropathogenicEscherichia coli(UPEC) is responsible for 85–90% of recurrent cystitis cases. Antibiotic treatment is becoming ineffective in the long term. To maximize therapeutic outcomes, a different strategy is worth considering. Common pathophysiological denominators of the three clusters of symptoms present in a patient should be identified. These include (1) predisposing factors: endocellular pathogenic biofilm of the uropathogenicEscherichia coli(UPEC), hyperactive pelvic floor, bowel problems, including irritable bowel syndrome and constipation, intestinal and vaginal dysbiosis, diabetes/familiarity with diabetes, and loss of sexual hormones after menopause; (2) precipitating factors: intercourse, constipation, and cold; and (3) maintaining factors: diagnostic omissions and minimalistic treatment approach. A targeted multimodal therapeutic strategy should then be based on accurate diagnosis. A comprehensive and skilled approach can optimize anticipation of comorbidities and offer better clinical outcomes for women, where sexual pain/penetration disorders, comorbid recurrent and/or post-coital cystitis, and vestibulodynia/vulvar pain are addressed synergistically, the sooner the better.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".