Sensory pain characteristics of vulvodynia and their association with nociceptive and neuropathic pain: an online survey pilot study
Bibliographic record
Abstract
Objectives: To evaluate self-reported sensory pain scores of women with generalized vulvodynia (GV) and provoked vestibulodynia (PVD), characterize pain phenotypes, and assess feasibility of using the Internet for recruitment and data collection among women with vulvodynia. Methods: Descriptive online survey. Data collected using an online survey accessed via a link on the National Vulvodynia Association web site. Convenience sample, 60 women aged 18 to 45 years (mean = 32.7 ± 5.5); 50 white, 2 black/African American, 4 Hispanic/Latino, and 4 Native American/Alaskan Native, diagnosed with vulvodynia, not in menopause. Pain assessment and medication modules from PAINReportlt. Results: Women with GV (n = 35) compared to PVD (n = 25). Estimated mean pain sites (2.5 ± 1.4 vs 2.2 ± 1.0, P = 0.31), mean current pain (8.7 ± 1.4 vs 5.5 ± 4.0, P = 0.0008), worst pain (8.1 ± 1.8 vs 6.1 ± 3.6, P = 0.02), and least pain in the past 24 hours (4.4 ± 1.8 vs 2.0 ± 2.0, P < 0.0001). Average pain intensity (7.1 ± 1.2 vs 4.6 ± 2.9, P = 0.0003) on a scale of 0 to 10, mean number of neuropathic words (8.3 ± 3.6 vs 7.7 ± 5.0), and mean number of nociceptive words (6.9 ± 4 vs 7.5 ± 4.4). Nineteen (54%) women with GV compared to 9 (38%) with PVD were not satisfied with pain levels. Conclusion: Women with GV reported severe pain, whereas those with PVD reported moderate to severe pain. Pain quality descriptors may aid a clinician's decisions about whether to prescribe adjuvant drugs vs opioids to women with vulvodynia.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".