Pain evoked by distension of the uterine cervix in women with dysmenorrhea: evidence for central sensitization
Bibliographic record
Abstract
OBJECTIVE: To study sensitization in women with dysmenorrhea using a standardized experimental model. Women with dysmenorrhea experience intense visceral pain during menstruation. The dysmenorrhea pain mechanisms are not known but sensitization may play a role. DESIGN: Prospective experimental study. SAMPLE: Ten women with dysmenorrhea and 10 control women having uterine cervical distensions in the mid-follicular period (days 6-10). SETTING: University clinic. METHOD: Cervical distension was delivered as three phasic stimuli with 1 min between distensions and as a prolonged (1 min) distension. MAIN OUTCOME MEASURE: Sensory intensity rated on a continuous visual analog scale. RESULTS: Distension-induced pain was described as dull and aching and referred to the pelvis, lower back and lower abdomen. Larger evoked referred pain areas were present in women with dysmenorrhea compared with control women (p < 0.05). The pain threshold to the first stimulus was significantly higher in patients than controls (p < 0.04), but decreased significantly with repeated distensions (p < 0.01). For the prolonged distension the pain rating increased significantly (p < 0.008) in women with dysmenorrhea, but decreased (p < 0.02) in control women. CONCLUSIONS: Pain sensitization (temporal summation, i.e. increase in pain during prolonged stimulation, and facilitation of referred pain areas as an indicator of central nervous system changes) is present in women with dysmenorrhea. The study provided new information on a poorly understood yet widespread condition and a basis for clinical studies to develop a biomarker tests for objective assessment of dysmenorrhea.
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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 | 0.000 | 0.000 |
| 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".