Parity and sliding sign in endometriosis-associated pain and infertility : two cross-sectional studies
Bibliographic record
Abstract
Symptomatic women with endometriosis may present with chronic pelvic pain (CPP) and infertility. Endometriosis leads to CPP through chronic inflammation, continuous peripheral nerve stimulation, and enhancement of central sensitization. The relationship between pregnancy and endometriosis is complex. Pregnancy has been proposed as a possible risk for developing CPP. However, amenorrhea has been thought to be protective against endometriosis. For fertility, endometriosis causes infertility mainly through distortion of reproductive anatomy with endometrioma and pelvic adhesions. Although endometrioma can be diagnosed with transvaginal ultrasound and sliding sign can evaluate adhesions in the posterior uterine compartment, the only way to estimate the pregnancy rate is by calculating the endometriosis fertility index (EFI). EFI calculation during laparoscopy provides a score between 0 and 10 (10 is associated with the best fertility prognosis while a score of 0 associated with the poorest fertility prognosis). In this thesis, I conducted two cross-sectional studies using a prospectively collected registry. In the first study, I compared the severity of pelvic pain between three groups of women: a group of nulligravid women (n=686), a group of parous women (n=371), and a group of women with a history of miscarriage or abortion (n=129). I found a higher number of women in the parous group had severe CPP. The nulligravid group had a higher rate of severe dysmenorrhea. Ordinal regression with backward elimination methods showed a strong association between parity and severe CPP (AOR= 1.448, 95%CI=1.092–1.918, P=0.010). In the second study, I divided infertile endometriosis patients into two groups based on the sliding sign results. The sliding sign is considered negative when the sliding motion is not observed between the colon and cervix or uterus. I found that participants with a negative sliding sign (n=26) had significantly lower total EFI scores and a lower score for each surgical factor than patients with positive sliding sign (n=60). Logistic regression showed that an EFI score of < 7 can be predicted using the negative sliding sign and EFI historical factors, with a high sensitivity of 87.9% and specificity of 81.1%; the area under the curve was 0.93 (95% CI = 0.88–0.98).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".