OC09.06: Update on the distribution of ovarian and deep endometriosis based on combination of advanced pelvic ultrasound and surgery
Bibliographic record
Abstract
An up-to-date description of ovarian and deep endometriosis distribution is necessary as the diagnostic algorithm now includes ultrasound as a highly specific diagnostic test. The primary objective was to describe ovarian/deep endometriosis distribution based on the combination of ultrasound, surgery, and pathology. The secondary objective was to determine if a certain location at surgery had a higher correlation with histopathology-confirmed endometriosis. 145 consecutive patients underwent ultrasound and surgery by one of two gynecologists in a tertiary care centre between October 2020-January 2023. All endometriosis lesions were excised unless otherwise decided by the patient. Standard ultrasound/surgery reports were reviewed, and data extracted. Chi-Square Tests and Pearson's correlation coefficients were calculated to define the correlation between surgical diagnosis and pathology diagnosis for each anatomical location. When combining findings from preoperative ultrasound, surgery and pathology, the most frequent locations for deep disease were uterosacral ligaments (51.0%), ovaries (45.5%), torus uterinus (19.3%) and bowel (17.2%). Deep endometriosis was more common on the left versus right uterosacral ligament (42.7% vs. 34.5%) and on the left versus right ovary (33.8% vs. 26.9%). Amongst patients with ovarian endometriosis, 74.2% had deep endometriosis in at least one other site. There was a significant association between surgically identified lesions and pathology confirmation for all locations (Chi-Square Test, p < 0.05). The correlation was strong for all locations (Pearson's coefficient 0.70-0.90, p < 0.05). The addition of advanced pelvic ultrasound to the diagnostic approach of patients with deep endometriosis allows for a more accurate description of disease distribution, combining ultrasound, surgical and pathological findings. In our cohort, we describe the most common locations for deep endometriosis as the uterosacral ligaments followed by the ovaries and the torus uterinus.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.018 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".