EP24.26: Using the IDEA consensus ‘pulling sleeve’ sign to guide surgical decisions
Bibliographic record
Abstract
Transvaginal ultrasound (TVS) has a sensitivity of 89% and specificity of 97% for detecting of bowel endometriosis (BE). When surgery is decided, a choice between shaving technique (ST), disc resection or segmental resection is needed, making preoperative TVS crucial. The six descriptors of BE as per the International Deep Endometriosis Analysis (IDEA) group have not proven to be useful in guiding surgical decisions. We hypothesise that the ‘pulling sleeve’ sign (PSS) is a good predictor of when to use a ST. Iterative TVS and laparoscopic surgery enhanced our understanding of this particular form of BE. We present PSS as seen on TVS and the surgical correlation. On TVS, we can appreciate the outer longitudinal muscularis layer involvement with preservation of the inner circular muscularis layer (CML). This critical landmarking can be used in surgical planning when considering ST, as this is the least invasive technique with lowest complication rates. The PSS indicates a triangular-shaped BE nodule that also yields an extrinsic reaction, focally ethering the bowel (see figure 1). We have generally noted a preserved hyperechoic line in the muscularis propria demarcating the longitudinal and circular layers (see figure 2). Preservation of this line suggests integrity of CML, enabling a ST without enterotomy as an appropriate surgical approach. An accompanying videoclip will showcase preoperative TVS findings of PSS and laparoscopic footage of BE shaving excision (see figure 3). If the hyperechoic line is not preserved, this indicates involvement of CML, which likely suggests the BE lesion might not be amenable to the ST. Further studies are needed to evaluate reliability and accuracy of this sign for predicting a ST. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.057 | 0.031 |
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".