A126 ONCE IS BY CHANCE, TWO IS A TREND: A RECURRING FINDING WITHIN THE POST-RESECTION DEFECT
Bibliographic record
Abstract
Abstract Background A 74-year-old male was referred for the management of a large non-pedunculated colorectal polyp in the transverse colon. On optical evaluation, including high-definition white-light and narrow-band imaging (NBI), a 30mm 0-IIA non-granular large non-pedunculated colorectal polyps (LNPCP) was identified with optical features in keeping with adenomatous histopathology (NBI International Colorectal Endoscopic II, Japan NBI Expert Team IIA, Kudo Pit Pattern III/IV). Endoscopic mucosal resection (EMR) was performed. During sequential tissue transection and evaluation of the expanding submucosal defect a hole with a surrounding white-cautery ring was identified in keeping with significant deep mural injury. However, on careful evaluation a cystic structure was identified with a viscous amorphous substance emanating from it. Endoscopic resection of the lesion was completed with subsequent through-the-scope mechanical clip closure of the area of concern. Aims case report showing unique finding of intra-cellular mucin emanating from the post-resection defect has been identified as a potential intra-procedural finding of a mucinous adenocarcinoma Methods Endoscopic mucosal resection of a mid transverse colon polyp Results Histopathology identified a villous adenoma with high-grade dysplasia with submucosal mucin and an indeterminate focus of carcinoma; highly suspicious for a mucinous adenocarcinoma. No muscularis propria was identified. After multi-disciplinary review, the patient underwent laparoscopic right hemicolectomy with no evidence of invasive disease. Conclusions Recently coined as the “fish-eye” polypectomy defect, intra-cellular mucin emanating from the post-resection defect has been identified as a potential intra-procedural finding of a mucinous adenocarcinoma; specifically, in an otherwise benign appearing LNPCP based on real-time optical evaluation. Herein we describe the second case in the literature. This reinforces the importance of meticulous evaluation of the post-resection defect to stratify this finding from deep mural injury. Moreover, further understanding of the clinical ramifications of this unique intra-procedural finding is needed. Funding Agencies None
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".