Effet de l’injection de gel sous-muqueux sur le taux de résection incomplète des polypes non-pédonculés de 4 à 20 mm et analyse du taux de récidive des polypes non-pédonculés de taille supérieure ou égale à 20 mm post-EMR h-APC
Bibliographic record
Abstract
Globally, colorectal cancer (CRC) was the third most diagnosed type of cancer and the second leading cause of cancer death in 2020. In Canada, CRC was the second leading cause of cancer death in men and the third leading cause of cancer death in women in 2021. In order to reduce the incidence of CRC, colonoscopies are needed to detect and resect any precancerous lesions. Missed lesions, incomplete detection due to inadequate examination (e.g., poor bowel preparation, failed cecal intubation), incomplete resection of colorectal polyps, and newly developed CRC have been highlighted as some of the major risk factors for the development of postpolypectomy CRC in patients 6 to 60 months after colonoscopy. Complete endoscopic resection of polyps is important to reduce the incidence of postpolypectomy CRC. Complete endoscopic resection of polyps and appropriate polypectomy and ablation techniques are paramount to reduce the incidence of post-polypectomy CRC. There are several different methods of resecting polyps depending on the size, morphology and invasion of the polyps in question. For this reason, this dissertation was written and based on two clinical studies investigating two different techniques. The main objectives are to evaluate two polypectomy techniques, namely cold snare polypectomy in conjunction with submucosal injection (CSP-SI), and mucosal endoscopic resection (EMR) in conjunction with hybrid argon plasma coagulation (h-APC) to prevent the incidence of CRC. After reviewing the literature, two prospective multi-endoscopist studies were conducted to examine each polypectomy method. The first study evaluated the incomplete resection rate of 4-20 mm nonpedunculated polyps following CSP-SI polypectomy in patients aged 45 to 80 years referred for elective colonoscopy at the Centre Hospitalier de l'Université de Montréal (CHUM). The second study evaluated the post-EMR and h-APC recurrence rate of nonpedunculated colorectal polyps measuring more than 20 mm in patients aged 18 to 89 years 6 months after the initial procedure at two research centers (Penn State Hershey Medical Centre and CHUM).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".