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Record W4379617855 · doi:10.1055/a-2077-0497

Curriculum for training in endoscopic mucosal resection in the colon: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement

2023· article· en· W4379617855 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEndoscopy · 2023
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsOttawa HospitalUniversity of OttawaUniversity of Calgary
Fundersnot available
KeywordsMedicinePolypectomyEndoscopic mucosal resectionColonoscopyEndoscopyCompetence (human resources)General surgerySurgeryMedical physicsColorectal cancerInternal medicineCancer

Abstract

fetched live from OpenAlex

Endoscopic mucosal resection (EMR) is the standard of care for the complete removal of large (≥ 10 mm) nonpedunculated colorectal polyps (LNPCPs). Increased detection of LNPCPs owing to screening colonoscopy, plus high observed rates of incomplete resection and need for surgery call for a standardized approach to training in EMR. 1 : Trainees in EMR should have achieved basic competence in diagnostic colonoscopy, < 10-mm polypectomy, pedunculated polypectomy, and common methods of gastrointestinal endoscopic hemostasis. The role of formal training courses is emphasized. Training may then commence in vivo under the direct supervision of a trainer. 2 : Endoscopy units training endoscopists in EMR should have specific processes in place to support and facilitate training. 3: A trained EMR practitioner should have mastered theoretical knowledge including how to assess an LNPCP for risk of submucosal invasion, how to interpret the potential difficulty of a particular EMR procedure, how to decide whether to remove a particular LNPCP en bloc or piecemeal, whether the risks of electrosurgical energy can be avoided for a particular LNPCP, the different devices required for EMR, management of adverse events, and interpretation of reports provided by histopathologists. 4: Trained EMR practitioners should be familiar with the patient consent process for EMR. 5: The development of endoscopic non-technical skills (ENTS) and team interaction are important for trainees in EMR. 6: Differences in recommended technique exist between EMR performed with and without electrosurgical energy. Common to both is a standardized technique based upon dynamic injection, controlled and precise snare placement, safety checks prior to the application of tissue transection (cold snare) or electrosurgical energy (hot snare), and interpretation of the post-EMR resection defect. 7: A trained EMR practitioner must be able to manage adverse events associated with EMR including intraprocedural bleeding and perforation, and post-procedural bleeding. Delayed perforation should be avoided by correct interpretation of the post-EMR defect and treatment of deep mural injury. 8: A trained EMR practitioner must be able to communicate EMR procedural findings to patients and provide them with a plan in case of adverse events after discharge and a follow-up plan. 9: A trained EMR practitioner must be able to detect and interrogate a post-endoscopic resection scar for residual or recurrent adenoma and apply treatment if necessary. 10: Prior to independent practice, a minimum of 30 EMR procedures should be performed, culminating in a trainer-guided assessment of competency using a validated assessment tool, taking account of procedural difficulty (e. g. using the SMSA polyp score). 11: Trained practitioners should log their key performance indicators (KPIs) of polypectomy during independent practice. A guide for target KPIs is provided in this document.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.328
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it