A126 ASSESSING THE QUALITY OF REFERRALS AND ADJUDICATION FOR ENDOSCOPIC RESECTION OF LARGE COLORECTAL POLYPS AT A CANADIAN TERTIARY REFERRAL CENTRE
Notice bibliographique
Résumé
Abstract Background Management of large colorectal polyps is increasingly complex with the expansion of endoscopic techniques, including endoscopic submucosal dissection (ESD), endoscopic mucosal resection (EMR), and endoscopic full thickness resection. Adjudicating lesions in an effort to select the optimal resection method is hugely dependent on the information included within the referral. At our institution, a referral pathway based on photo and/or video documentation was created to facilitate the timely assessment and treatment of large colorectal polyps. To date, little is known about quality of referrals for endoscopic resection of large colorectal polyps. Purpose Our study aimed to assess the adjudication process and quality of referrals for endoscopic resection of large colorectal polyps at our advanced endoscopy referral center. Method We conducted a single-center prospective study of consecutive colorectal polyps referred for EMR from March 2021 to March 2022. Cases selected upfront for ESD were excluded. Referral information, intraprocedural data and histology was captured. No procedural and histology data were captured if EMR does not occur after adjudication. The outcome was defined as the frequency of adequate referrals. A referral was deemed adequate if it contained: sufficient photo or video documentation, description of any characteristics that increase the difficulty of endoscopic resection, accurate polyp localization/size estimate (with <1 cm discrepancy when compared to real-time endoscopic evaluation), and description of any endoscopic features of advanced dysplasia (AD), including HGD/IMCa, or submucosal invasion (SMI). Result(s) During the study period, 213 referrals were received for colorectal polyps and underwent adjudication for EMR: 211 underwent EMR; 2 underwent ESD despite being triaged for EMR. Only 5% (10/213) of referrals were deemed to be adequate. Only 34% (73/213) contained any photo or video documentation and only 13% (28/213) photos/videos were of sufficient quality for adjudication. Difficult location or polyp characteristics, if present, were accurately described in 86.7% of referrals (183/211) of referrals. The accurate polyp location was described 80.6% of the time (170/211). Polyp size was estimated in 50.2% (107/213) of referrals. Amongst referrals with size estimated, the size was accurate in 73.8% of the time (79/107). On histological evaluation, 35.1% (74/211) of polyps had AD or SMI. Amongst polyps with AD or SMI, 48.6% (36/74) had endoscopic appearance suggestive of HGD/IMCa/SMI but only 69.4% (25/36) of these polyps with high-risk endoscopic features were accurately predicted based on the referral information. Conclusion(s) Referrals for large colorectal polyps often lack important clinical information. This significantly impairs the ability to adjudicate polyps for triage and resection and may negatively impact patient outcomes. To improve referral adequacy and patient outcomes, we plan to evaluate the impact of polyp adjudication on EMR success. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,006 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».