P119 There is minimal agreement on the recognition of deep ulcers as seen on endoscopy in patients with Inflammatory Bowel Disease: a national survey
Notice bibliographique
Résumé
Abstract Background Deep ulcers have been described as a marker of severe disease phenotype in patients with IBD and play a role in choice or escalation of therapy. However, there is no agreed upon characterization of deep ulcers in the literature. We therefore assessed Canadian gastroenterologists’ ability to identify the presence of deep ulcers on endoscopic images. Methods We present a post-hoc analysis of a cross-sectional questionnaire from gastroenterologists across Canada (March-October 2017). Three IBD experts independently rated 20 ileocolonoscopy images of single bowel segments. They described the images by selecting descriptors from a list developed a priori. Images described by all 3 experts as having “deep ulcers” were retained for analysis (5 images). Survey participants similarly applied descriptors from the same list to each endoscopy image. We examined the percent agreement between the gastroenterologists and the experts. The percent agreement for each question was summarized using median and IQR. Difference in median scores in physician subgroups was determined using the Mann-Whitney U test. We also assessed the inter-observer agreement on the presence of deep ulcers amongst gastroenterologists using Fleiss Kappa. Results 131 gastroenterologists participated in the study. The majority (55.7%) were between 36–50 years old. 48% were in practice for less than 10 years. 59.5% practiced in an academic setting. 9.9% of responders were pediatric gastroenterologists. The median agreement between the gastroenterologists and the experts was 30.5% (30.5–76.3), indicating an under-recognition of deep ulcers. As a group, inter-observer agreement on the presence of deep ulcers was minimal (k = 0.39, CI: 0.16–0.65). Inter-observer agreement was lower in the academic setting than the community setting (k= 0.39 vs k= 0.49 respectively) and was fairly similar in those with more experience compared to those with less experience (k= 0.40 for less than 10 years in practice, vs k= 0.36 for those with greater than 10 years in practice). Compared to the experts’ responses, there was no significant difference if the physician practiced in an academic vs community setting (49.24% correct identification vs 54.52%, p = 0.6004) or if the physician had less than 10 years’ experience vs greater than 10 years’ experience (48.26% vs 53.44%, p =0.2948). Conclusion Deep ulcers have been described as a critical indicator of disease severity in patients with IBD. However, our study shows that there is poor agreement between physicians in identifying this important feature. This indicates the need for a standardized definition of deep ulcers to prevent undertreatment of patients who require escalated therapy.
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 | 0,004 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».