S404 Quality Indicator Development for the Approach to Ineffective Esophageal Motility: A Modified Delphi Study
Notice bibliographique
Résumé
Introduction: Ineffective esophageal motility (IEM) is identified in up to 30% of patients undergoing esophageal high resolution manometry (HRM) based on the Chicago Classification version 4.0. The clinical significance of this pattern is not established and management remains challenging due to a limited framework guiding gastroenterologists when IEM is identified. Aim: To establish quality indicators for approaching IEM when identified on esophageal HRM. Methods: Using RAND/University of California, Los Angeles (UCLA) Appropriateness Methods, we employed a modified-Delphi approach for quality indicator statement development. Quality indicators were proposed based on prior literature. Experts independently and blindly scored proposed quality statements on importance, scientific acceptability, usability, and feasibility in a three-round iterative process. Highly valid quality indicators reached scores with ≥80% agreement in the 7-9 range (on a 9-point Likert scale) across all four categories. Results: There were 10 experts in the management of esophageal diseases invited to participate and all (100%) rated 12 proposed quality indicator statements. In round one, 7 (58.3%) quality indicators were rated with mixed agreement (< 80% agreement across all four categories). Statements were modified based on panel suggestion, modified further following round two’s virtual discussion, and in round three voting identified 2 highly valid quality indicators, 4 moderately valid, and 1 invalid. In total, 2 (16.7%) quality indicators reached high validity. The panel agreed on the concept of determining if IEM is clinically relevant to the patient’s presentation and managing GERD rather than the IEM pattern (Table). The panel disagreed in all four domains on the use of promotility agents (e.g., prucalopride, metoclopramide) in IEM, and had mixed agreement that IEM with contraction reserve on pre-operative HRM can be viewed similar to a manometric pattern without IEM specific to anti-reflux surgery, probably reflecting the lack of solid scientific evidence on this pattern. Conclusion: Using a robust methodology, two IEM quality indicators were identified. These quality indicators can track performance when physicians identify this manometric pattern on HRM with the goal of ultimately improving patient outcomes. This study further highlights the challenges met with IEM, and the need for additional research to better understand the clinical importance of this manometric pattern. Table 1. - Proportion of Expert Agreement on Proposed Quality Indicators: Round #2 Proportion Agreement (%) with high validity Statements Importance Scientific Acceptability Usability Feasibility IF a high resolution esophageal manometry reveals >70% ineffective swallow sequences then the manometric pattern is consistent with IEM 60 60 90 100 IF a high resolution esophageal manometry reveals >= 50% 50 60 90 100 IF a patient’s high resolution esophageal manometry reveals IEM, THEN a member of the care team should assess if the manometric pattern is clinically relevant. 90 80 80 100 IF a patient’s high resolution esophageal manometry reveals IEM, THEN a member of the care team should communicate the clinical relevance of this manometric pattern to the patient. 80 70 60 90 IF a patient has gastroesophageal reflux disease (GERD) and a manometric pattern of IEM, THEN control of GERD is the main approach to patient management. 90 80 90 100 IF a patient with a manometric pattern of IEM and contractile reserve on pre-operative high resolution esophageal manometry is being considered for anti-reflux surgery, THEN surgical management should not differ from a patient without IEM. 40 50 60 60 IF a patient with a manometric pattern of IEM and absent contractile reserve on pre-operative high resolution esophageal manometry is being considered for anti-reflux surgery, THEN the care team should discuss the increased risks of post-operative dysphagia. 70 60 60 80
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 | 0,152 | 0,142 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,002 |
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 ».