Internal Hernia after Laparoscopic Roux-en-Y Gastric Bypass: Optimal CT Signs for Diagnosis and Clinical Decision Making
Notice bibliographique
Résumé
Purpose To evaluate the accuracy of computed tomography (CT) for diagnosis of internal hernia (IH) in patients who have undergone laparoscopic Roux-en-Y gastric bypass and to develop decision tree models to optimize diagnostic accuracy. Materials and Methods This was a retrospective, ethics-approved study of patients who had undergone laparoscopic Roux-en-Y gastric bypass with surgically confirmed IH (n = 76) and without IH (n = 78). Two radiologists independently reviewed each examination for the following previously established CT signs of IH: mesenteric swirl, small-bowel obstruction (SBO), mushroom sign, clustered loops, hurricane eye, small bowel behind the superior mesenteric artery, and right-sided anastomosis. Radiologists also evaluated images for two new signs, superior mesenteric vein (SMV) “beaking” and “criss-cross” of the mesenteric vessels. Overall impressions for diagnosis of IH were recorded. Diagnostic accuracy and interobserver agreement were calculated, and multivariate recursive partitioning was performed to evaluate various decision tree models by using the CT signs. Results Accuracy and interobserver agreement regarding the nine CT signs of IH showed considerable variation. The best signs were mesenteric swirl (sensitivity and specificity, 86%–89% and 86%–90%, respectively; κ = 0.74) and SMV beaking (sensitivity and specificity, 80%–88% and 94%–95%, respectively; κ = 0.83). Overall reader impression yielded the highest sensitivity and specificity (96%–99% and 90%–99%, respectively; κ = 0.79). The decision tree model with the highest overall accuracy and sensitivity included mesenteric swirl and SBO, with a diagnostic odds ratio of 154 (95% confidence interval [CI]: 146, 161), sensitivity of 96% (95% CI: 87%, 99%), and specificity of 87% (95% CI: 75%, 93%). The decision tree with the highest specificity included SMV beaking and SBO, with a diagnostic odds ratio of 105 (95% CI: 101, 109), sensitivity of 90% (95% CI: 79%, 95%), and specificity of 92% (95% CI: 83%, 97%). Conclusion The decision tree with the highest accuracy and sensitivity for diagnosis of IH included mesenteric swirl and SBO, the model with the highest specificity included SMV beaking and SBO, and the remaining signs showed lower accuracy and/or poor to fair interobserver agreement. Overall reader impression yielded the highest accuracy for diagnosis of IH, likely because alternate diagnoses not incorporated in the models were considered. © RSNA, 2016 Online supplemental material is available for this article.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».