A208 OPTIMIZING THE UTILITY OF CT ENTEROGRAPHY FOR THE EVALUATION OF OBSCURE GASTROINTESTINAL BLEEDING: A NOVEL HIGHLY SENSITIVE CLINICAL PREDICTION TOOL
Notice bibliographique
Résumé
Computed tomography (CTE) and capsule endoscopy (CE) are common modalities used to investigate obscure GI bleeds (OGIB). Although recent guidelines recommend CE before CTE as the first modality to evaluate OGIB, CTE offers multiple advantages including lower cost, greater availability, and the ability to detect strictures, masses, and extraluminal pathology. It is not yet clear which OGIB patients would most benefit from CTE before CE. Our study sought to determine patient factors associated with positive CTE in OGIB patients to develop a novel clinical decision tool to predict which patients are more likely versus less likely to have a diagnostic CTE. This was a retrospective study using patients who underwent CTE for OGIB defined as a suspected gastrointestinal (GI) bleed with no cause identified on gastroscope or colonoscopy at The Ottawa Hospital between 2005- 2015. Factors (symptoms, history, investigations, interventions, outcomes) selected a priori from literature review were collected by chart review. Logistic regression with univariate and multivariate analysis were performed to identify factors associated with a positive CTE study. Of 147 patients with OGIB, CTE was positive in 1 in 5 cases (n=31, 21%). 22 (71%) of the CTE positive cases had at least one of intestinal wall thickening, angiodysplasias, suspected bowel mass, or concerning stricture. The presence of overt GI bleeding (OR 12.4, 95% CI 1.6–95.0), abdominal or constitutional symptoms (OR 2.9, 95% CI 1.2–7.0), or a personal history of GI cancer (OR 17.5, 95% CI 1.9–163.5) were factors that predicted a positive CTE study with univariate analysis. This was also seen in multivariate analysis (OR 13.3, 95% CI 1.5–121.9; OR 2.5, 95% CI 1.0–6.6; OR 30.3, 95% CI 1.4–634.2 respectively). Absence of these 3 factors was associated with zero likelihood of having a positive CTE, while presence of any of these factors was associated with a 1 in 4 likelihood of having a positive CTE. A rule based on the absence of these factors for predicting a positive CTE would have a sensitivity, specificity, negative predictive value, and positive predictive value of 100% (95% CI 80–100%), 16% (95% CI 10–24%), 100%, and 24% (95% CI 23–26%) respectively. CTE can be diagnostic in 1 in 5 cases of OGIB. Diagnostic yield may be greater for patients with overt GI bleeding, abdominal and/or constitutional symptoms, or a personal history of GI malignancy. Absence of these 3 factors was associated with zero likelihood of a positive CTE. Together, these factors can function as a highly sensitive tool to predict which OGIB patients are unlikely to have a diagnostic CTE. This can potentially reduce non-diagnostic CTE and avoid the need for CE. Future research to validate this tool in other populations with OGIB are needed. None
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 | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».