A114 DEVELOPING AND VALIDATING A PATIENT RISK ASSESSMENT TOOL TO PREDICT POST-ERCP PANCREATITIS
Notice bibliographique
Résumé
Abstract Background Post-ERCP pancreatitis (PEP), the most common complication of ERCP, can lead to significant patient morbidity and even mortality. Both American (ASGE) and European (ESGE) guidelines emphasize the importance of assessing PEP risk among patients about to undergo ERCP so appropriate preventative measures can be initiated. Though multiple PEP risk factors have been identified, an ideal risk assessment tool has not yet been developed that accurately predicts PEP risk among ERCP patients. An ideal PEP risk factor screening tool would be one that most sensitively identifies patients likely to benefit from PEP preventative measures. We have developed a patient PEP risk screening tool based on both ASGE and ESGE guidelines (Table 1) and analyzed its accuracy predicting PEP rates in our clinical practice. Aims We investigated whether the ERCP patient and procedural risk factors listed in the ASGE and ESGE guidelines were linked to PEP rates using a novel PEP risk screening tool in patients undergoing ERCP. Methods Retrospective chart reviews of patients undergoing ERCP were performed within a single clinician’s practice at the London Health Science Centre, Victoria Hospital, between January 2016 and October 2019 to: 1) assess the proportion of patients identified as high PEP risk using our novel PEP risk screening tool; 2) determine whether a high PEP risk score using this tool was linked to higher PEP rates following ERCP; and 3) identify the absolute score threshold that best delineates patients at higher risk. A chi-square test of independence was performed to examine the relationship between high PEP risk identified via screening and the actual PEP rate following ERCP. Results Five hundred sixty-one patients who underwent ERCP were assessed using the new PEP risk screening tool. Among those patients, 6.6% (37/561) developed post-ERCP pancreatitis. Using the screening tool, 79.5% (446/561) were identified as high risk, using a cut-off score of 1; the score with the highest sensitivity (95%) and specificity (22%) combination. Identifying high PEP risk patients at this cut-off was significantly linked to increased PEP rates in patients who underwent ERCP (X2 = 5.5; df = 1, p < .05). Conclusions Using a cut-off score of 1, the PEP risk screening tool was very sensitive, but relatively non-specific at identifying patients who went on to develop post-ERCP pancreatitis. We hope that, based on these findings, high-risk patient identification can be improved, so more aggressive and appropriately-targeted prophylactic measures against PEP can be provided. Funding Agencies None
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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 | 0,001 | 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 ».