In Therapeutic advances in gastroenterology
Endoscopic retrograde cholangiopancreatography (ERCP) is an advanced endoscopic procedure that might lead to severe adverse events. Post-ERCP pancreatitis (PEP) is the most common post-procedural complication, which is related to significant mortality and increasing healthcare costs. Up to now, the prevalent approach to prevent PEP consisted of employing pharmacological and technical expedients that have been shown to improve post-ERCP outcomes, such as the administration of rectal nonsteroidal anti-inflammatory drugs, aggressive intravenous hydration, and the placement of a pancreatic stent. However, it has been reported that PEP originates from a more complex interaction of procedural and patient-related factors. Appropriate ERCP training has a pivotal role in PEP prevention strategy, and it is not a chance that a low PEP rate is universally considered one of the most relevant indicators of proficiency in ERCP. Scant data on the acquisition of skills during the ERCP training are currently available, although some efforts have been recently done to shorten the learning curve by way of simulation-based training and demonstrate competency by meeting technical requirements as well as adopting skill evaluation scales. Besides, the identification of adequate indications for ERCP and accurate pre-procedural risk stratification of patients might help to reduce PEP occurrence regardless of the endoscopist's technical abilities, and generally preserve safety in ERCP. This review aims at delineating current preventive strategies and highlighting novel perspectives for a safer ERCP focusing on the prevention of PEP.
Borrelli de Andreis Federica, Mascagni Pietro, Schepis Tommaso, Attili Fabia, Tringali Andrea, Costamagna Guido, Boškoski Ivo
2023
Artificial Intelligence (D001185), Cholangiopancreatography, Education (D004493), Endoscopic Retrograde (D002760), Machine Learning (D000069550), Medical (D004501), Pancreatitis (D010195), Risk Factors (D012307), prevention and control (Q000517)
