Objective:To generate an up-to-date bundle to manage acute biliary pancreatitis using an evidence-based, artificial intelligence (AI)-assisted GRADE method.Background:A care bundle is a set of core elements of care that are distilled from the most solid evidence-based practice guidelines and recommendations.Methods:The research questions were addressed in this bundle following the PICO criteria. The working group summarized the effects of interventions with the strength of recommendation and quality of evidence applying the GRADE methodology. ChatGPT AI system was used to independently assess the quality of evidence of each element in the bundle, together with the strength of the recommendations.Results:The 7 elements of the bundle discourage antibiotic prophylaxis in patients with acute biliary pancreatitis, support the use of a full-solid diet in patients with mild to moderately severe acute biliary pancreatitis, and recommend early enteral nutrition in patients unable to feed by mouth. The bundle states that endoscopic retrograde cholangiopancreatography should be performed within the first 48 to 72 hours of hospital admission in patients with cholangitis. Early laparoscopic cholecystectomy should be performed in patients with mild acute biliary pancreatitis. When operative intervention is needed for necrotizing pancreatitis, this should start with the endoscopic step-up approach.Conclusions:We have developed a new care bundle with 7 key elements for managing patients with acute biliary pancreatitis. This new bundle, whose scientific strength has been increased thanks to the alliance between human knowledge and AI from the new ChatGPT software, should be introduced to emergency departments, wards, and intensive care units.
Podda, M., Di Martino, M., Ielpo, B., Catena, F., Coccolini, F., Pata, F., et al. (2024). The 2023 MANCTRA Acute Biliary Pancreatitis Care Bundle. ANNALS OF SURGERY, 279(2), 203-212 [10.1097/sla.0000000000006008].
The 2023 MANCTRA Acute Biliary Pancreatitis Care Bundle
Catena, Fausto;Coccolini, Federico;Kluger, Yoram;Di Saverio, Salomone;
2024
Abstract
Objective:To generate an up-to-date bundle to manage acute biliary pancreatitis using an evidence-based, artificial intelligence (AI)-assisted GRADE method.Background:A care bundle is a set of core elements of care that are distilled from the most solid evidence-based practice guidelines and recommendations.Methods:The research questions were addressed in this bundle following the PICO criteria. The working group summarized the effects of interventions with the strength of recommendation and quality of evidence applying the GRADE methodology. ChatGPT AI system was used to independently assess the quality of evidence of each element in the bundle, together with the strength of the recommendations.Results:The 7 elements of the bundle discourage antibiotic prophylaxis in patients with acute biliary pancreatitis, support the use of a full-solid diet in patients with mild to moderately severe acute biliary pancreatitis, and recommend early enteral nutrition in patients unable to feed by mouth. The bundle states that endoscopic retrograde cholangiopancreatography should be performed within the first 48 to 72 hours of hospital admission in patients with cholangitis. Early laparoscopic cholecystectomy should be performed in patients with mild acute biliary pancreatitis. When operative intervention is needed for necrotizing pancreatitis, this should start with the endoscopic step-up approach.Conclusions:We have developed a new care bundle with 7 key elements for managing patients with acute biliary pancreatitis. This new bundle, whose scientific strength has been increased thanks to the alliance between human knowledge and AI from the new ChatGPT software, should be introduced to emergency departments, wards, and intensive care units.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.