A simple core dataset for triglyceride-induced acute pancreatitis. (2nd January 2023)

• Record Type: Journal Article
• Authors: Freedman, Steve; de-Madaria, Enrique; Singh, Vikesh K.; Bruckert, Eric; Löhr, Matthias; Sutton, Robert; Rebours, Vinciane; Jones, Richard; Jandhyala, Ravi
• Is Part Of: Current medical research and opinion. Volume 39:Number 1(2023)
• Page Start: 37
• Page End: 46
• Publication Date: 2023-01-02
• Subjects: Triglyceride -- acute pancreatitis -- core dataset -- diagnosis and monitoring -- disease severity; Clinical medicine -- Periodicals; Therapeutics -- Periodicals; 615.5
• DOI: 10.1080/03007995.2022.2144054
• Languages: English
• ISSNs: 0300-7995

Abstract

Abstract: Objective: The objective of this study is to generate a core clinical dataset (CD) containing the minimum acceptable amount of information that should be collected for each patient presenting with triglyceride-induced acute pancreatitis within global treatment centres or sites. Method: The Jandhyala Method, including systematic literature review and SMART interviews, was used to observe expert opinion from ten leaders in the treatment of triglyceride-induced acute pancreatitis (TG-IAP) across the US and EU. Results: Using the PRISMA Literature Review Protocol, data were extracted from 123 of the 6718 identified studies. A total of 243 items were identified from the data extracted from these studies and, combined with the unique items coded from the Awareness Round (1) survey, formed the Consensus Round (2) survey. One hundred and ninety-five of the 243 items (80%) met the consensus threshold and were included for appraisal in the SMART interview phase. A total of 109 items were agreed to form part of the current clinical diagnostic and monitoring procedure by all experts once the weights across all the stakeholder disciplines were balanced to eliminate bias. These items were further condensed to form the core dataset, comprising a total of 87 items. Conclusion: Once validated and adopted, the TG-IAP CD will improve the overall management of patients with TG-IAP by speeding up diagnosis and detecting changes in disease severity and subsequent disease progression, informing personalized patient management plans, and improving patient outcomes.