ArticleCureus2023
Severe Acute Pancreatitis Prediction: A Model Derived From a Prospective Registry Cohort.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed.
- Prediction of Severe Acute Pancreatitis at a Very Early Stage of the Disease Using Artificial Intelligence Techniques, Without Laboratory Data or Imaging Tests: The PANCREATIA Study.Annals of surgery · 2026Article
- Deep learning-based prediction of acute pancreatitis severity from abdominal CT with multicenter external validation.Radiology advances · 2026Article
- Acute pancreatitis: mechanisms and therapeutic approaches.Signal transduction and targeted therapy · 2026Review
- EASIX as a moderately effective prognostic marker for mortality in severe acute pancreatitis: a retrospective study.Frontiers in medicine · 2026Article
- Development and validation of a nomogram for predicting 30-day mortality in patients with severe acute pancreatitis and pneumonia.Scientific reports · 2025Article
- Additional considerations on a combination of inflammatory markers and scoring systems for early severity stratification of acute pancreatitis.World journal of gastroenterology · 2025Article
- Diagnostic and therapeutic management of severe acute pancreatitis. Evidence based medicine (EBM) clinical practice guidelines.Wideochirurgia i inne techniki maloinwazyjne = Videosurgery and other miniinvasive techniques · 2025Article
- Comparative Analysis of Laboratory Markers, Severity Scores, and Outcomes in 179 Patients with Severe Acute Pancreatitis.Biomedicines · 2025Article
- Predictive value of machine learning for the severity of acute pancreatitis: A systematic review and meta-analysis.Heliyon · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Severe acute pancreatitis (SAP) has a mortality rate as high as 40%. Early identification of SAP is required to appropriately triage and direct initial therapies. The purpose of this study was to develop a prognostic model that identifies patients at risk for developing SAP of patients managed according to a guideline-based standardized early medical management (EMM) protocol. Methods This single-center study included all patients diagnosed with acute pancreatitis (AP) and managed with the EMM protocol Methodist Acute Pancreatitis Protocol (MAPP) between April 2017 and September 2022. Classification and regression tree (CART®; Professional Extended Edition, version 8.0; Salford Systems, San Diego, CA), univariate, and logistic regression analyses were performed to develop a scoring system for AP severity prediction. The accuracy of the scoring system was measured by the area under the receiver operating characteristic curve. Results A total of 516 patients with mild (n=436) or moderately severe and severe (n=80) AP were analyzed. CART analysis identified the cutoff values: creatinine (CR) (1.15 mg/dL), white blood cells (WBC) (10.5 × 10
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