ArticleBMC gastroenterology2022
Identification of early predictors for infected necrosis in acute pancreatitis.
Article in BMC gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Neutrophil-to-lymphocyte ratio for primary risk stratification in acute pancreatitis: a systematic review and meta-analysis.Frontiers in medicine · 2025Pooled it
- Persistently High Procalcitonin and C-Reactive Protein Are Good Predictors of Infection in Acute Necrotizing Pancreatitis: A Systematic Review and Meta-Analysis.International journal of molecular sciences · 2024Pooled it
- Predicting infected pancreatic necrosis in acute pancreatitis using machine learning models and feature selection.Scientific reports · 2026Article
- Inflammation, Organ Failure, and the Path to Surgery in Acute Pancreatitis.Medicina (Kaunas, Lithuania) · 2026Article
- Acute pancreatitis: mechanisms and therapeutic approaches.Signal transduction and targeted therapy · 2026Review
- Epidemiology, etiopathogenesis, immune response, diagnosis, and complications of acute pancreatitis: current insights.Annals of medicine · 2025Review
- Prediction of infected pancreatic necrosis in patients with acute necrotizing pancreatitis based on ensemble machine learning model.World journal of emergency surgery : WJES · 2025Article
- Endoscopic management of infected necrotizing pancreatitis: Advancing through standardization.World journal of gastroenterology · 2025Review
- 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
- Predicting mortality in intensive care unit patients with acute pancreatitis using an interpretable machine learning model.Frontiers in medicine · 2025Article
- Early clinical predictors of infected pancreatic necrosis: a multicentre cohort study.eGastroenterology · 2024Article
- Predictive value of machine learning for the severity of acute pancreatitis: A systematic review and meta-analysis.Heliyon · 2024Article
- Management of infected acute necrotizing pancreatitis.World journal of clinical cases · 2023Article
Corrections and comments
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Authors and funding
12 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundIn acute pancreatitis, secondary infection of pancreatic necrosis is a complication that mostly necessitates interventional therapy. A reliable prediction of infected necrotizing pancreatitis would enable an early identification of patients at risk, which however, is not possible yet.
methodsThis study aims to identify parameters that are useful for the prediction of infected necrosis and to develop a prediction model for early detection. We conducted a retrospective analysis from the hospital information and reimbursement data system and screened 705 patients hospitalized with diagnosis of acute pancreatitis who underwent contrast-enhanced computed tomography and additional diagnostic puncture or drainage of necrotic collections. Both clinical and laboratory parameters were analyzed for an association with a microbiologically confirmed infected pancreatic necrosis. A prediction model was developed using a logistic regression analysis with stepwise inclusion of significant variables. The model quality was tested by receiver operating characteristics analysis and compared to single parameters and APACHE II score.
resultsWe identified a total of 89 patients with necrotizing pancreatitis, diagnosed by computed tomography, who additionally received biopsy or drainage. Out of these, 59 individuals had an infected necrosis. Eleven parameters showed a significant association with an infection including C-reactive protein, albumin, creatinine, and alcoholic etiology, which were independent variables in a predictive model. This model showed an area under the curve of 0.819, a sensitivity of 0.692 (95%-CI [0.547-0.809]), and a specificity of 0.840 (95%-CI [0.631-0.947]), outperforming single laboratory markers and APACHE II score. Even in cases of missing values predictability was reliable.
conclusionA model consisting of a few single blood parameters and etiology of pancreatitis might help for differentiation between infected and non-infected pancreatic necrosis and assist medical therapy in acute necrotizing pancreatitis.
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