ArticleJournal of inflammation research2024
Establishment and Validation of an Early Predictive Model for Severe Acute Pancreatitis.
Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Predictive factors and nomogram for post-endoscopic retrograde cholangiopancreatography pancreatitis.BMC gastroenterology · 2026Article
- Development and Validation of a Nomogram Model for Severe Acute Pancreatitis Risk Stratification: A Retrospective Cohort Study.Current medical science · 2026Article
- Development of a machine learning-based early prediction model for disease severity in acute pancreatitis.European journal of medical research · 2026Article
- Nomogram for Predicting Pancreatic Pseudocyst in Hypertriglyceridemic Acute Pancreatitis: A Retrospective Cohort Study.Journal of inflammation research · 2026Article
- Predicting the acute pancreatitis severity with multi-machine learning models: constructing an online prediction platform.Frontiers in cellular and infection microbiology · 2026Article
- Development of a novel nomogram to predict the prognosis of acute pancreatitis in pregnancy.BMC gastroenterology · 2025Article
- Additional considerations on a combination of inflammatory markers and scoring systems for early severity stratification of acute pancreatitis.World journal of gastroenterology · 2025Article
- Prediction of acute pancreatitis severity using NLR, procalcitonin, and CT severity score: A retrospective study.Medicine · 2025Article
- Triglyceride-glucose index as a key predictor of ARDS in acute pancreatitis: SHAP analysis reveals its critical role in risk stratification.Frontiers in nutrition · 2025Article
- An early warning model for predicting major adverse kidney events within 30 days in acute pancreatitis patients.Renal failure · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The purpose of this study is to establishment and validation of an early predictive model for severe acute pancreatitis (SAP). Methods: From January 2015 to August 2022, 2986 AP patients admitted to Changsha Central Hospital were enrolled in this study. They were randomly divided into a modeling group (n = 2112) and a validation group (n = 874). In the modeling group, identify risk factors through logistic regression models and draw column charts. Use internal validation method to verify the accuracy of column chart prediction. Apply calibration curves to evaluate the consistency between nomograms and ideal observations. Draw a DCA curve to evaluate the net benefits of the prediction model. Results: Nine variables including respiratory rate, heart rate, WBC, PDW, PT, SCR, AMY, CK, and TG are the risk factors for SAP. The column chart risk prediction model which was constructed based on these 9 independent factors has high prediction accuracy (modeling group AUC = 0.788, validation group AUC = 7.789). The calibration curve analysis shows that the prediction probabilities of the modeling and validation groups are consistent with the observation probabilities. By drawing a DCA curve, it shows that the model has a wide threshold range (0.01-0.88). Conclusion: The study developed an intuitive nomogram containing readily available laboratory parameters to predict the incidence rate of SAP.
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