ArticleAnnals of medicine2023
Development and internal validation of a practical model to predict 30 days mortality of severe acute pancreatitis patients.
Article in Annals of medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Metabolic syndrome components individually worsen the outcome of acute pancreatitis: a systematic review and meta-analysis.Frontiers in endocrinology · 2025Pooled it
- An interpretable XGboost algorithm for predicting 30-day mortality in acute pancreatitis using routine biomarkers.BMC medical research methodology · 2026Article
- Development and Validation of a Nomogram Model for Severe Acute Pancreatitis Risk Stratification: A Retrospective Cohort Study.Current medical science · 2026Article
- Serum aberrant expression of miR-331-3p and its diagnostic value in severe pancreatitis.BMC gastroenterology · 2026Article
- Article
- Development and validation of a nomogram for predicting 30-day mortality in patients with severe acute pancreatitis and pneumonia.Scientific reports · 2025Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSevere acute pancreatitis (SAP) is a common disease in the intensive care unit (ICU) accompanied by high mortality, the purpose of this study was to build a prediction model for the 30 days mortality of SAP.
methodsWe retrospectively reviewed 149 patients with SAP after admission in 48 h to the ICU of the First Affiliated Hospital of Nanjing Medical University between January 2015 and December 2019. Clinical variables including gender, age, blood routine, and biochemical indicators were collected. On the basis of these variables, stepwise regression analysis was carried out to establish the model. A bootstrapping technique was applied for internal validation.
resultsAge, aspartate aminotransferase (AST), alkaline phosphatase (ALP), triglycerides (TG), and creatinine (CREA) were differences between survivors and nonsurvivors groups (all
conclusionOur study has built a refined model with easily acquired biochemical parameters to predict 30 days mortality of SAP admitted to ICU. This model will require external and prospective validation prior to translate into clinical management.
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