ArticleEuropean journal of medical research2025
Establishment and validation of a prediction model for acute kidney injury in moderate severe and severe acute pancreatitis patients.
Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk prediction models for acute kidney injury in patients with acute pancreatitis: a systematic review.BMC gastroenterology · 2026Pooled it
- Interpretable machine learning reveals phosphorus-to-albumin ratio as a novel predictor of mortality and acute kidney injury in critically ill pancreatitis patients: a multi-center retrospective analysis.European journal of medical research · 2026Article
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10 authors.
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Abstract
purposeThis study aimed to develop a nomogram for predicting acute kidney injury (AKI) in patients with moderate severe acute pancreatitis (MSAP) and severe acute pancreatitis (SAP).
methodsThis study enrolled a total of 1,077 patients with MSAP and SAP, categorizing them into three groups: training (n = 646), internal validation (n = 278), and external validation (n = 153). In the training cohort, logistic regression analysis identified independent predictors of AKI in patients with MSAP and SAP. A nomogram was developed based on these independent predictors. The model's performance was assessed using the receiver operating characteristics (ROC) curve, precision-recall (PR) curve, calibration curve, and decision curve analysis (DCA).
resultsThe incidence rates of AKI in the training set, internal validation set, and external validation set were 32.82%, 32.01%, and 27.45%, respectively. Independent predictors of AKI in patients with MSAP and SAP included: shock index (odds ratio [OR] = 7.42, 95% confidence interval [CI] 2.18-25.19), blood urea nitrogen (OR = 1.32, 95% CI 1.22-1.43), uric acid (OR = 1.002, 95% CI 1.000-1.003), serum calcium (OR = 0.38, 95% CI 0.18-0.79), triglycerides (OR = 1.02, 95% CI 1.004-1.041), hematocrit > 0.5 (OR = 3.24, 95% CI 1.10-9.59), serum sodium < 135 mmol/L (OR = 2.01, 95% CI 1.15-3.49), creatine kinase isoenzyme > 4 ng/mL (OR = 2.61, 95% CI 1.48-4.61), and thrombin time < 14 s (OR = 2.83, 95% CI 1.28-6.27). In the training, internal validation, and external validation sets, the areas under the ROC curves for the nomogram were 0.841, 0.789, and 0.853, respectively. Similarly, the areas under the PR curves were 0.807, 0.733, and 0.770. The calibration curves demonstrated that the predicted outcomes were well-aligned with the actual results. The decision curve analysis (DCA) indicated that the model had satisfactory clinical applicability.
conclusionsNine indicators have been identified as independent predictors of AKI in patients with MSAP and SAP. The developed nomogram exhibits robust predictive capability and shows promise for clinical application.
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