ArticleRenal failure2023
Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis.
Article in Renal failure, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses that pooled it.
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Who cites it
23 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- AI Models for Predicting Acute Kidney Injury (AKI) and Post-AKI Mortality: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Risk prediction models for acute kidney injury in patients with acute pancreatitis: a systematic review.BMC gastroenterology · 2026Pooled it
- Predictive models for acute kidney injury in acute pancreatitis: a systematic review and meta-analysis.Frontiers in medicine · 2025Pooled it
- Development of an Explainable Machine Learning Model to Predict Mortality Risk in Sepsis Patients: Insights From a Real-World Clinical Data.Shock (Augusta, Ga.) · 2026Article
- Association of red blood cell distribution width combined with alanine aminotransferase with gastrointestinal hemorrhage in patients with acute pancreatitis: a retrospective MIMIC-IV study.Frontiers in medicine · 2026Article
- Development and interpretable machine learning models for classification of pancreatic pseudocyst risk in acute pancreatitis.Frontiers in digital health · 2026Article
- Concentration and predictive value of plasma neutrophil gelatinase-associated lipocalin in patients with acute pancreatitis and acute kidney injury.World journal of nephrology · 2025Article
- Relationship between intra-bladder pressure and acute kidney injury in patients with acute pancreatitis: interpretable machine learning approach.BMC nephrology · 2025Article
- 28-day all-cause mortality in patients with alcoholic cirrhosis: a machine learning prediction model based on the MIMIC-IV.Clinical and experimental medicine · 2025Article
- A risk nomogram for 30-day mortality in Chinese patients with acute pancreatitis using LASSO-logistic regression.Scientific reports · 2025Article
- Establishment and validation of a prediction model for acute kidney injury in moderate severe and severe acute pancreatitis patients.European journal of medical research · 2025Article
- Association between the development of sepsis and the triglyceride-glucose index in acute pancreatitis patients: a retrospective investigation utilizing the MIMIC-IV database.BMC gastroenterology · 2025Article
- Construction and validation of risk prediction models for renal replacement therapy in patients with acute pancreatitis.European journal of medical research · 2025Article
- Development of a machine learning-based risk prediction model for early-stage pneumoconiosis: a retrospective study.Frontiers in medicine · 2025Article
- Construction and Validation of a Nomogram-Based Predictive Model for Acute Kidney Injury Caused by Drug Resistance to Tuberculosis.International journal of general medicine · 2025Article
- Risk factors for acute kidney injury in patients with acute pancreatitis and construction of nomogram model: a single-center study and external validation.Frontiers in medicine · 2025Article
- The difference in hematocrit and albumin levels and the risk of sepsis for patients with acute pancreatitis: a retrospective cohort study based on the MIMIC-IV database.Sao Paulo medical journal = Revista paulista de medicina · 2025Article
- Predictive model of acute kidney injury in critically ill patients with acute pancreatitis: a machine learning approach using the MIMIC-IV database.Renal failure · 2024Article
- Machine learning models for mortality prediction in critically ill patients with acute pancreatitis-associated acute kidney injury.Clinical kidney journal · 2024Article
- Association between acute peripancreatic fluid collections and early readmission in acute pancreatitis: A propensity-matched analysis.World journal of experimental medicine · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute pancreatitis (AP) is associated with a high incidence of acute kidney injury (AKI). This study aimed to develop a nomogram for predicting the early onset of AKI in AP patients admitted to the intensive care unit.
methodClinical data for 799 patients diagnosed with AP were extracted from the Medical Information Mart for Intensive Care IV database. Eligible AP patients were randomly divided into training and validation cohorts. The independent prognostic factors for the early development of AKI in AP patients were determined using the all-subsets regression method and multivariate logistic regression. A nomogram was constructed for predicting the early occurrence of AKI in AP patients. The performance of the nomogram was evaluated based on the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA).
resultsSeven independent prognostic factors were identified as predictive factors for early onset AKI in AP patients. The AUC of the nomogram in the training and validation cohorts were 0.795 (95% CI, 0.758-0.832) and 0.772 (95% CI, 0.711-0.832), respectively. The AUC of the nomogram was higher compared with that of the BISAP, Ranson, APACHE II scores. Further, the calibration curve revealed that the predicted outcome was in agreement with the actual observations. Finally, the DCA curves showed that the nomogram had a good clinical applicability value.
conclusionThe constructed nomogram showed a good predictive ability for the early occurrence of AKI in AP patients.
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