ArticleWorld journal of gastroenterology2022
Development and external validation of models to predict acute respiratory distress syndrome related to severe acute pancreatitis.
Article in World journal of gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 22 citations in OpenAlex.
- Clinical controls and model calibration as keys to complete blood count-based studies of pediatric fistula-in-ano.World journal of gastrointestinal surgery · 2026Article
- Multimodal prediction models integrating radiomics and three-dimensional deep learning for acute respiratory distress syndrome in acute pancreatitis patients.The Journal of international medical research · 2026Article
- Development and validation of a nomogram for predicting 30-day mortality in patients with severe acute pancreatitis and pneumonia.Scientific reports · 2025Article
- An early predictive model for acute respiratory distress-syndrome related to pancreatitis in pregnancy: an 8-year multicenter analysis.European journal of medical research · 2025Article
- A prediction model for 30-day mortality in patients with ARDS admitted to the intensive care unit.European journal of medical research · 2025Article
- Morbidity and Mortality Predictors of Acute Respiratory Failure in Acute Pancreatitis: A Cohort Study Conducted in Vietnam.JGH open : an open access journal of gastroenterology and hepatology · 2025Article
- Acute respiratory distress syndrome (ARDS): from mechanistic insights to therapeutic strategies.MedComm · 2025Review
- 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
- Clinical Use of Nomogram Based on Machine Learning for Diagnosis Prediction of Acute Respiratory Distress Syndrome in Patients With Acute Pancreatitis.Mediators of inflammation · 2025Article
- We are all in this together: Understanding organ crosstalk in the pathogenesis of acute respiratory distress syndrome.Pulmonary circulation · 2024Article
- Automated machine learning for early prediction of acute kidney injury in acute pancreatitis.BMC medical informatics and decision making · 2024Article
- Acute pancreatitis: Structured report template of magnetic resonance imaging.World journal of radiology · 2023Review
- Medical imaging for pancreatic diseases: Prediction of severe acute pancreatitis complicated with acute respiratory distress syndrome.World journal of gastroenterology · 2022Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute respiratory distress syndrome (ARDS) is a major cause of death in patients with severe acute pancreatitis (SAP). Although a series of prediction models have been developed for early identification of such patients, the majority are complicated or lack validation. A simpler and more credible model is required for clinical practice.
aimTo develop and validate a predictive model for SAP related ARDS.
methodsPatients diagnosed with AP from four hospitals located at different regions of China were retrospectively grouped into derivation and validation cohorts. Statistically significant variables were identified using the least absolute shrinkage and selection operator regression method. Predictive models with nomograms were further built using multiple logistic regression analysis with these picked predictors. The discriminatory power of new models was compared with some common models. The performance of calibration ability and clinical utility of the predictive models were evaluated.
resultsOut of 597 patients with AP, 139 were diagnosed with SAP (80 in derivation cohort and 59 in validation cohort) and 99 with ARDS (62 in derivation cohort and 37 in validation cohort). Four identical variables were identified as independent risk factors for both SAP and ARDS: heart rate [odds ratio (OR) = 1.05; 95%CI: 1.04-1.07;
conclusionThe present study constructed and validated a simple and accurate predictive model for SAP-related ARDS in patients with AP.
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