ArticleWorld journal of gastroenterology2022
Development and validation of a prediction model for moderately severe and severe acute pancreatitis in pregnancy.
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 19 papers.
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Who cites it
19 citing papers in PubMed.
- Diagnostic and prognostic value of serum lactate dehydrogenase and amylase in severe acute pancreatitis: A clinical biochemistry-based evaluation.Journal of medical biochemistry · 2026Article
- Development of a prediction method for severe pancreatitis using a nomogram.Frontiers in medicine · 2026Article
- Development of a novel nomogram to predict the prognosis of acute pancreatitis in pregnancy.BMC gastroenterology · 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
- Utilizing machine learning models for predicting outcomes in acute pancreatitis: development and validation in three retrospective cohorts.BMC medical informatics and decision making · 2025Article
- Global incidence and mortality of pancreatitis in women of childbearing age from 1990 to 2021.Scientific reports · 2025Article
- Machine learning-based prediction of the risk of moderate-to-severe catheter-related bladder discomfort in general anaesthesia patients: a prospective cohort study.BMC anesthesiology · 2024Article
- Assessment of early factors for identification or prediction severe acute pancreatitis in pregnancy.World journal of clinical cases · 2024Article
- Acute Pancreatitis in Pregnancy: A Propensity Score Matching Analysis and Dynamic Nomogram for Risk Assessment.Digestive diseases and sciences · 2024Article
- Acute Pancreatitis during and after Pregnancy: A Review.Journal of clinical medicine · 2024Review
- Identification of novel biomarkers based on lipid metabolism-related molecular subtypes for moderately severe and severe acute pancreatitis.Lipids in health and disease · 2024Article
- Establishment and Validation of a Dynamic Nomogram for Persistent Organ Failure in Acute Biliary Pancreatitis: A Retrospective Study.Journal of inflammation research · 2024Article
- A novel HCP (heparin-binding protein-C reactive protein-procalcitonin) inflammatory composite model can predict severe acute pancreatitis.Scientific reports · 2023Article
- A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy.BMC pregnancy and childbirth · 2023Article
- Relationship between Cholesterol-Related Lipids and Severe Acute Pancreatitis: From Bench to Bedside.Journal of clinical medicine · 2023Review
- Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis.Journal of inflammation research · 2023Article
- Pancreatitis in Pregnancy-Comprehensive Review.International journal of environmental research and public health · 2022Review
- Prediction of moderately severe and severe acute pancreatitis in pregnancy: Several issues.World journal of gastroenterology · 2022Review
- Development of a Novel Nomogram Incorporating Red Blood Cell Distribution Width-Albumin Ratio for the Prediction of 30-day Mortality in Acute Pancreatitis Patients.Emergency medicine international · 2022Article
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Authors and funding
6 authors.
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Abstract
backgroundThe severity of acute pancreatitis in pregnancy (APIP) is correlated with higher risks of maternal and fetal death.
aimTo develop a nomogram that could predict moderately severe and severe acute pancreatitis in pregnancy (MSIP).
methodsPatients with APIP admitted to West China Hospital between January 2012 and December 2018 were included in this study. They were divided into mild acute pancreatitis in pregnancy (MAIP) and MSIP. Characteristic parameters and laboratory results were collected. The training set and test set were randomly divided at a ratio of 7:3. Least absolute shrinkage and selection operator regression was used to select potential prognostic factors. A nomogram was developed by logistic regression. A random forest model was used to validate the stability of the prediction factors. Receiver operating characteristic curves and calibration curves were used to evaluate the model's predictive performance.
resultsA total of 190 patients were included in this study. A total of 134 patients (70.5%) and 56 patients (29.5%) were classified as having MAIP and MSIP, respectively. Four independent predictors (lactate dehydrogenase, triglyceride, cholesterol, and albumin levels) were identified for MSIP. A nomogram prediction model based on these factors was established. The model had areas under the curve of 0.865 and 0.853 in the training and validation sets, respectively. The calibration curves showed that the nomogram has a good consistency.
conclusionA nomogram including lactate dehydrogenase, triglyceride, cholesterol, and albumin levels as independent predictors was built with good performance for MSIP prediction.
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