Related Experiment Video
Updated: Mar 28, 2026
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Development and validation of a nomogram model for predicting unplanned readmission in patients with acute
Ping Zhu1, Weiping Fang2, Huifang Tu1
1Department of Gastroenterology, The First People's Hospital of Linping District, Hangzhou, Zhejiang, China.
Insights
This study developed a nomogram to predict 1-year unplanned readmissions in acute pancreatitis (AP) patients. The tool helps identify individuals at high risk for readmission, improving patient management.
Area of Science:
- Medical Informatics
- Clinical Prediction Models
- Gastroenterology
Background:
- Acute pancreatitis (AP) poses a significant risk for unplanned hospital readmissions.
- Identifying patients at high risk for readmission is crucial for effective resource allocation and patient care.
Purpose of the Study:
- To develop and validate a nomogram for predicting 1-year unplanned readmission in patients diagnosed with acute pancreatitis.
- To identify key predictors for unplanned readmissions in AP patients.
Main Methods:
- Retrospective analysis of 474 AP patients from two hospitals.
- Variable selection using the least absolute shrinkage and selection operator (LASSO) regression.
- Development and validation of a nomogram using logistic regression and assessing performance with C-index, calibration curves, ROC curves, and DCA.
Main Results:
- The nomogram identified six independent predictors: biliary AP, diabetes, alcohol, infected pancreatic necrosis (IPN), acute peripancreatic fluid collection (APFC), and readmission score.
- The nomogram demonstrated good predictive accuracy with AUC values of 0.739 (training), 0.836 (internal validation), and 0.704 (external validation).
- Calibration curves confirmed good agreement between predicted and observed risks.
Conclusions:
- The developed nomogram is a valuable tool for predicting 1-year unplanned readmission in AP patients.
- This tool can aid clinicians in identifying high-risk populations for targeted interventions and improved outcomes.
Objective:
The objective of this study was to develop and validate a nomogram for predicting 1-year unplanned readmission in patients with acute pancreatitis (AP) to identify high-risk populations.
Methods:
We retrospectively selected 474 AP patients who were treated and discharged from the First People's Hospital of Linping District, Hangzhou City, from 1 January 2021 to 31 December 2023. These patients were randomly divided into a training cohort (n = 332) and an internal validation cohort (n = 142) in a 7:3 ratio. In addition, 218 AP patients treated during the same period at the People's Hospital of Jiande City were selected as an external validation cohort. The least absolute shrinkage and selection operator (LASSO) was used for variable selection, and multivariable logistic regression was applied for model development. A nomogram was then constructed to estimate the risk of 1-year unplanned readmission. Model performance was evaluated using the consistency index (C-index), calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).
Results:
Within 1 year, the incidence of unplanned readmission was 36.1% (120/332) in the training cohort, 40.1% (57/142) in the internal validation cohort, and 42.7% (93/218) in the external validation cohort. Six independent predictors of unplanned readmission in patients with AP were identified, including biliary AP, diabetes, alcohol, infected pancreatic necrosis (IPN) at first admission, acute peripancreatic fluid collection (APFC), and readmission score. The nomogram demonstrated sufficient predictive accuracy, with area under the curve (AUC) values of 0.739 (95% confidence interval [CI]: 0.684-0.794), 0.836 (95% CI: 0.770-0.902), and 0.704 (95% CI: 0.636-0.772) in the training cohort, internal validation cohort, and external validation cohort, respectively. The calibration curve showed good agreement between the predicted risk and the actual risk observed.
Conclusions:
The nomogram developed in this study demonstrates good predictive value for unplanned readmission in patients with AP and may help identify high-risk populations.
Related Concept Videos
01:30Acute Pancreatitis II: Clinical Manifestations and Management
01:23Dosage Regimen Designs: Nomograms and Tabulations
01:29Chronic Pancreatitis II: Collaborative Care
Assessment:
01:27Acute Pancreatitis I: Introduction
Acute pancreatitis is characterized by rapid inflammation of the pancreas, often caused by factors like gallstone blockage or excessive alcohol consumption. Chronic pancreatitis, on the other hand, is a slow, progressive inflammation that may result from long-term alcohol abuse, obstructions in the pancreatic duct, or genetic factors.
The causes of acute pancreatitis include: