ArticleBMC medical informatics and decision making2024
Establishment of a risk prediction model for bowel necrosis in patients with incarcerated inguinal hernia.
Article in BMC medical informatics and decision making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 9 citations in OpenAlex.
- To explore or not: machine learning models for intraoperative decision on testicular exploration in infants under 3 months with incarcerated inguinal hernia.BMC surgery · 2026Article
- Evaluation of usefulness of manual reduction in the management of adult acute irreducible abdominal wall hernia: a study from a community-based teaching hospital.Hernia : the journal of hernias and abdominal wall surgery · 2026Article
- Early prediction of bowel necrosis in incarcerated groin hernia using parsimonious machine learning models: a retrospective cohort study.Hernia : the journal of hernias and abdominal wall surgery · 2026Article
- Prediction of bowel resection in acute irreducible inguinal hernia: a retrospective analysis of preoperative computed tomography and clinical risk factors.BMC surgery · 2026Observational
- High bilirubin and blood urea nitrogen predict intestinal necrosis in incarcerated groin hernia.Hernia : the journal of hernias and abdominal wall surgery · 2026Article
- Inflammatory markers as predictors of severity in adult incarcerated groin hernias - a retrospective comparative study.BMC surgery · 2026Article
- Predicting bowel necrosis in pediatric acute intussusception using roundness and other related factors.BMC pediatrics · 2025Article
- Interpretable machine learning model predicts 1-year inguinal hernia risk after robot-assisted radical prostatectomy.Journal of robotic surgery · 2025Article
- Machine learning-based radiomic nomogram from unenhanced computed tomography and clinical data predicts bowel resection in incarcerated inguinal hernia.World journal of gastrointestinal surgery · 2025Article
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Authors and funding
2 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
introductionIncarceration occurred in approximately 5% to 15% of inguinal hernia patients, with around 15% of incarcerated cases progressing to intestinal necrosis, necessitating bowel resection surgery. Patients with intestinal necrosis had significantly higher mortality and complication rates compared to those without necrosis.The primary objective of this study was to design and validate a diagnostic model capable of predicting intestinal necrosis in patients with incarcerated groin hernias.
methodsWe screened the clinical records of patients who underwent emergency surgery for incarcerated inguinal hernia between January 1, 2015, and December 31, 2022. To ensure balanced representation, the enrolled patients were randomly divided into a training set (n = 180) and a validation set (n = 76) using a 2:1 ratio. Logistic regression analysis was conducted using the rms package in R software, incorporating selected features from the LASSO regression model, to construct a predictive model.
resultsBased on the results of the LASSO regression analysis, a multivariate logistic regression model was developed to establish the predictive model. The predictors included in the model were Abdominal effusion, Hernia Sac Effusion, and Procalcitonin. The area under the receiver operating characteristic (ROC) curve for the nomogram graph in the training set was 0.977 (95% CI = 0.957-0.992). In the validation set, the AUC for the nomogram graph was 0.970. Calibration curve and decision curve analysis (DCA) verified the accuracy and practicability of the nomogram graph in our study.
conclusionBowel necrosis in patients with incarcerated inguinal hernia was influenced by multiple factors. The nomogram predictive model constructed in this study could be utilized to predict and differentiate whether incarcerated inguinal hernia patients were at risk of developing bowel necrosis.
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