Development and Validation of an Early Prediction Model for Postoperative Gastrointestinal Bleeding After Cardiac Surgery Using the MIMIC-IV Database
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: Gastrointestinal bleeding (GIB) after cardiac surgery is a crucial complication. Therefore, this study aimed to develop and validate an early prediction model for postoperative GIB after cardiac surgery using routinely available preoperative data and early postoperative variables. Methods: We conducted a retrospective cohort study of adult intensive care unit (ICU) patients after cardiac surgery using the Medical Information Mart for Intensive Care IV (MIMIC-IV) v3.1 database. The first 24 hours after ICU admission served as the prediction window, and preoperative characteristics and variables collected within this window were extracted using Structured Query Language (SQL). The cohort was randomly split into training and validation sets (7:3). Candidate predictors were selected using least absolute shrinkage and selection operator (LASSO) regression, combined with 1000 bootstrap resamples to improve stability. A multivariable logistic regression model was developed and presented as a nomogram. Model discrimination was evaluated using receiver operating characteristic (ROC) curves and the area under the curve (AUC), with 95% confidence intervals (CIs), in the training and validation cohorts and in prespecified surgical subgroups. Calibration was assessed by bootstrap resampling with the Brier score, and clinical utility was examined using decision curve analysis (DCA). Results: Among 10,611 included patients, 324 (3.1%) developed GIB. The final nomogram included 13 predictors: the first arterial partial pressure of oxygen (PaO2) after ICU admission, minimum PaO2, maximum blood urea nitrogen (BUN), activated partial thromboplastin time (APTT), red cell distribution width (RDW), red blood cell (RBC) transfusion within 24 h after ICU admission, mean peripheral oxygen saturation (SpO2), mean heart rate (HR), mean arterial pressure during the first 6 h after ICU admission, atrial fibrillation, hyperlipidemia, chronic heart failure, and the Simplified Acute Physiology Score II (SAPS II). The model demonstrated discrimination in the training set (AUC 0.770; 95% CI 0.737–0.803) and validation set (AUC 0.772; 95% CI 0.721–0.823). The AUCs across subgroups ranged from 0.764 to 0.785, suggesting stable discrimination across procedure types. Calibration plots showed agreement between predicted and observed risks, and DCA suggested potential clinical benefit across relevant threshold probabilities. Conclusions: This study developed and validated a prediction model based on routinely available preoperative and early postoperative data that can identify patients at increased risk of GIB after open cardiac surgery.
Source: The Heart Surgery Forum
DOI: 10.31083/hsf50244
Institutions: Shandong University, Qilu Hospital of Shandong University
Language: English
Subfield: Gastroenterology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7159797639