Risk factor analysis and nomogram model construction for mortality in patients following colonic perforation surgery.

Area of Science:

• Surgical Critical Care
• Predictive Modeling in Medicine
• Gastrointestinal Surgery Outcomes

Background:

• Colonic perforation is a critical surgical emergency with high mortality, often due to rapid septic shock progression.
• Early identification of high-risk patients is crucial, but current predictive tools are often complex and impractical.
• Developing a clinically applicable predictive model is essential for improving patient outcomes.

Purpose of the Study:

• To identify risk factors associated with postoperative mortality in patients experiencing colonic perforation.
• To develop and validate a practical predictive model for postoperative mortality in this patient population.

Main Methods:

• Retrospective analysis of 134 patients undergoing surgery for colonic perforation (Jan 2020 - Jul 2025).
• Comparison of demographic, laboratory, and imaging data between death and survival groups.
• Multivariate logistic regression identified risk factors; a predictive model was constructed and internally validated using bootstrap resampling and decision curve analysis (DCA).

Main Results:

• Mortality rate was 15.6% (21/134 patients).
• Significant risk factors for mortality included higher APACHE II score, elevated lactate levels, and presence of portal venous gas (PVG).
• Elevated white blood cell (WBC) count was a protective factor. The model achieved an AUC of 0.852, demonstrating strong predictive performance.

Conclusions:

• A predictive model incorporating APACHE II score, lactate, WBC count, and PVG offers robust prediction of postoperative mortality in colonic perforation.
• A dual cut-off strategy significantly reduced intensive care unit resource utilization (53% reduction) while maintaining high sensitivity (95.2%).
• This validated tool can be integrated into clinical information systems to guide decision-making and improve patient management.