Mortality Prediction Model before Surgery for Acute Mesenteric Infarction: A Population-Based Study

Area of Science:

• Surgical outcomes research
• Clinical prediction modeling
• Gastrointestinal surgery

Background:

• Surgery for acute mesenteric infarction (AMI) carries a high mortality rate.
• Effective risk stratification is crucial for managing AMI patients undergoing surgery.

Purpose of the Study:

• To develop and validate a predictive model for 30-day mortality in patients undergoing surgery for AMI.
• To create the ‘Surgery for acute mesenteric infarction mortality score’ (SAMIMS) system.

Main Methods:

• Multivariable analysis was used to identify predictors of 30-day mortality.
• Patients undergoing bowel resection for AMI were divided into derivation and validation groups.
• The SAMIMS system incorporates factors such as age, hemodialysis, heart failure, peptic ulcer disease, diabetes, cerebrovascular disease, and liver disease.

Main Results:

• The SAMIMS score effectively stratified patients into very low, low, intermediate, and high-risk groups for 30-day mortality.
• Mortality rates increased significantly with higher risk scores in both derivation and validation cohorts.
• The model demonstrated good discriminative ability with areas under the ROC curve of 0.677 and 0.696.

Conclusions:

• The developed SAMIMS prediction model enables accurate stratification of 30-day mortality risk in surgical patients with AMI.
• This tool can assist clinicians in identifying high-risk individuals and tailoring perioperative management.
• The SAMIMS system offers a valuable approach to improving outcomes for acute mesenteric infarction surgery.