Related Experiment Video
Updated: Aug 8, 2026
06:50
A Model of Acute Lung Injury Following Visceral Ischemia-Reperfusion by Supra-Coeliac Aortic Cross Clamping in Rats
Published on: August 15, 2025
Intestinal ischaemia following cardiac surgery: a multivariate risk model
Nilanjan Chaudhuri1, Justin James, Adnan Sheikh
1Department of Cardiothoracic Surgery, The Cardiothoracic Centre-Liverpool, The Cardiothoracic Centre NHS Trust, Thomas Drive, Liverpool L14 3PE, United Kingdom.
Summary
Post-operative intestinal ischaemia after cardiac surgery is rare but deadly. Key risk factors include inotrope/dialysis support, prolonged ventilation, older age, atrial fibrillation, and significant blood loss, aiding early risk identification.
Area of Science:
- Cardiovascular Surgery
- Gastroenterology
- Critical Care Medicine
Background:
- Intestinal ischaemia is a severe complication of cardiac surgery with high mortality.
- Existing research focuses on pre-operative and intra-operative risk factors.
Purpose of the Study:
- To develop a multivariate risk model for identifying patients at high risk of intestinal ischaemia post-cardiac surgery.
- To identify key predictors of post-operative intestinal ischaemia.
Main Methods:
- Prospective data collection from 10,976 cardiac surgery patients (April 1997 - March 2004).
- Multivariate logistic regression analysis to identify predictors.
- Variables were censored at the time of intestinal ischaemia onset.
Main Results:
- Identified predictors: post-operative inotrope/dialysis support (OR 6.7), ventilation >48h (OR 5.1), increased age (OR 1.06/year), post-op atrial fibrillation (OR 2.3), and ICU blood loss >700ml (OR 2.0).
- The model demonstrated excellent predictive ability (AUC 0.93).
- In-hospital mortality for patients with intestinal ischaemia was 94% versus 3.6% for others.
Conclusions:
- Intestinal ischaemia post-cardiac surgery has a low incidence but extremely poor prognosis.
- A multivariate prediction tool incorporating identified risk factors can help identify high-risk patients.
