Preoperative Prediction of Prolonged Mechanical Ventilation Following Coronary Artery Bypass Grafting

Objective: Few studies have attempted to evaluate who would require prolonged mechanical ventilation following heart surgery. The objectives of this study were to identify predictors of prolonged ventilation in a large group of coronary artery bypass grafting (CABG) patients from a single institution.

Methods: One thousand, eight hundred and twenty-nine consecutive patients undergoing CABG were reviewed retrospectively and evaluated for preoperative predictors of prolonged ventilation which included: age, gender, ejection fraction (EF), renal function, diabetes, angina status, New York Heart Association Class, number of diseased vessels, urgency of the procedure, re-operation, chronic lung disease (COPD) and intraoperative variables such as IABP, inotropes, stroke and myocardial infarction. Prolonged ventilation was defined as > or = 24 h. Stepwise logistic regression analysis was performed.

Results: Patients were on average 65.4+/-10.6 years of age, 30% were diabetic, 80% had triple vessel disease and 93% were of functional class III/IV. The mean ejection fraction was 60+/-16 percent. Overall peri-operative mortality was 2.7%. There were 157 patients that required prolonged ventilation with a peri-operative mortality of 18.5% (P < 0.001). Preoperative independent predictors of prolonged ventilation were found to be: unstable angina (OR 5.6), EF < 50 (OR 2.3), COPD (OR 2.0), preop. renal failure (OR 1.9), female gender (OR 1.8) and age > 70 (OR 1.7). Based on these predictors, a model was created to estimate of the risk of prolonged ventilation in individual patients following CABG with results ranging from < or = 3% in patients without any risk factors to > or = 32% in patients with five or more independent risk factors. Certain intraoperative variables were strong predictors of prolonged ventilation and included: stroke (OR 12.3), re-operation for bleeding (OR 6.9) and perioperative MI (OR 5.8).

Conclusion: We were able to create a stable model where several preoperative and intra-operative variables were shown to be predictive of prolonged ventilation after CABG surgery. The ability to identify patients at increased risk for prolonged ventilation may allow the development of pre-emptive strategies and more effective resource allocation.