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.