Use of postoperative information to predict mortality rates for patients who have long stays in the intensive care unit after coronary artery bypass grafting.

OBJECTIVE: To derive and evaluate prediction models for patients who had undergone coronary artery bypass grafting (CABG) and had a difficult postoperative course.
DESIGN: Observational.
SETTING: Midwestern hospital specializing in high-risk CABG procedures. PATIENTS: One hundred eighty-three patients who stayed at least 10 consecutive days in the intensive care unit after a CABG procedure. OUTCOME MEASURE: Death within 60 days of surgery. INTERVENTION: None.
RESULTS: The final logistic regression prediction models included the following findings: pulmonary capillary wedge pressure, cardiac index, heart rate, urine output, positive end-expiratory pressure, blood urea nitrogen levels, and the arterial pressure of carbon dioxide. The model was able to stratify patients into four risk groups with observed 60-day mortality rates of 0.0% (n = 107), 21% (n = 39), 55% (n = 20), and 88% (n = 17). Preoperative patient information was not associated with prognosis for these patients.
CONCLUSIONS: The findings suggest that a risk model that is specific for patients who have undergone CABG and is based on postoperative findings may provide useful prognostic information for patients who are having a difficult postoperative course.