Todd M. Dewey2, David Brown2, William H. Ryan3, Morley A. Herbert2, Syma L. Prince1, Michael J. Mack2; 1CRSTI, Dallas, TX; 2Medical City Dallas Hospital, Dallas, TX; 3Presbyterian Hospital of Dallas, Dallas, TX
Objective: Standard operative risk scoring algorithms have been proposed as a means to identify an appropriate "high-risk" cohort for the use of transcatheter aortic valve implantation instead of standard aortic valve replacement (AVR) in patients with aortic stenosis (AS). We evaluated the efficacy of these methods for predicting outcomes in high risk patients undergoing standard AVR.Methods: 573 patients were identified as having isolated aortic valve replacement between 1/1/1998 and 12/31/2005. Perioperative data was collected using the STS database, and long-term survival determined using the Social Security Death Index, or family contact. All patients had their operative risk calculated using the Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PROM), logistic (LE) and additive (AE) EuroSCORE, and the Ambler score. Patients in the highest 10% of predicted risk by each algorithm (STS = 8.3%, Logistic EuroSCORE = 36%, Additive EuroSCORE = 13, and Ambler Score = 17.2) were identified as high risk. We then compared actual to the predicted surgical outcomes, and the ability to identify patients with the worst long-term survival by scoring method.
Results: Perioperative mortality was 23/573 (4.0%). Average follow-up was 4.2 ± 2.4 years. 104 additional patients (18.2%) died during the study period, for an overall mortality of 127/573 (22.2%). Predicted operative mortality in the high risk cohort as predicted by risk algorithm was 13.4 ± 7% for STS-PROM, 54.1 ± 14.8% for LE, >20 % for AE, and 45.5% by Ambler score. Observed early mortality was 19% in the STS-PROM cohort, 15.5% and 15.9% in the LE and AE cohorts respectively, and 12.8% in the Ambler score. Of the overall deaths, 65% were captured in the high risk cohort by STS-PROM, 51.7% and 52.4% by LE and AE respectively, and 38.5% by Ambler score. Logistic regression showed that the STS-PROM was the most accurate in identifying the patients who ultimately died as being high risk (ROC = 0.74).
Conclusion: The STS-PROM most accurately predicts perioperative mortality for the highest risk patients having AVR. Additionally, it was also the most accurate in identifying those patients at greatest risk of long-term death, with 66% of the high risk group dying within 4.2 years.
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