Predicting Quality of Life at 1 Year After Transcatheter Aortic Valve Replacement in a Real-World Population.

Background Among clinical trial patients at high surgical risk, a model has been developed and externally validated to estimate patient risk for poor outcomes after transcatheter aortic valve replacement (TAVR). How this model performs in lower risk and unselected patients is not known. We sought to examine and optimize the performance of the TAVR poor outcome risk model among patients in the US Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry. Methods and Results Among 13 351 patients who underwent TAVR at 252 US sites between November 9, 2011 and June 30, 2015, the rate of poor outcome at 1 year after TAVR was 38.9%, which was because of death in 20.7% and poor quality of life or quality of life decline in 18.2%. The rate of poor outcome has decreased slightly over time, from 42.0% in 2012 to 37.8% in 2015 ( P for trend=0.076). The original TAVR poor outcome risk model did not calibrate well on this population. We then reestimated the intercept and coefficients in the model and retested model performance, after which it performed well (both overall and in subgroups), with a C index 0.65 and excellent calibration. Conclusions In a large cohort of unselected patients in the United States, we found that while a substantial minority of patients continue to have a poor outcome after TAVR, outcomes have slowly improved over time. After recalibration, the TAVR poor outcome risk model performed well. This model could potentially be used before TAVR to help patients have appropriate expectations of recovery.

Duke Scholars

Author Fan Li Statistical Science

Author Laine Elliott Thomas Biostatistics & Bioinformatics, Division of Biostatistics

Author Roland Albert Matsouaka Biostatistics & Bioinformatics, Division of Biostatistics

Author J. Matthew Brennan Medicine, Cardiology