Can We Predict Who Will Be Alive and Well After Transcatheter Aortic Valve Replacement? Is That Useful to Individual Patients?

T he goal of healthcare is to optimize both quantity and quality of life for patients.Among select patients with severe symptomatic aortic stenosis, transcatheter aortic valve replacement (TAVR) can, on average, improve both survival and health status (ie, symptoms, functional status, and quality of life).1,2 However, the technology is currently limited to patients who are either ineligible or at high risk for open surgical aortic valve replacement.The result is that TAVR is used in older patients with multimorbidity and frailty.As such, success is far from guaranteed for each of these complex cases.Indeed, despite the overall benefits seen in the Placement of AoRtic TraNscathetER Valve (PARTNER) trial, ≈1 in 5 patients undergoing TAVR died within 6 months.3 An unmet need is to better determine, before TAVR, which individual patients are unlikely to achieve a "good" outcome. Article see p 2682Risk models offer the potential to move beyond the average effects presented in summary trial results by further risk stratifying patients on the basis of their individual characteristics.4 A number of TAVR risk models have been constructed, primarily to predict risk for death.However, for many of these patients (the average TAVR recipient is in his or her ninth decade of life), survival alone may not constitute a "victory."Persistently poor or worsening patient health status, even among longer-term survivors, is unlikely to be perceived as a success for most patients and their families.Fortunately, the PARTNER trial collected data on a wide range of anticipated benefits and risks of treatment, including formal measures of health status.2,5 In this issue of Circulation, Arnold and colleagues 6 tackle the critical question, "Can we predict who will be 'alive and well' after TAVR?" Using the cohort of patients who underwent TAVR in the PARTNER trial or continued access registry, they derived and validated a risk model to predict poor outcome after TAVR.Poor outcome was defined as death orThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.