Arnold Suzanne V, Cohen David J, Dai David, Jones Philip G, Li Fan, Thomas Laine, Baron Suzanne J, Frankel Naftali Z, Strong Susan, Matsouaka Roland A, Edwards Fred H, Brennan J Matthew
Saint Luke's Mid America Heart Institute, University of Missouri-Kansas City (S.V.A., D.J.C., P.G.J., S.J.B.).
Duke University, Durham, NC (D.D., F.L., L.T., R.A.M., J.M.B.).
Circ Cardiovasc Qual Outcomes. 2018 Oct;11(10):e004693. doi: 10.1161/CIRCOUTCOMES.118.004693.
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.
在手术风险高的临床试验患者中，已开发出一种模型并进行了外部验证，以估计经导管主动脉瓣置换术（TAVR）后患者出现不良结局的风险。该模型在低风险和未经过筛选的患者中的表现尚不清楚。我们试图在美国胸外科医师协会/美国心脏病学会经导管瓣膜治疗注册中心的患者中检查并优化TAVR不良结局风险模型的性能。
在2011年11月9日至2015年6月30日期间于美国252个地点接受TAVR的13351例患者中，TAVR后1年不良结局的发生率为38.9%，其中20.7%是由于死亡，18.2%是由于生活质量差或生活质量下降。不良结局的发生率随时间略有下降，从2012年的42.0%降至2015年的37.8%（趋势P值 = 0.076）。原始的TAVR不良结局风险模型在此人群中校准效果不佳。然后我们重新估计了模型中的截距和系数，并重新测试了模型性能，之后该模型表现良好（整体和亚组均如此），C指数为0.65，校准良好。
在美国一大群未经过筛选的患者中，我们发现虽然相当一部分患者在TAVR后仍有不良结局，但随着时间的推移结局已缓慢改善。重新校准后，TAVR不良结局风险模型表现良好。该模型可能在TAVR前用于帮助患者对恢复有适当的预期。
