Risk Prediction Model for In-Hospital Mortality After TAVR
What are predictors of in-hospital mortality after transcatheter aortic valve replacement (TAVR)?
This study identifies predictors of mortality in 13,718 patients undergoing TAVR from the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy (STS/ACC TVT) Registry, with model validation in a subsequent cohort of 6,868 individuals.
In-hospital mortality occurred in 730 individuals (5.3%) treated with TAVR. The C statistic was 0.67 and 0.66 for discrimination in the development and validation groups, respectively. Independent predictors of mortality included age (odds ratio [OR], 1.13; 95% confidence interval [CI], 1.06-1.20), glomerular filtration rate (OR, 0.93 per 5-U; 95% CI, 0.91-0.95), hemodialysis (OR, 3.25; 95% CI, 2.42-4.37), New York Heart Association class IV symptoms (OR, 3.34; 95% CI, 1.59-7.02), severe chronic lung disease (OR, 1.67; 95% CI, 1.35-2.05), nonfemoral access (OR, 1.96; 95% CI, 1.65-2.33), and increased procedural acuity categories (categories 2, 3, and 4 with OR 1.57, 2.70, and 3.34, respectively).
This study creates a predictive model of in-hospital mortality in patients treated with TAVR, which is validated in a subsequent population. These results should inform assessment of risk in patients considered for TAVR.
As TAVR becomes widely used, one challenge has been identifying which patients are most and least likely to benefit from this procedure. This large registry identifies seven variables that have a good ability to discriminate risk of in-hospital mortality, and are validated in a subsequent cohort of patients. These results can help us understand which patients are at increased short-term risk of mortality, and improve patient selection for TAVR. We can look forward to future models from this registry that identify factors that predict 30-day and 1-year mortality.
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