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Importance Patient selection for transcatheter aortic valve replacement (TAVR) should include assessment of the risks of TAVR compared with surgical aortic valve replacement (SAVR). Existing SAVR risk models accurately predict the risks for the population undergoing SAVR, but comparable models to predict risk for patients undergoing TAVR are currently not available and should be derived from a population that underwent TAVR. Objective To use a national population of patients undergoing TAVR to develop a statistical model that will predict in-hospital mortality after TAVR. Design, Setting, and Participants Patient data were obtained from the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy (STS/ACC TVT) Registry. The model was developed from 13 718 consecutive US patients undergoing TAVR in centers participating in the STS/ACC TVT Registry from November 1, 2011, to February 28, 2014. Validation was conducted using 6868 records of consecutive patients undergoing TAVR from March 1 to October 8, 2014. Covariates were selected through a process of expert opinion and statistical analysis. The association between in-hospital mortality and baseline covariates was estimated using logistic regression. The final set of predictors was selected via stepwise variable selection. Data were collected and analyzed from November 1, 2011, to February 28, 2014. Main Outcomes and Measures In-hospital TAVR mortality. Results The development sample included 13 718 patient records from 265 participant sites (of 13 672 with data available, 6680 men [48.9%]; 6992 women [51.1%]; mean [SD] age, 82.1 [8.3] years). The final validation cohort included 6868 patients from 314 participating centers (3554 men [51.7%]; 3314 women [48.3%]; mean [SD] age, 81.6 [8.8] years). In-hospital mortality occurred in 730 patients (5.3%). The C statistic for discrimination was 0.67 (95% CI, 0.65-0.69) in the development group and 0.66 (95% CI, 0.62-0.69) in the validation group. The final model covariates (reported as odds ratios; 95% CIs) were age (1.13; 1.06-1.20), glomerular filtration rate per 5-U increments (0.93; 0.91-0.95), hemodialysis (3.25; 2.42-4.37), New York Heart Association functional class IV (1.25; 1.03-1.52), severe chronic lung disease (1.67; 1.35-2.05), nonfemoral access site (1.96; 1.65- 2.33), and procedural acuity categories 2 (1.57; 1.20-2.05), 3 (2.70; 2.05-3.55), and 4 (3.34; 1.59-7.02). Calibration analysis demonstrated no significant difference between the model (predicted vs observed) calibration line (−0.18 and 0.97 for intercept and slope, respectively) compared with the ideal calibration line. Conclusions and Relevance Data from the STS/ACC TVT Registry have been used to develop a predictive model of in-hospital mortality for patients undergoing TAVR. Validation based on a population of patient records not used in model development demonstrates discrimination and calibration indices that are more favorable than other models used in populations with TAVR. This model should be a valuable adjunct for patient counseling, local quality improvement, and national monitoring for appropriateness of selection of patients for TAVR.

Prediction of operative risk is a critical step in decision making for cardiac surgery. Existing risk models may be improved by integrating a measure of frailty, such as 5-m gait speed, to better capture the heterogeneity of the older adult population.To determine the association of 5-m gait speed with operative mortality and morbidity in older adults undergoing cardiac surgery.A prospective cohort study was conducted from July 1, 2011, to March 31, 2014, at 109 centers participating in the Society of Thoracic Surgeons Adult Cardiac Surgery Database. The 5-m gait speed test was performed in 15 171 patients aged 60 years or older undergoing coronary artery bypass graft, aortic valve surgery, mitral valve surgery, or combined procedures.All-cause mortality during the first 30 days after surgery; secondarily, a composite outcome of mortality or major morbidity during the index hospitalization.Among the cohort of 15 171 patients undergoing cardiac surgery, the median age was 71 years and 4622 were female (30.5%). Compared with patients in the fastest gait speed tertile (1.00 m/s), operative mortality was increased for those in the middle tertile (0.83-1.00 m/s; odds ratio [OR], 1.77; 95% CI, 1.34-2.34) and slowest tertile (0.83 m/s; OR, 3.16; 95% CI, 2.31-4.33). After adjusting for the Society of Thoracic Surgeons predicted risk of mortality and the surgical procedure, gait speed remained independently predictive of operative mortality (OR, 1.11 per 0.1-m/s decrease in gait speed; 95% CI, 1.07-1.16). Gait speed was also predictive of the composite outcome of mortality or major morbidity (OR, 1.03 per 0.1-m/s decrease in gait speed; 95% CI, 1.00-1.05). Addition of gait speed to the Society of Thoracic Surgeons predicted risk resulted in a C statistic change of 0.005 and integrated discrimination improvement of 0.003.Gait speed is an independent predictor of adverse outcomes after cardiac surgery, with each 0.1-m/s decrease conferring an 11% relative increase in mortality. Gait speed can be used to refine estimates of operative risk, to support decision-making and, since incremental value is modest when used as a sole criterion for frailty, to screen older adults who could benefit from further assessment.