National Cardiovascular Data Registry Model Predicts Long-Term Mortality in Patients Undergoing Percutaneous Coronary Interventions

National Cardiovascular Data Registry (NCDR)-based logistic regression model is available for clinicians to predict in-hospital all-cause mortality after a percutaneous coronary intervention (PCI). However, this model has never been used to predict long-term all-cause mortality after PCI. Therefore, we sought to test the ability of the NCDR model to predict the short- and long-term risk of all-cause mortality in patients undergoing PCI. All patients undergoing PCI in the Mayo Clinic Health System were enrolled in the Mayo Clinic CathPCI registry. Patient-level demographic, clinical, and angiographic data from January 2006 to December 2017 were extracted from the registry. Patients who underwent coronary artery bypass graft surgery (CABG) were excluded. The area under the receiver operator characteristic curve (AUC) was calculated to assess the ability of the NCDR model to predict outcomes of interest (6-month, 1-year, 2-year, and 5-year all-cause mortality) after PCI. A total of 17,356 unique patients were included for the final analysis after excluding 165 patients who underwent CABG surgery. The mean age was 66.9 ± 12.5 years, and 71% were men. The 6-month, 1-year, 2-year, and 5-year all-cause mortality rates were 4.2% (n = 737), 5.8% (n = 1,005), 8.06% (n = 1,399), and 14.2% (n = 2,472), respectively. The AUCs of the NCDR model to predict 6-month, 1-year, 2-year, and 5-year all-cause mortality were 0.84 (95% CI: 0.82–0.86), 0.82 (95% CI: 0.80–0.84), 0.80 (95% CI: 0.79–0.81), and 0.78 (95% CI: 0.77–0.79), respectively. The NCDR model was able to accurately predict both short- and long-term all-cause mortality after PCI.