Enhanced mortality risk prediction with a focus on high-risk percutaneous coronary intervention: results from 1,208,137 procedures in the NCDR (National Cardiovascular Data Registry).JACC Cardiovasc Interv. 2013 Aug; 6(8):790-9.JC
This study sought to update and validate a contemporary model for inpatient mortality following percutaneous coronary intervention (PCI), including variables indicating high clinical risk.
Recently, new variables were added to the CathPCI Registry data collection form. This modification allowed us to better characterize the risk of death, including recent cardiac arrest and duration of cardiogenic shock.
Data from 1,208,137 PCI procedures performed between July 2009 and June 2011 at 1,252 CathPCI Registry sites were used to develop both a "full" and pre-catheterization PCI in-hospital mortality risk model using logistic regression. To support prospective implementation, a simplified bedside risk score was derived from the pre-catheterization risk model. Model performance was assessed by discrimination and calibration metrics in a separate split sample.
In-hospital mortality was 1.4%, ranging from 0.2% among elective cases (45.1% of total cases) to 65.9% among patients with shock and recent cardiac arrest (0.2% of total cases). Cardiogenic shock and procedure urgency were the most predictive of inpatient mortality, whereas the presence of a chronic total occlusion, subacute stent thrombosis, and left main lesion location were significant angiographic predictors. The full, pre-catheterization, and bedside risk prediction models performed well in the overall validation sample (C-indexes 0.930, 0.928, 0.925, respectively) and among pre-specified patient subgroups. The model was well calibrated across the risk spectrum, although slightly overestimating risk in the highest risk patients.
Clinical acuity is a strong predictor of PCI procedural mortality. With inclusion of variables that further characterize clinical stability, the updated CathPCI Registry mortality models remain well-calibrated across the spectrum of PCI risk.