- 作者：J. Matthew Brennan ; Jeptha P. Curtis ; David Dai ; Susan Fitzgerald ; Akshay K. Kh ; elwal ; John A. Spertus ; Sunil V. Rao ; M ; eep Singh ; Richard E. Shaw ; Kalon K.L. Ho ; Ronald J. Krone ; William S. Weintraub ; W. Douglas Weaver ; Eric D. Peterson ; National Cardiovascular Data Registry
- 关键词：American College of Cardiology ; National Cardiovascular Data Registry CathPCI Registry ; percutaneous coronary intervention ; risk prediction
- 刊名：JACC: Cardiovascular Interventions
- 出版年：2013
- 出版时间：August, 2013
- 年：2013
- 卷：6
- 期：8
- 页码：790-799
- 全文大小：954 K
Objectives
This study sought to update and validate a contemporary model for inpatient mortality following percutaneous coronary intervention (PCI), including variables indicating high clinical risk.Background
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.
Methods
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.
Results
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.
Conclusions
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.