Three models may have multiple applications in research, clinical and policy decision-making
THURSDAY, April 8 (HealthDay News) -- A newly developed set of risk models can accurately predict early mortality risk after percutaneous coronary intervention (PCI), and can be used to guide research, clinical decisions and policy making, according to research published online March 31 in the Journal of the American College of Cardiology.
Eric D. Peterson, M.D., of the Duke Clinical Research Institute in Durham, N.C., and colleagues assembled data from the National Cardiovascular Data Registry on 181,775 PCI procedures performed during 2004 to 2006. The researchers developed PCI mortality risk models based on pre-procedure and angiographic factors. They developed a "full" model that took account of all candidate variables; a "pre-cath" model that excluded angiographic information; and a simplified pre-cath model that excluded even more variables. The models were validated in two large cohorts.
The researchers found that in-hospital mortality in the PCI data set ranged from 0.65 percent for elective PCI to 4.81 percent for patients with ST-segment elevation myocardial infarction (STEMI). The full model, which included 21 clinical variables, performed well in assessing risk, and there was only a slight loss of accuracy when angiographic information was excluded for the pre-cath model. The simplified model included age, New York Heart Association functional class, STEMI versus no STEMI, renal function, chronic lung disease, peripheral vascular disease, cardiogenic shock and congestive heart failure.
"Risks for early mortality following PCI can be accurately predicted in contemporary practice. Incorporation of such risk tools should facilitate research, clinical decisions and policy applications," the authors write.
Several study authors reported financial ties to pharmaceutical or medical device companies or health plans.