JACC: Registry mortality risk models valid for post-PCI mortality
Risks for early mortality following PCI can be accurately predicted in contemporary practice, according to a review published online March 31 in the Journal of the American College of the Cardiology.
Eric D. Peterson, MD, from the Duke Clinical Research Institute in Durham, N.C., and colleagues said there is a need to identify PCI risk factors and accurately quantify procedural risks to facilitate comparative effectiveness research, provider comparisons and informed patient decision making. Therefore, they sought to create contemporary models for predicting mortality risk following PCI.
The researchers used data from 181,775 procedures performed from January 2004 to March 2006 to develop risk models based on pre-procedural and/or angiographic factors using logistic regression. They independently evaluated the models in two validation cohorts: contemporarily (121,183 patients, January 2004 to March 2006) and prospectively (285,440 patients, March 2006 to March 2007).
When model chi-square value was used as the metric, cardiogenic shock was the most predictive of in-hospital mortality, followed by renal function (estimated glomerular filtration rate [eGFR]) and age. In contrast, angiographic predictors were generally less prognostic. The angiographic feature most highly associated with in-hospital mortality was lesion location (e.g., left main lesions and proximal left anterior descending lesions).
Overall, Peterson and colleagues found that PCI in-hospital mortality was 1.27 percent, ranging from 0.65 percent in elective PCI to 4.81 percent in STEMI patients.
“Multiple pre-procedural clinical factors were significantly associated with in-hospital mortality,” the authors wrote. “Angiographic variables provided only modest incremental information to pre-procedural risk assessments.”
Peterson and colleagues found that the overall National Cardiovascular Data Registry (NCDR) model, as well as a simplified NCDR risk score (based on eight pre-procedure factors), had “excellent discrimination” (c-index: 0.93 and 0.91, respectively).
Discrimination and calibration of both risk tools were retained among specific patient subgroups, in the validation samples, and when used to estimate 30-day mortality rates among Medicare patients, they found.
Of note, the authors reported that the exclusion of angiographic details and ejection fraction from the full model resulted in only a slight decrement in the overall model accuracy.
Using data from the ACC NCDR CathPCI Registry, the researchers claimed to have “developed and validated contemporary models” for assessing peri-procedural PCI mortality risk. They said each of these has “excellent predictive accuracy throughout the full spectrum of patient risk, and important patient subgroups.”
They wrote the incorporation of “such risk tools should facilitate research, clinical decisions and policy applications.”
Eric D. Peterson, MD, from the Duke Clinical Research Institute in Durham, N.C., and colleagues said there is a need to identify PCI risk factors and accurately quantify procedural risks to facilitate comparative effectiveness research, provider comparisons and informed patient decision making. Therefore, they sought to create contemporary models for predicting mortality risk following PCI.
The researchers used data from 181,775 procedures performed from January 2004 to March 2006 to develop risk models based on pre-procedural and/or angiographic factors using logistic regression. They independently evaluated the models in two validation cohorts: contemporarily (121,183 patients, January 2004 to March 2006) and prospectively (285,440 patients, March 2006 to March 2007).
When model chi-square value was used as the metric, cardiogenic shock was the most predictive of in-hospital mortality, followed by renal function (estimated glomerular filtration rate [eGFR]) and age. In contrast, angiographic predictors were generally less prognostic. The angiographic feature most highly associated with in-hospital mortality was lesion location (e.g., left main lesions and proximal left anterior descending lesions).
Overall, Peterson and colleagues found that PCI in-hospital mortality was 1.27 percent, ranging from 0.65 percent in elective PCI to 4.81 percent in STEMI patients.
“Multiple pre-procedural clinical factors were significantly associated with in-hospital mortality,” the authors wrote. “Angiographic variables provided only modest incremental information to pre-procedural risk assessments.”
Peterson and colleagues found that the overall National Cardiovascular Data Registry (NCDR) model, as well as a simplified NCDR risk score (based on eight pre-procedure factors), had “excellent discrimination” (c-index: 0.93 and 0.91, respectively).
Discrimination and calibration of both risk tools were retained among specific patient subgroups, in the validation samples, and when used to estimate 30-day mortality rates among Medicare patients, they found.
Of note, the authors reported that the exclusion of angiographic details and ejection fraction from the full model resulted in only a slight decrement in the overall model accuracy.
Using data from the ACC NCDR CathPCI Registry, the researchers claimed to have “developed and validated contemporary models” for assessing peri-procedural PCI mortality risk. They said each of these has “excellent predictive accuracy throughout the full spectrum of patient risk, and important patient subgroups.”
They wrote the incorporation of “such risk tools should facilitate research, clinical decisions and policy applications.”