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Published on: January 28, 2020
Contemporary mortality risk prediction for percutaneous coronary intervention: results from 588,398 procedures in the
Eric D Peterson1, David Dai, Elizabeth R DeLong
1Duke Clinical Research Institute, Durham, North Carolina 27715, USA. Peter016@mc.duke.edu
Insights
New models accurately predict mortality risk after percutaneous coronary intervention (PCI). These tools aid research, clinical decisions, and policy by quantifying procedural risks for patients undergoing PCI.
Area of Science:
- Cardiovascular Medicine
- Medical Informatics
- Health Services Research
Background:
- Accurate risk stratification is crucial for comparative effectiveness research, provider comparisons, and patient decision-making in percutaneous coronary intervention (PCI).
- Existing risk models may not reflect contemporary PCI outcomes and patient populations.
Purpose of the Study:
- To develop and validate contemporary risk prediction models for in-hospital mortality following percutaneous coronary intervention (PCI).
- To identify key pre-procedural and angiographic factors associated with PCI-related mortality.
Main Methods:
- Logistic regression models were developed using data from 181,775 PCI procedures (January 2004 to March 2006).
- Models were validated in two independent cohorts: a contemporary cohort (n=121,183) and a prospective cohort (n=285,440).
- Model performance was assessed using discrimination (c-index) and calibration.
Main Results:
- Overall in-hospital mortality following PCI was 1.27%, varying by indication.
- Pre-procedural clinical factors were strong predictors of mortality; angiographic factors offered limited incremental value.
- The National Cardiovascular Data Registry (NCDR) model and a simplified NCDR risk score demonstrated excellent discrimination (c-indices of 0.93 and 0.91, respectively) and calibration across subgroups and validation sets.
Conclusions:
- Contemporary risk models accurately predict early mortality after percutaneous coronary intervention (PCI).
- These validated risk prediction tools can enhance research, guide clinical decisions, and inform health policy.
- The NCDR risk score provides a reliable method for assessing PCI-related mortality risk.
Objectives:
We sought to create contemporary models for predicting mortality risk following percutaneous coronary intervention (PCI).
Background:
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.
Methods:
Data from 181,775 procedures performed from January 2004 to March 2006 were used to develop risk models based on pre-procedural and/or angiographic factors using logistic regression. These models were independently evaluated in 2 validation cohorts: contemporary (n = 121,183, January 2004 to March 2006) and prospective (n = 285,440, March 2006 to March 2007).
Results:
Overall, PCI in-hospital mortality was 1.27%, ranging from 0.65% in elective PCI to 4.81% in ST-segment elevation myocardial infarction patients. Multiple pre-procedural clinical factors were significantly associated with in-hospital mortality. Angiographic variables provided only modest incremental information to pre-procedural risk assessments. The overall National Cardiovascular Data Registry (NCDR) model, as well as a simplified NCDR risk score (based on 8 key 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.
Conclusions:
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.
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