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Predicting long-term bleeding after percutaneous coronary intervention
Praneet K Sharma1,2, Adnan K Chhatriwalla1,2, David J Cohen1,2
1Saint Luke's Mid America Heart Institute, Kansas City, Missouri.
Insights
Bleeding events are common in the first year after percutaneous coronary intervention (PCI). A new model using patient characteristics and drug-eluting stent (DES) use can predict these long-term bleeding risks.
Area of Science:
- Cardiology
- Interventional Cardiology
- Clinical Risk Prediction
Background:
- Dual antiplatelet therapy (DAPT) after PCI balances ischemic event prevention with bleeding risk.
- Existing models do not adequately predict long-term bleeding events post-PCI.
Purpose of the Study:
- To develop and validate a predictive model for long-term bleeding events following percutaneous coronary intervention (PCI).
Main Methods:
- Analysis of 1-year bleeding outcomes from 3,128 PCI procedures in the PRISM observational study.
- Bleeding events categorized using Bleeding Academic Research Consortium (BARC) definitions.
- Logistic regression used to build a predictive model for BARC ≥1 bleeding.
Main Results:
- 18.4% of patients experienced BARC ≥1 bleeding within one year.
- Predictors of bleeding included female sex, Caucasian ethnicity, DES implantation, and warfarin use; diabetes was protective.
- A 10-variable model demonstrated good discrimination (c-statistic=0.667) and calibration for BARC ≥1 bleeding, and moderate discrimination for BARC ≥2 bleeding (c-statistic=0.653).
Conclusions:
- Bleeding is a frequent complication within the first year after PCI.
- Pre-procedural patient factors and drug-eluting stent (DES) use are significant predictors of bleeding risk.
- The developed model can aid in shared decision-making regarding stent choice and DAPT duration.
Objectives:
To construct a model to predict long-term bleeding events following percutaneous coronary intervention (PCI).
Background:
Treatment with dual antiplatelet therapy following PCI involves balancing the benefits of preventing ischemic events with the risks of bleeding. There are no models to predict long-term bleeding events after PCI.
Methods:
We analyzed 1-year bleeding outcomes from 3,128 PCI procedures in the Patient Risk Information Services Manager (PRISM) observational study. Patient-reported bleeding events were categorized according to Bleeding Academic Research Consortium (BARC) definitions. Logistic regression analysis was used to develop a model predicting BARC ≥ 1 bleeding.
Results:
BARC 0, 1, 2 or 3 bleeding was observed in 574 (18.4%); 2382 (76.2%); 114 (3.6%); and 58 (1.8%) patients, respectively. Compared to patients who had no bleeding, patients with BARC ≥ 1 bleeding were more often female (30 vs. 23%), Caucasian (94 vs. 83%), had a higher incidence of drug eluting stent (DES) implantation (83 vs. 76%) and warfarin therapy (7.4 vs. 3.9%), and a lower incidence of diabetes (31 vs. 45%; P-value <0.01 for all comparisons). A 27-variable model had moderate discrimination (c-statistic of 0.674), and good calibration, as did a parsimonious model with 10 variables (c-statistic = 0.667). This model performed well in predicting BARC ≥ 2 bleeding events as well (c-statistic = 0.653).
Conclusions:
Bleeding is common in the first year after PCI, and can be predicted by pre-procedural patient characteristics and use of DES. Objective estimates of bleeding risk may help support shared decision-making with respect to stent selection and duration of antiplatelet therapy following PCI. © 2016 Wiley Periodicals, Inc.
