Validity of a PCI Bleeding Risk Score in patient subsets stratified for body mass index

David R Dobies1, Kimberly R Barber2, Amanda L Cohoon3

  • 1Regional Cardiology Associates , Grand Blanc, Michigan , USA.

Open Heart
|March 7, 2015
PubMed

Insights

This study found that the National Cardiovascular Data Registry (NCDR) percutaneous coronary intervention (PCI) Bleeding Risk Score (BRS) had poor accuracy in predicting major bleeding events in a real-world patient population, even in high-risk subgroups.

Area of Science:

  • Cardiology
  • Clinical Risk Prediction
  • Health Outcomes Research

Background:

  • Accurate bleeding risk assessment is crucial for managing patients undergoing percutaneous coronary intervention (PCI).
  • Existing bleeding risk models often lack external validation in diverse clinical datasets.
  • The National Cardiovascular Data Registry (NCDR) PCI Bleeding Risk Score (BRS) is a widely used tool.

Purpose of the Study:

  • To externally validate the NCDR PCI BRS tool.
  • To assess the accuracy of the BRS in predicting major bleeding events.
  • To evaluate BRS performance in subgroups, including those based on body mass index (BMI).

Main Methods:

  • Retrospective analysis of a large, multisite registry dataset (37 hospitals).
  • Included 4693 patients undergoing PCI between June 2009 and June 2012.
  • Validated the NCDR PCI BRS, with major bleeding as the primary endpoint, using receiver operating characteristic (ROC) curve analysis.

Main Results:

  • The overall accuracy (Area Under the Curve [AUC]) of the BRS was poor to fair (0.71).
  • Accuracy was particularly low for specific anticoagulants (e.g., 0.65 for bivalirudin).
  • The tool's predictive value did not improve in intermediate-risk groups or among patients with low BMI.

Conclusions:

  • Current bleeding risk tools, including the NCDR PCI BRS, demonstrate limited diagnostic utility for major bleeding.
  • The predictive performance of these tools is insufficient for widespread clinical application.
  • Anticoagulation strategy significantly impacts the discrimination of bleeding risk models.
Abstract