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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.
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.
Objective:
An accurate tool with good discriminative for bleeding would be useful to clinicians for improved management of all their patients. Bleeding risk models have been published but not externally validated in independent clinical data set. We chose the National Cardiovascular Data Registry (NCDR) percutaneous coronary intervention (PCI) score to validate within a large, multisite community data set. The aim of the study was validation of this Bleeding Risk Score (BRS) tool among a subgroup of patients based on body mass index.
Methods:
This is a large-scale retrospective analysis of a current registry utilising data from a 37-hospital health system. The central repository of patients with coronary heart disease undergoing PCI between 1 June 2009 and 30 June 2012 was utilised to validate the NCDR PCI BRS among 4693 patients. The primary end point was major bleeding. Validation analysis calculating the receiver operating characteristic curve was performed.
Results:
There were 143 (3%) major bleeds. Mean BRS was 14.7 (range 3-42). Incidence of bleeding by risk category: low (0.5%), intermediate (1.7%) and high risk (7.6%). Tool accuracy was poor to fair (area-under-the curve (AUC) 0.78 heparin, 0.65 bivalirudin). Overall accuracy was 0.71 (CI 0.66 to 0.76). Accuracy did not improve when confined to just the intermediate risk group (AUC 0.58; CI 0.55 to 0.67). Tool accuracy was the lowest among the low BMI group (AUC 0.62) though they are at increased risk of bleeding following PCI.
Conclusions:
Bleeding risk tools have low predictive value even among subgroups of patients at higher risk. Adjustment for anticoagulation use resulted in poor discrimination because bivalirudin differentially biases outcomes toward no bleeding. The current state of bleeding risk tools provide little support for diagnostic utility in regards to major bleeding and therefore have limited clinical applicability.
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