Bleeding risk assessment tools for patients with myocardial infarction: a comparative review and clinical
Kaeshaelya Thiruchelvam1, Jonathan Than Chun Xin1, Win Kit Law1
1School of Pharmacy, IMU University, Bukit Jalil, Kuala Lumpur, Malaysia.
Insights
Bleeding risk stratification tools are crucial for managing myocardial infarction (MI) patients. This review examines established and emerging models, highlighting the need for dynamic, integrated approaches to improve patient outcomes.
Area of Science:
- Cardiology
- Clinical Risk Stratification
- Pharmacotherapy
Background:
- Optimizing ischemic protection while minimizing bleeding is critical for myocardial infarction (MI) patients, especially those on dual antiplatelet therapy (DAPT) post-percutaneous coronary intervention (PCI).
- Accurate bleeding risk stratification is essential for guiding treatment decisions and improving patient outcomes in MI management.
Purpose of the Study:
- To review and evaluate traditional and novel bleeding risk stratification models used in myocardial infarction (MI) management.
- To identify limitations of current models and suggest future research directions for enhanced risk assessment.
Main Methods:
- A systematic literature search was performed across PubMed, Scopus, and Web of Science for studies published between January 2005 and December 2024.
- Evaluation of established bleeding risk tools (CRUSADE, ACUITY-HORIZONS, ACTION, PRECISE-DAPT) and emerging models (SWEDEHEART, ARC-HBR, CREDO-KYOTO, BleeMACS).
Main Results:
- Established tools predict in-hospital and early post-discharge bleeding but have limitations in long-term assessment and adaptation to modern PCI.
- Emerging models incorporate broader clinical variables and long-term predictors, offering improved applicability to contemporary MI management.
- Current models show moderate predictive accuracy (c-statistics 0.70-0.80) and rely on static factors, lacking real-time applicability and integration of ischemic risk.
Conclusions:
- There is a need for advanced bleeding risk models that are dynamic, integrate ischemic risk, and are validated across diverse populations.
- Future research should focus on AI-driven models and integration into electronic health records for improved clinical decision-making.
- Enhanced bleeding risk stratification is crucial for balancing antithrombotic therapy and bleeding complications in MI patients.
Introduction:
Bleeding risk stratification tools are essential for optimizing ischemic protection while minimizing bleeding complications in patients with myocardial infarction, particularly for those undergoing percutaneous coronary intervention (PCI) or dual antiplatelet therapy.
Areas Covered:
A structured search of PubMed, Scopus, and Web of Science was conducted for studies published from January 2005 to December 2024. This review evaluates traditional and novel bleeding risk models in MI management. Established tools like CRUSADE, ACUITY-HORIZONS, ACTION, and PRECISE-DAPT aid in predicting in-hospital and early post-discharge bleeding but have limitations in long-term risk assessment and adapting to modern PCI techniques. Emerging models - SWEDEHEART, ARC-HBR, CREDO-KYOTO, and BleeMACS - offer enhanced risk stratification by incorporating broader clinical variables and long-term bleeding predictors, improving their applicability to contemporary MI management.
Expert Opinion:
Despite advancements, current models exhibit moderate predictive accuracy (c-statistics 0.70-0.80) and rely on static baseline factors, limiting real-time applicability. They also fail to integrate ischemic risk assessment, creating challenges in balancing thrombotic and bleeding risks. Future research should focus on AI-driven dynamic risk models, broader validation across diverse populations, and integrating bleeding and ischemic risk stratification into a unified framework. Embedding these tools into electronic health records will enhance clinical decision-making and improve patient outcomes.
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