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Precision Medicine for Anticoagulation Strategies in the Cath Lab: Part 2
Tanawat Attachaipanich1, Tania Ahuja2, Samin K Sharma3
1Department of Internal Medicine, University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA.
Managing anticoagulation during percutaneous coronary intervention (PCI) is complex in high-risk patients. This review highlights challenges and knowledge gaps in selecting, dosing, and monitoring anticoagulants for specific populations, emphasizing precision-guided strategies.
Area of Science:
- Cardiology
- Pharmacology
- Nephrology
Background:
- Intraprocedural anticoagulation during percutaneous coronary intervention (PCI) presents unique challenges in high-risk and underrepresented patient groups.
- Balancing thrombotic and bleeding risks is complex and often unpredictable in these populations.
Purpose of the Study:
- To review current evidence and identify knowledge gaps in anticoagulant selection, dosing, and monitoring for specific high-risk populations undergoing PCI.
- To address challenges in patients with advanced chronic kidney disease (CKD), cirrhosis, nonagenarians, thrombocytopenia, chronic oral anticoagulation, mechanical circulatory support, and STEMI post-fibrinolysis.
Main Methods:
- Review of contemporary evidence and existing literature on anticoagulation strategies in specialized patient cohorts.
- Analysis of challenges related to altered pharmacokinetics, rebalanced hemostasis, and device-specific risks.
Main Results:
- High-risk populations are often excluded from clinical trials, limiting evidence for optimal anticoagulation.
- Conventional bleeding risk scores have reduced predictive performance in these groups.
- Emerging strategies focus on precision-guided anticoagulation using patient-specific factors, pharmacogenomics, and real-time monitoring.
Conclusions:
- Optimal anticoagulation strategies for high-risk populations undergoing PCI require further investigation through dedicated prospective studies.
- Individualized, precision-guided approaches integrating patient-specific data and advanced monitoring are crucial for improving outcomes.
- There is a need for enhanced risk stratification tools and clinical decision support systems for these complex cases.
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