Antithrombotic Therapy in Patients Undergoing Transcatheter Aortic Valve Implantation.
Francesco PallanteRenato Francesco Maria ScaliseVictoria Garcia RuizGiampiero VizzariPietro IannelloLucio TeresiGabriele CarciottoStefania Lo GiudiceGiustina IuvaraGiulia LaterraAnder RegueiroGennaro GiustinoJuan Horacio Alonso BrialesJose Maria HernandezMarco BarbantiAntonio MicariFrancesco PatanèPublished in: Journal of clinical medicine (2024)
Transcatheter aortic valve implantation (TAVI) now represents the mainstay of treatment for severe aortic stenosis. Owing to its exceptional procedural efficacy and safety, TAVI has been extended to include patients at lower surgical risk, thus now encompassing a diverse patient population receiving this treatment. Yet, long-term outcomes also depend on optimal medical therapy for secondary vascular prevention, with antithrombotic therapy serving as the cornerstone. Leveraging data from multiple randomized controlled trials, the current guidelines generally recommend single antithrombotic therapy, with either single antiplatelet therapy (SAPT) or oral anticoagulation (OAC) alone in those patients without or with atrial fibrillation, respectively. Yet, individualization of this pattern, as well as specific case uses, may be needed based on individual patient characteristics and concurrent procedures. This review aims to discuss the evidence supporting antithrombotic treatments in patients treated with TAVI, indications for a standardized treatment, as well as specific considerations for an individualized approach to treatment.
Keyphrases
- transcatheter aortic valve implantation
- aortic stenosis
- ejection fraction
- atrial fibrillation
- aortic valve
- aortic valve replacement
- transcatheter aortic valve replacement
- patients undergoing
- antiplatelet therapy
- coronary artery disease
- left ventricular
- healthcare
- squamous cell carcinoma
- systematic review
- radiation therapy
- newly diagnosed
- end stage renal disease
- percutaneous coronary intervention
- venous thromboembolism
- chronic kidney disease
- case report
- machine learning