Suppr超能文献

改变房颤抗凝模式:达比加群、阿哌沙班和利伐沙班。

Changing anticoagulant paradigms for atrial fibrillation: dabigatran, apixaban and rivaroxaban.

机构信息

Department of Cardiology and Cardiovascular Surgery, FLENI, Montañeses 2325 (1428), Buenos Aires, Argentina.

出版信息

Expert Opin Pharmacother. 2011 Mar;12(4):567-77. doi: 10.1517/14656566.2011.528754. Epub 2011 Jan 22.

Abstract

INTRODUCTION

Vitamin K antagonists (VKAs) are the main therapeutic agents used to prevent embolic events in patients with atrial fibrillation (AF). Despite their proven efficacy, VKAs are underused and have several limitations. In recent years, there has been great interest in the development of new oral anticoagulants with a more efficient pharmacological profile, first tested in venous thromboembolism prevention and later in AF.

AREAS COVERED

The authors review the pharmacological differences between dabigatran, rivaroxaban and apixaban, and potential subgroups of patients in whom these new drugs would constitute a possible alternative to VKA therapy. Pharmacodynamic and pharmacokinetic data from each compound are analyzed in respect to their potential use in AF. This article provides an exhaustive review of the current status of this topic and the controversies still regarding each drug.

EXPERT OPINION

Apixaban and rivaroxaban are under evaluation for thromboembolic prevention in AF; dabigatran was recently approved for this indication. Therefore, it is important to know the characteristics of these drugs as a potential alternative to VKAs.

摘要

简介

维生素 K 拮抗剂(VKAs)是预防心房颤动(AF)患者栓塞事件的主要治疗药物。尽管已证明它们具有疗效,但 VKAs 的使用不足且存在多种局限性。近年来,人们对开发具有更高效药理学特性的新型口服抗凝剂产生了浓厚的兴趣,这些药物首先在预防静脉血栓栓塞症方面进行了测试,随后在 AF 中进行了测试。

涵盖领域

作者回顾了达比加群、利伐沙班和阿哌沙班之间的药理学差异,以及这些新药可能替代 VKA 治疗的潜在亚组患者。分析了每种化合物的药效学和药代动力学数据,以了解它们在 AF 中的潜在用途。本文对这一主题的最新进展和每个药物仍存在的争议进行了详尽的综述。

专家意见

阿哌沙班和利伐沙班正在评估用于 AF 的血栓栓塞预防;达比加群最近也被批准用于该适应症。因此,了解这些药物作为 VKAs 的潜在替代物的特性非常重要。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验