Stroke and thromboembolism in atrial fibrillation: A systematic review of stroke risk factors, risk stratification schema and cost effectiveness data
Stroke and thromboembolism in atrial fibrillation: A systematic review of stroke risk factors, risk stratification schema and cost effectiveness data
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DOI：
10.1160/th07-08-0508
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发表时间：
2008-02-01
影响因子：
6.7
通讯作者：
Lip, Gregory Y. H.
中科院分区：
文献类型：
--
作者：
Hughes, Michael;Lip, Gregory Y. H.
需要评估每位患者房颤（AF）卒中的风险，以确定血栓预防的临床和成本效益，目的是适当使用抗血栓治疗。为了实现这一目标，需要识别AF人群中的卒中风险因素，并根据这些风险因素设计卒中风险分层模型。在这篇文章中，我们首先提供了一个系统的审查研究，检查各种临床，人口统计学和超声心动图患者特征的房颤人群中归因于中风的风险。其次，我们对已发表的卒中风险分层模型进行了系统回顾，回顾了卒中风险因素的结果及其准确区分不同卒中风险水平的能力。第三，我们回顾了与抗凝和抗血小板治疗作为AF患者血栓预防的成本效益相关的卫生经济学证据。纳入卒中风险因素系统综述的研究确定卒中或TIA病史、年龄增加、高血压和结构性心脏病（左心室功能障碍或肥大）是AF患者卒中风险的良好预测因子。有关糖尿病、性别和其他患者特征的证据不太一致。确定了三种卒中风险分层模型，这些模型能够区分不同类别的卒中风险，准确率至少为95%。很少有模式处理风险因素的累积性质，即风险因素的组合比单独的任何一个因素带来更大的风险。在卒中高危患者中，抗凝治疗具有成本效益，但对于卒中低风险患者则不然。根据卒中危险因素的可用证据和各种替代卒中危险分层模型，根据设计这些模型的证据及其在代表性AF人群中的表现对这些模型进行综述是重要的。房颤患者血栓预防的适当管理需要平衡抗血栓治疗的风险和获益及其成本效益。
The risk of stroke in atrial fibrillation (AF) needs to be assessed in each patient to determine the clinical and cost-effectiveness of thromboprophylaxis, with the aim of appropriate use of antithrombotic therapy. To achieve this, stroke risk factors in AF populations need to be identified and stroke risk stratification models have been devised on the basis of these risk factors. In this article, we firstly provide a systematic review of studies examining the attributable stroke risk of various clinical, demographic and echocardiographic patient characteristics in AF populations. Secondly, we performed a systematic review of published stroke risk stratification models, in terms of the results of the review of stroke risk factors and their ability to accurately discriminate between different levels of stroke risk. Thirdly, we review the health economic evidence relating to the cost-effectiveness of anticoagulation and antiplatelet therapy as thromboprophylaxis in AF patients. The studies included in the systematic review of stroke risk factors identified history of stroke or TIA, increasing age, hypertension and structural heart disease (left-ventricular dysfunction or hypertrophy) to be good predictors of stroke risk in AF patients. The evidence regarding diabetes mellitus, gender and other patient characteristics was less consistent. Three stroke risk stratification models were identified that were able to discriminate between different categories of stroke risk to at least 95% accuracy. Few models had addressed the cumulative nature of risk factors where a combination of risk factors would confer a greater risk than either factor alone. In patients at high risk of stroke, anticoagulation is cost effective, but not for those with a low risk of stroke. With the evidence available for stroke risk factors and the various alternative stroke risk stratification models, a review of these models in terms of the evidence on which they are devised and their performance in representative AF populations is important. The appropriate administration of thromboprophylaxis in AF patients would need to balance the risks and benefits of antithrombotic therapy with its cost-effectiveness.