Revelation of Brugada electrocardiographic pattern during a febrile state associated with acute myocardial infarction.

来自 PUBMED

作者:

Patanè SMarte F

展开

摘要:

The prevalence of the Brugada-type ECG and its natural history are still unclear. The Brugada syndrome is usually identified by a characteristic Brugada-type ECG that consists of ST elevation of a coved type in the precordial leads V1 to V3 and ventricular fibrillation that can lead to sudden cardiac death, although affected individuals may have a normal ECG. Mutations in the cardiac sodium channel gene SCN5A, which encodes the alpha-subunit of the human cardiac voltage-dependent Na+ channel (Na(v)1.5), are identified in 15-30% of patients with Brugada syndrome. Most SCN5A mutations lead to a 'loss-of-function' phenotype, reducing the Na+ current during the early phases of the action potential. Several nongenetic factors have been mentioned in the literature as possible inductors of the ECG pattern resembling Brugada syndrome. As such, a Brugada-type ECG may appear in some patients during febrile states and in those who are under the influence of cocaine and pharmaceutical drugs that have a sodium channel-blocking effect. It has been also reported chest pain and ST elevation Brugada pattern during febrile states. We present a case of revelation of Brugada pattern in a 69-year-old Italian man during a febrile state associated with acute myocardial infarction. Also this report confirms that Brugada pattern should be considered as one of differential diagnoses when we examine the patients during a febrile state.

收起

展开

DOI:

10.1016/j.ijcard.2008.12.037

被引量:

2

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(440)

参考文献(0)

引证文献(2)

来源期刊

-

影响因子:暂无数据

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读