Suppr超能文献

Limited value of stress electrocardiographic changes in predicting late 201Tl reversibility: do all patients need reinjection?

作者信息

Schroeder-Tanka J M, Tiel-van Buul M M, van der Wall E E, Lie K I, van Royen E A

机构信息

Department of Cardiology, University of Amsterdam, The Netherlands.

出版信息

Nucl Med Commun. 1996 Jan;17(1):15-9. doi: 10.1097/00006231-199601000-00004.

Abstract

The aim of this study was to assess the relationship between the exercise electrocardiogram (ECG) and late thallium-201 (201Tl) reversibility in a series of 72 consecutive patients with undiagnosed chest pain and an initial persistent perfusion defect on conventional stress/4-h redistribution imaging. We wished to establish the diagnostic accuracy of the exercise ECG in predicting the outcome of late 201Tl reversibility. All 72 patients, of whom 44 (61%) had had a previous myocardial infarction (MI), underwent quantitative planar 201Tl stress-redistribution imaging followed by resting 201Tl imaging 1-4 days later. Fifty (69%) patients showed exercise ECG changes during conventional stress-redistribution imaging, of whom 30 (42%) had a history of previous MI and 20 (28%) had suspected coronary artery disease (CAD). The overall diagnostic accuracy of the exercise ECG in predicting 201Tl reversibility was 83% (60/72 patients): 75% (21/28 patients) in patients with suspected CAD and 87% (39/44 patients) in patients with previous MI. Only the patients with a previous MI and a negative exercise ECG showed 100% accuracy (n = 14). We conclude that reinjection of 201Tl might be withheld in patients with a previous MI and a negative exercise ECG. For patients with previous MI and a positive exercise ECG, and for patients with suspected coronary artery disease regardless of the result of their exercise ECG, reinjection of 201Tl should be strongly considered if the redistribution images are abnormal, because of the suboptimal diagnostic accuracy of the exercise ECG in these patients.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验