Suppr超能文献

用于阻塞性冠状动脉疾病的欧洲心脏病学会预测试概率估计:它们能在巴西使用吗?

ESC pre-test probability estimates for obstructive coronary artery disease: can they be used in Brazil?

作者信息

Erthal Fernanda, Lima Ronaldo, Penna Filipe, Chow Benjamin J W, Gismondi Ronaldo

机构信息

Department of Medicine (Cardiology), Universidade Federal Fluminense, Rua Marques de Parana 303, 24033-900 Niteroi, Brazil.

DASA/CDPI, Avenida das Américas 4666, Rio de Janeiro, RJ 22640-102, Brazil.

出版信息

Eur Heart J Imaging Methods Pract. 2024 Jul 17;2(3):qyae075. doi: 10.1093/ehjimp/qyae075. eCollection 2024 Jul.

Abstract

AIMS

Cardiovascular disease, primarily coronary artery disease (CAD), is the leading cause of mortality worldwide. Accurate diagnosis of CAD often requires pre-test probability (PTP) estimation, traditionally performed using scoring systems like the Diamond-Forrester (DF) and European Society of Cardiology (ESC) models. However, the applicability of such models in specific populations may vary. This study compares the performance of DF and PTP scores in the Brazilian context, using coronary computed tomography angiography (CCTA) as a reference standard.

METHODS AND RESULTS

PTP for obstructive CAD was calculated using DF and ESC scores in 409 symptomatic patients without known CAD who underwent CCTA between 2019 and 2022. Predicted PTP was compared with actual CAD prevalence. DF overestimated CAD prevalence across age and symptom categories, while ESC showed better alignment with actual prevalence.

CONCLUSION

Our study confirms that the ESC PTP model is more appropriate than the DF model for determining PTP in the Brazilian population.

摘要

目的

心血管疾病,主要是冠状动脉疾病(CAD),是全球范围内的主要死因。CAD的准确诊断通常需要进行预测试概率(PTP)评估,传统上使用Diamond-Forrester(DF)和欧洲心脏病学会(ESC)模型等评分系统来进行。然而,此类模型在特定人群中的适用性可能有所不同。本研究以冠状动脉计算机断层扫描血管造影(CCTA)作为参考标准,比较了DF和PTP评分在巴西人群中的表现。

方法与结果

对2019年至2022年间接受CCTA检查的409例无已知CAD的有症状患者,使用DF和ESC评分计算阻塞性CAD的PTP。将预测的PTP与实际CAD患病率进行比较。DF在各个年龄和症状类别中均高估了CAD患病率,而ESC与实际患病率的一致性更好。

结论

我们的研究证实,在巴西人群中,ESC PTP模型比DF模型更适合用于确定PTP。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc60/11367947/c36fe2a7efb8/qyae075_ga.jpg

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