Predictive value of pulmonary venous flow patterns in detecting mitral regurgitation and left ventricular abnormalities.

医学 二尖瓣反流 心脏病学 内科学 预测值 心脏病
作者
Hynes Ms,Tam Jl,Burwash Ig,Ka Fai Chan
出处
期刊:PubMed 卷期号:15 (6): 665-70
链接
标识
摘要

To determine whether abnormalities in pulmonary venous flow (PVF) patterns detected by transesophageal echocardiography (TEE) correlate with the severity of mitral regurgitation (MR) or the presence of left ventricular (LV) abnormalities, and to demonstrate whether a normal PVF pattern predicts the absence of structural heart disease.Review of all TEEs performed at a tertiary care cardiac hospital over a four-month period.Among 195 studies, 100 fulfilled the inclusion criteria.PVF was categorized into three patterns, which have been described previously. A normal PVF pattern predicted the absence of clinically significant MR with a high degree of certainty (positive predictive value [PPV] 98%). However, it did not predict the absence of structural cardiac disease (PPV 64%). A PVF pattern that showed systolic flow reversal was strongly predictive of the presence of significant MR (sensitivity 86%, specificity 100%, PPV 100%). The frequency of significant MR in this group was much higher than in patients with normal PVF (12 of 12 versus one of 66, P<0.0001). Patients with a blunted PVF pattern were more likely than patients with a normal PVF to have LV abnormalities (18 of 22 versus 23 of 66, P=0.0005). However, a blunted PVF was not associated with clinically significant MR.A normal PVF does not rule out the absence of LV abnormalities but confirms the absence of significant MR. Systolic flow reversal is highly predictive of the presence of significant MR. A blunted PVF is more likely to be associated with LV abnormalities than with MR and has limited usefulness in the diagnosis of significant MR.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
完美世界应助顺利鱼采纳,获得10
1秒前
搜集达人应助招财不肥采纳,获得10
2秒前
sweetbearm应助李秋静采纳,获得10
2秒前
Michael_li完成签到,获得积分10
2秒前
whs完成签到,获得积分10
4秒前
科研通AI5应助xlj采纳,获得10
5秒前
再干一杯发布了新的文献求助10
5秒前
6秒前
满意的天完成签到 ,获得积分10
6秒前
luoshiwen完成签到,获得积分10
6秒前
落寞的觅柔完成签到,获得积分10
8秒前
9秒前
LUNWENREQUEST发布了新的文献求助10
9秒前
10秒前
11秒前
123cxj完成签到,获得积分10
14秒前
CO2发布了新的文献求助10
14秒前
summer发布了新的文献求助10
14秒前
15秒前
Xx.发布了新的文献求助10
15秒前
大大关注了科研通微信公众号
15秒前
稚祎完成签到 ,获得积分10
15秒前
15秒前
CodeCraft应助东东采纳,获得10
16秒前
17秒前
叽里咕噜完成签到 ,获得积分10
18秒前
田様应助zccc采纳,获得10
19秒前
隐形的雁完成签到,获得积分10
19秒前
追寻的秋玲完成签到,获得积分10
20秒前
李繁蕊发布了新的文献求助10
20秒前
21秒前
舒心的紫雪完成签到 ,获得积分10
22秒前
22秒前
24秒前
24秒前
25秒前
不上课不行完成签到,获得积分10
26秒前
再干一杯完成签到,获得积分10
26秒前
27秒前
汉堡包应助rudjs采纳,获得10
28秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527961
求助须知:如何正确求助?哪些是违规求助? 3108159
关于积分的说明 9287825
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540070
邀请新用户注册赠送积分活动 716926
科研通“疑难数据库(出版商)”最低求助积分说明 709808