Comparing non-invasive diagnostic methods for arteriovenous fistula stenosis: a prospective study

医学 狭窄 放射科 超声波 接收机工作特性 动静脉瘘 瘘管 内科学
作者
Sukit Raksasuk,Weerakit Naweera,Satit Rojwatcharapibarn,Thatsaphan Srithongkul
出处
期刊:Journal of Ultrasound [Springer Science+Business Media]
卷期号:26 (3): 687-693 被引量:4
标识
DOI:10.1007/s40477-022-00731-x
摘要

International guidelines recommend screening for arteriovenous fistula (AVF) stenosis using various non-invasive methods. We evaluate different non-invasive AVF flow measurements for detecting AVF stenosis. Twenty-three haemodialysis patients with suspected AVF stenosis are enrolled based on abnormal physical signs or high venous pressure during dialysis. Ultrasound dilution, urea dilution, Doppler ultrasonography, and fistulography are performed on all patients. The accuracy of three non-invasive methods is compared. Fistulography reveals AVF stenosis in 18 patients, 12 of whom have severe stenosis (greater than 50% stenosis in diameter). Concerning the location of the stenosis lesions, eight are at the inflow site, six at the outflow site, and four on both sites. Receiver operating characteristic curve analysis shows that Doppler ultrasonography has a high discriminative ability and the averaged areas under the curves are 0.933 (95% confidence interval [CI]; 0.81 to 0.99) for stenosis and 0.929 (95% CI 0.82–0.99) for severe stenosis. The sensitivity of each method for the prediction of access stenosis using ultrasound dilution, urea dilution, and Doppler ultrasonography is 73%, 73%, and 80%, respectively. The respective specificity of each method is 40%, 80%, and 100%, respectively. Physical examination (PE) shows an 80% sensitivity and 80% specificity in the detection of AVF stenosis. The combination of Doppler ultrasound with PE produces the highest sensitivity (93%) for detecting AVF stenosis. Doppler ultrasound combined with physical examination is more accurate than other non-invasive methods for detecting AVF stenosis.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
叁壶薏苡完成签到,获得积分10
1秒前
Jacob完成签到,获得积分10
1秒前
井盖发完成签到,获得积分10
1秒前
1秒前
U2完成签到,获得积分10
2秒前
sasamuxi完成签到 ,获得积分10
2秒前
希望天下0贩的0应助pbj采纳,获得10
2秒前
卢孤菱完成签到,获得积分10
2秒前
Jack完成签到,获得积分10
3秒前
yh发布了新的文献求助20
3秒前
咕噜噜完成签到 ,获得积分20
3秒前
tt完成签到,获得积分20
3秒前
笨笨豆芽完成签到 ,获得积分10
4秒前
Kuhaku完成签到,获得积分10
4秒前
小李可可萘完成签到,获得积分10
4秒前
零吾完成签到 ,获得积分10
5秒前
幸运周周周完成签到,获得积分10
5秒前
FashionBoy应助叁壶薏苡采纳,获得10
5秒前
星辰大海应助wang1343259150采纳,获得10
5秒前
5秒前
5秒前
尼克的朱迪完成签到,获得积分10
6秒前
jygjhgy完成签到,获得积分10
6秒前
6秒前
Li完成签到,获得积分10
6秒前
所所应助卢孤菱采纳,获得10
6秒前
太行行者发布了新的文献求助10
7秒前
天涯完成签到,获得积分10
7秒前
谢小盟举报量子星尘求助涉嫌违规
8秒前
8秒前
ni完成签到,获得积分10
8秒前
朴素幼晴完成签到 ,获得积分10
9秒前
鹿小娇完成签到,获得积分10
9秒前
小王完成签到,获得积分10
9秒前
852应助fate8680采纳,获得10
9秒前
9秒前
omo发布了新的文献求助10
9秒前
魔幻以菱完成签到 ,获得积分10
9秒前
10秒前
chen完成签到,获得积分10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of Milkfat Fractionation Technology and Application, by Kerry E. Kaylegian and Robert C. Lindsay, AOCS Press, 1995 1000
A novel angiographic index for predicting the efficacy of drug-coated balloons in small vessels 500
Textbook of Neonatal Resuscitation ® 500
The Affinity Designer Manual - Version 2: A Step-by-Step Beginner's Guide 500
Affinity Designer Essentials: A Complete Guide to Vector Art: Your Ultimate Handbook for High-Quality Vector Graphics 500
Optimisation de cristallisation en solution de deux composés organiques en vue de leur purification 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5080970
求助须知:如何正确求助?哪些是违规求助? 4298646
关于积分的说明 13392584
捐赠科研通 4122376
什么是DOI,文献DOI怎么找? 2257684
邀请新用户注册赠送积分活动 1262038
关于科研通互助平台的介绍 1196129