Reproducibility, and sensitivity to motor unit loss in amyotrophic lateral sclerosis, of a novel MUNE method: MScanFit MUNE

再现性 肌萎缩侧索硬化 医学 电机单元 曲线下面积 变异系数 接收机工作特性 内科学 疾病 化学 解剖 色谱法
作者
Anna Bystrup Jacobsen,Hugh Bostock,Anders Fuglsang‐Frederiksen,Lene Duez,Sándor Beniczky,Anette Torvin Møller,Jakob Udby Blicher,Hatice Tankişi
出处
期刊:Clinical Neurophysiology [Elsevier BV]
卷期号:128 (7): 1380-1388 被引量:80
标识
DOI:10.1016/j.clinph.2017.03.045
摘要

To examine inter- and intra-rater reproducibility and sensitivity to motor unit loss of a novel motor unit number estimation (MUNE) method, MScanFit MUNE (MScan), compared to two traditional MUNE methods; Multiple point stimulation MUNE (MPS) and Motor Unit Number Index (MUNIX). Twenty-two ALS patients and 20 sex- and age-matched healthy controls were included. MPS, MUNIX, and MScan were performed twice each by two blinded physicians. Reproducibility of MUNE values was assessed by coefficient of variation (CV) and intra class correlation coefficient (ICC). Ability to detect motor unit loss was assessed by ROC curves and area under the curve (AUC). The times taken for each of the methods were recorded. MScan was more reproducible than MPS and MUNIX both between and within operators. The mean CV for MScan (12.3%) was significantly lower than for MPS (24.7%) or MUNIX (21.5%). All methods had ICC > 0.94. MScan and Munix were significantly quicker to perform than MPS (6.3 m vs. 13.2 m). MScan (AUC = 0.930) and MPS (AUC = 0.899) were significantly better at discriminating between patients and healthy controls than MUNIX (AUC = 0.831). MScan was more consistent than MPS or MUNIX and better at distinguishing ALS patients from healthy subjects. MScan may improve detection and assessment of motor unit loss.

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
二哈哈哈哈哈哈完成签到,获得积分10
刚刚
2秒前
霜降发布了新的文献求助10
3秒前
如意道天发布了新的文献求助10
3秒前
4秒前
5秒前
hxy完成签到,获得积分20
6秒前
霖槿发布了新的文献求助10
9秒前
鸟鸣发布了新的文献求助10
9秒前
10秒前
罗莹完成签到 ,获得积分10
10秒前
一下不怕完成签到,获得积分10
11秒前
lllll完成签到 ,获得积分20
11秒前
CodeCraft应助sky采纳,获得10
11秒前
13秒前
13秒前
wulala发布了新的文献求助10
13秒前
孔孔发布了新的文献求助10
13秒前
科研通AI6.4应助黑浩源采纳,获得30
13秒前
14秒前
15秒前
一下不怕发布了新的文献求助10
16秒前
17秒前
Sakura发布了新的文献求助10
17秒前
zhangzhang发布了新的文献求助10
17秒前
17秒前
21秒前
Nole应助yyy采纳,获得10
22秒前
Leung发布了新的文献求助10
23秒前
鸟鸣完成签到,获得积分10
23秒前
23秒前
科研通AI6.3应助zhangzhang采纳,获得10
23秒前
万能图书馆应助zhangzhang采纳,获得10
23秒前
燕子发布了新的文献求助10
25秒前
lgf发布了新的文献求助10
25秒前
九九应助yyy采纳,获得10
25秒前
深情安青应助Leung采纳,获得10
27秒前
lixinglei应助So采纳,获得20
27秒前
彭于晏应助是一颗大树呀采纳,获得10
28秒前
脑洞疼应助lgf采纳,获得10
29秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 2000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7554722
求助须知:如何正确求助?哪些是违规求助? 9137165
关于积分的说明 19529071
捐赠科研通 7146014
什么是DOI,文献DOI怎么找? 3260905
关于科研通互助平台的介绍 2427347
邀请新用户注册赠送积分活动 2249908