Xpert Ultra in diagnosing extrapulmonary TB: accuracy and trace calls

医学 金标准(测试) 肺外结核 诊断准确性 内科学 前瞻性队列研究 病理 肺结核 结核分枝杆菌
作者
Marilyn M. Ninan,Priscilla Rupali,George M. Varghese,E. Shalini,Venkatesh Krishnan,Mark Ranjan Jesudason,Grace Rebekah,J. S. Michael
出处
期刊:International Journal of Tuberculosis and Lung Disease [International Union Against Tuberculosis and Lung Disease]
卷期号:26 (5): 441-445 被引量:2
标识
DOI:10.5588/ijtld.21.0480
摘要

INTRODUCTION: Xpert Ultra (Ultra) was developed to improve the detection of TB; however, data on Ultra´s diagnostic accuracy in extrapulmonary TB (EPTB) are limited.METHODS: In this prospective diagnostic accuracy study, 242 EPTB samples were subjected to Ultra and Xpert MTB/Rif (Xpert) testing, and these were compared with both culture and a composite gold standard.RESULTS: Compared to culture, Ultra sensitivity and specificity using bone, cerebrospinal fluid (CSF), lymph node and tissue samples, and overall were respectively 100% and 77.3%, 75% and 100%, 87.5% and 87.5%, 100% and 87%, and 89.7% and 87.4%; in comparison to the composite gold standard, Ultra´s sensitivity and specificity were respectively 66.7% and 100%, 17.6% and 100%, 46.9% and 95.7%, 38.5% and 94.1%, and 46.2% and 96.9%. Using latent class analysis, sensitivity and specificity were respectively 94.5% and 96.3% for Ultra, 65.5% and 99.8% for Xpert, and 58.6% and 99.2% for culture. There were 22/242 (9%) trace calls on Ultra.CONCLUSION: We found improved sensitivity for Ultra compared to Xpert, although Ultra specificity was lower, with a large number of trace results (9%).

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
ding应助科研通管家采纳,获得30
刚刚
刚刚
乐乐应助科研通管家采纳,获得10
刚刚
t忒对完成签到 ,获得积分20
刚刚
领导范儿应助科研通管家采纳,获得10
刚刚
Ava应助科研通管家采纳,获得10
1秒前
充电宝应助科研通管家采纳,获得10
1秒前
所所应助樱桃茶采纳,获得10
1秒前
香蕉觅云应助科研通管家采纳,获得10
1秒前
汉堡包应助科研通管家采纳,获得10
1秒前
小二郎应助科研通管家采纳,获得10
1秒前
星辰大海应助科研通管家采纳,获得10
1秒前
打打应助科研通管家采纳,获得10
2秒前
小小发布了新的文献求助10
2秒前
2秒前
李爱国应助科研通管家采纳,获得10
2秒前
2秒前
英俊的铭应助科研通管家采纳,获得10
2秒前
2秒前
包破茧完成签到,获得积分0
2秒前
我是老大应助yzz采纳,获得10
2秒前
2秒前
bkagyin应助科研通管家采纳,获得10
2秒前
十三应助科研通管家采纳,获得10
3秒前
烟花应助科研通管家采纳,获得10
3秒前
今后应助Hugo采纳,获得10
3秒前
十三应助科研通管家采纳,获得10
3秒前
大个应助科研通管家采纳,获得10
3秒前
sword发布了新的文献求助10
3秒前
健壮的妙海关注了科研通微信公众号
4秒前
123完成签到,获得积分20
4秒前
在水一方应助==采纳,获得10
5秒前
鲁啊鲁发布了新的文献求助10
6秒前
慕青应助李兴雅采纳,获得10
6秒前
6秒前
6秒前
能干戒指发布了新的文献求助20
7秒前
7秒前
7秒前
西西完成签到,获得积分10
7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
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
Advanced Weaponeering Fourth Edition, Volume 2 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 7516571
求助须知:如何正确求助?哪些是违规求助? 9104509
关于积分的说明 19436150
捐赠科研通 7121550
什么是DOI,文献DOI怎么找? 3253841
关于科研通互助平台的介绍 2422562
邀请新用户注册赠送积分活动 2240741