A score system used to screen the suitability for recanalization in carotid artery occlusions

颈内动脉 医学 管腔(解剖学) 闭塞 放射科 颈动脉 对比度(视觉) 逻辑回归 心脏病学 动脉 内科学 人工智能 计算机科学
作者
Weitao Jin,Xun Ye,Xiaolin Chen,Ran Duan,Yang Zhao,Yukun Zhang,Weijing Wang,Xin Lou,Yuanli Zhao,Ning Ma,Rong Wang
出处
期刊:Biotechnology & Genetic Engineering Reviews [Taylor & Francis]
卷期号:40 (3): 2760-2775 被引量:3
标识
DOI:10.1080/02648725.2023.2202522
摘要

Recanalization of chronic occluded internal carotid arteries has the potential to provide significant benefits for patients in the future, but the procedure is technically challenging. Therefore, this study aimed to identify a better method to predict the success of recanalization for patients with chronic internal carotid artery occlusion. The study's overall success rate was 73.77%. The multivariate logistic regression analysis revealed that two factors were independent predictors of successful recanalization: the continuous low signal lumen in the occluded segment of the internal carotid artery on the MRI image without contrast (OR: 15.9; 95% CI: 2.67-94.63) and the architecture of the clinoid segment of the internal carotid artery on the MRI image with contrast (OR: 11.97; 95% CI: 2.44-58.79). Based on the model coefficient, the researchers established an MRI score system. The MRI score system's area under the curve (AUC) in predicting successful recanalization was 0.916 (95% CI: 0.815 to 0.972; p < 0.001) with a sensitivity of 83.33% and a specificity of 72.22%. Compared to the previous score system based on the DSA morphology, the MRI system had a similar sensitivity and a better specificity. Therefore, the continuous low signal lumen in the occluded segment of the internal carotid artery on the MRI image without contrast and the architecture of the clinoid segment of the internal carotid artery on the MRI image with contrast were identified as independent predictors for successful recanalization in patients with chronic internal carotid artery occlusion (CICAO).
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
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
刚刚
酷酷亦凝发布了新的文献求助10
1秒前
JanaL完成签到,获得积分10
1秒前
1秒前
贾思敏完成签到 ,获得积分10
2秒前
小二郎的应助被so采纳,获得10
2秒前
moon发布了新的文献求助10
2秒前
Hanls关注了科研通微信公众号
3秒前
LEO发布了新的文献求助10
3秒前
MRzhu完成签到,获得积分10
4秒前
4秒前
fpc关闭了fpc的文献求助
5秒前
小九发布了新的文献求助10
5秒前
NexusExplorer的应助被wangxiangqin采纳,获得10
6秒前
子悦发布了新的文献求助10
6秒前
wylwyl完成签到,获得积分10
7秒前
csy发布了新的文献求助10
7秒前
9秒前
10秒前
顺利的八宝粥完成签到,获得积分10
13秒前
13秒前
JamesPei的应助被邪恶青年采纳,获得10
14秒前
kai发布了新的文献求助30
14秒前
Lyn完成签到,获得积分10
15秒前
彭于晏的应助被庆13采纳,获得10
15秒前
薛定谔的猫完成签到,获得积分10
16秒前
英姑的应助被科研通管家采纳,获得10
18秒前
脑洞疼的应助被科研通管家采纳,获得10
18秒前
18秒前
华仔的应助被科研通管家采纳,获得10
18秒前
orixero的应助被科研通管家采纳,获得10
18秒前
隐形曼青的应助被科研通管家采纳,获得10
18秒前
脑洞疼的应助被科研通管家采纳,获得10
18秒前
Owen的应助被科研通管家采纳,获得10
18秒前
JamesPei的应助被科研通管家采纳,获得10
19秒前
19秒前
赘婿的应助被科研通管家采纳,获得10
19秒前
19秒前
FashionBoy的应助被科研通管家采纳,获得10
19秒前
今后的应助被科研通管家采纳,获得10
19秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
The Student's Guide to Social Neuroscience 600
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
A Will for the Machine: Computerization, Automation, and the Arts in South Africa 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7810697
求助须知:如何正确求助?哪些是违规求助? 9342433
关于积分的说明 20512217
捐赠科研通 7403541
什么是DOI,文献DOI怎么找? 3329460
关于科研通互助平台的介绍 2476320
邀请新用户注册赠送积分活动 2348358