Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics

doi:https://doi.org/10.7554/eLife.36173

	Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics
	Song Ming1,2 ; Yi Yang 3; Jianghong He 3; Zhengyi Yang1,2 ; Shan Yu1,2 ; Qiuyou Xie 4; Xiaoyu Xia 3; Yuanyuan Dang 3; Qiang Zhang 3; Xinhuai Wu 5; Yue Cui1,2 ; Bing Hou1,2 ; Ronghao Yu 4; Ruxiang Xu 3; Tianzi Jiang1,2,6,7,8
发表期刊	eLife
	2018-08-14
卷号	2018 期号:7 页码:e36173
摘要	Disorders of consciousness are a heterogeneous mixture of different diseases or injuries. Although some indicators and models have been proposed for prognostication, any single method when used alone carries a high risk of false prediction. This study aimed to develop a multidomain prognostic model that combines resting state functional MRI with three clinical characteristics to predict one year outcomes at the single-subject level. The model discriminated between patients who would later recover consciousness and those who would not with an accuracy of around 88% on three datasets from two medical centers. It was also able to identify the prognostic importance of different predictors, including brain functions and clinical characteristics. To our knowledge, this is the first reported implementation of a multidomain prognostic model based on resting state functional MRI and clinical characteristics in chronic disorders of consciousness, which we suggest is accurate, robust, and interpretable.
关键词	Disorders Of Consciousness Prognosis Resting State Fmri Functional Connectivity Brain Network
DOI	https://doi.org/10.7554/eLife.36173
收录类别	SCI ; SSCi
WOS记录号	WOS:000444967900001
引用统计	被引频次：49[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/22078
专题	脑图谱与类脑智能实验室_脑网络组研究
通讯作者	Tianzi Jiang
作者单位	1.National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences 2.Brainnetome Center, Institute of Automation, The Chinese Academy of Sciences, 3.Department of Neurosurgery, PLA Army General Hospital 4.Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command 5.Department of Radiology, PLA Army General Hospital 6.CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences 7.Key Laboratory for Neuroinformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China 8.The Queensland Brain Institute, University of Queensland
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Song Ming,Yi Yang,Jianghong He,et al. Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics[J]. eLife,2018,2018(7):e36173.
APA	Song Ming.,Yi Yang.,Jianghong He.,Zhengyi Yang.,Shan Yu.,...&Tianzi Jiang.(2018).Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics.eLife,2018(7),e36173.
MLA	Song Ming,et al."Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics".eLife 2018.7(2018):e36173.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
Song_Yang_elife_2018（7400KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览下载