Intraoperative enhancement of effective connectivity in the default mode network predicts postoperative delirium following cardiovascular surgery

Xuanwei Zeng,Yong Yang,Qiaoqiao Xu,Huimiao Zhan, Haoan Lv,Zhiqiang Zhou,Xin Ma, Xiaojuan Liu, Jiaojiao Gui,Qianruo Kang, Neal Xiong,Junfeng Gao,Hua Zheng

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE(2023)

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摘要
Postoperative delirium is a common and preventable complication after cardiovascular surgery and is associated with increased risk of morbidity and mortality. However, strategies for identifying at-risk patients are limited. In this prospective observational study, intraoperative electroencephalography data of 50 patients undergoing cardiovascular surgery were collected. Twenty-five patients of them experienced delirium after surgery and 25 patients did not. The partial directional coherence method was used to evaluate the effective connectivity within the default mode network (DMN) regions in four frequency bands. Statistically significant features were considered as input signals in the CatBoost classifier to predict postoperative delirium. Compared with patients without delirium, patients with postoperative delirium had enhancement of causal effects in the DMN area, especially in the delta band. The accuracy rate of distinguishing patients with postoperative delirium from patients without postoperative delirium could reach 89.1%. These findings might help to explain why information processing was disturbed in patients with delirium and predict postoperative delirium.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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关键词
postoperative delirium,effective connectivity,intraoperative enhancement,default mode network
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