Literature DB >> 19163118

Predict the neurological recovery under hypothermia after cardiac arrest using C0 complexity measure of EEG signals.

Yueli Lu, Dineng Jiang, Xiaofeng Jia, Yihong Qiu, Yisheng Zhu, Nitish Thakor, Shanbao Tong.   

Abstract

Clinical trials have proven the efficacy of therapeutic hypothermia in improving the functional outcome after cardiac arrest (CA) compared with the normothermic controls. Experimental researches also demonstrated quantitative electroencephalogram (qEEG) analysis was associated with the long-term outcome of the therapeutic hypothermia in brain injury. Nevertheless, qEEG has not been able to provide a prediction earlier than 6h after the return of spontaneous circulation (ROSC). In this study, we use C0 complexity to analyze the nonlinear characteristic of EEG, which could predict the neurological recovery under therapeutic hypothermia during the early phase after asphyxial cardiac arrest in rats. Twelve Wistar rats were randomly assigned to 9-min asphyxia injury under hypothermia (33 degrees C, n=6) or normothermia (37 degrees C, n=6). Significantly greater C0 complexity was found in hypothermic group than that in normothermic group as early as 4h after the ROSC (P0.05). C0 complexity at 4h correlated well with the 72h neurodeficit score (NDS) (Pearson's correlation = 0.882). The results showed that the C0 complexity could be an early predictor of the long-term neurological recovery from cardiac arrest.

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Year:  2008        PMID: 19163118     DOI: 10.1109/IEMBS.2008.4649615

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

Review 1.  Quantitative measures of EEG for prediction of outcome in cardiac arrest subjects treated with hypothermia: a literature review.

Authors:  Shadnaz Asgari; Hana Moshirvaziri; Fabien Scalzo; Nima Ramezan-Arab
Journal:  J Clin Monit Comput       Date:  2018-02-26       Impact factor: 2.502

2.  COX5A over-expression protects cortical neurons from hypoxic ischemic injury in neonatal rats associated with TPI up-regulation.

Authors:  Ya Jiang; Xue Bai; Ting-Ting Li; Mohammed Al-Hawwas; Yuan Jin; Yu Zou; Yue Hu; Lin-Yi Liu; Ying Zhang; Qing Liu; Hao Yang; Jun Ma; Ting-Hua Wang; Jia Liu; Liu-Lin Xiong
Journal:  BMC Neurosci       Date:  2020-04-29       Impact factor: 3.288

3.  Exploring EEG Features in Cross-Subject Emotion Recognition.

Authors:  Xiang Li; Dawei Song; Peng Zhang; Yazhou Zhang; Yuexian Hou; Bin Hu
Journal:  Front Neurosci       Date:  2018-03-19       Impact factor: 4.677

  3 in total

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