Application of neuro-electrophysiological techniques in sepsis-associated encephalopathy

YU Min; ZHAN Qing

doi:10.12022/jnnr.2017-0024

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Journal of Neurology and Neurorehabilitation ›› 2017, Vol. 13 ›› Issue (2) : 80-84. DOI: 10.12022/jnnr.2017-0024

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Application of neuro-electrophysiological techniques in sepsis-associated encephalopathy

YU Min, ZHAN Qing

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Abstract

Sepsis-associated encephalopathy (SAE) is a diffuse dysfunction of brain caused by systemic inflammation. It is often missed in clinical practice. At present, there is still a lack of unified and definite diagnostic criteria for SAE. The diagnosis is mainly based on clinical manifestations and electrophysiological and neuroimaging findings. As compared with computed tomography (CT) and magnetic resonance imaging (MRI), the changes of the disease in patients with SAE can be observed earlier by neuro-physiological techniques which are noninvasive and quick and the bedside operation can be conducted repeatedly. This paper reviews the progress in electroencephalogram and continuous electroencephalogram monitoring, somatosensory evoked potential, transcranial Doppler sonography and other neuro-physiological techniques in SAE.

Key words

Sepsis-associated encephalopathy / Neuro-electrophysiological techniques / Continuous electroencephalogram monitoring / Video electroencephalogram monitoring / Somatosensory evoked potential / Transcranial Doppler sonography

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YU Min, ZHAN Qing. Application of neuro-electrophysiological techniques in sepsis-associated encephalopathy[J]. Journal of Neurology and Neurorehabilitation. 2017, 13(2): 80-84 https://doi.org/10.12022/jnnr.2017-0024

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Funding

Youth Fund Project of Science and Technology Commission of Shanghai Municipality (No. 20164Y0073); Academic Research Project of Shanghai University of Traditional Chinese Medicine (No. 2016YG36); Course Construction Project of Shanghai University of Traditional Chinese Medicine (No. SHUTCMKCJSY2016090); Talents Training Program of Seventh People’s Hospital Affiliated to Shanghai University of Traditional Chinese Medicine (No. MZY2017-01; QMX2017-03)