Mengdi Jiang1, Yingying Su2, Gang Liu1, Weibi Chen1, Daiquan Gao1. 1. Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China. 2. Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China. Electronic address: suyingying@xwh.ccmu.edu.cn.
Abstract
BACKGROUND: Quantitative electroencephalography (QEEG) data are useful to predict outcomes of cerebral infarction patients. This study was performed to establish the value of QEEG in the prediction of outcomes in patients with large hemispheric infarction (LHI). METHODS: A prognostic blinded cohort study was conducted on patients diagnosed with LHI in our neurocritical care unit. The electroencephalography (EEG) was recorded at the bedside within 3 days of LHI onset. Each EEG expert scored the raw EEG, and QEEG parameters including the absolute power, (delta + theta)/ (alpha + beta) ratio and brain symmetry index were obtained afterwards. Baseline data including Glasgow Coma Scale (GCS) was recorded at the meantime. Outcomes included survival or non-survival at the time of discharge and 6 months after the onset of LHI. RESULTS: A total of 50 patients entered into the final analysis. There were no differences in baseline data or visual EEG grades between survival and non-survival groups. QEEG analysis showed that the absolute theta power of all of the electrodes and the contralateral electrodes was significantly higher in the non-survival group than in the survival group at discharge. Multivariable logistic regression analysis demonstrated that theta power of the contralateral electrodes was an independent predictor of death at discharge and at 6 months. Compared to the GCS and EEG grading, the QEEG index exhibited higher accuracy in predicting non-survival outcomes. CONCLUSIONS: Among QEEG indices, theta power is valuable in predicting non-survival outcome in participants and is superior to visual EEG and GCS.
BACKGROUND: Quantitative electroencephalography (QEEG) data are useful to predict outcomes of cerebral infarctionpatients. This study was performed to establish the value of QEEG in the prediction of outcomes in patients with large hemispheric infarction (LHI). METHODS: A prognostic blinded cohort study was conducted on patients diagnosed with LHI in our neurocritical care unit. The electroencephalography (EEG) was recorded at the bedside within 3 days of LHI onset. Each EEG expert scored the raw EEG, and QEEG parameters including the absolute power, (delta + theta)/ (alpha + beta) ratio and brain symmetry index were obtained afterwards. Baseline data including Glasgow Coma Scale (GCS) was recorded at the meantime. Outcomes included survival or non-survival at the time of discharge and 6 months after the onset of LHI. RESULTS: A total of 50 patients entered into the final analysis. There were no differences in baseline data or visual EEG grades between survival and non-survival groups. QEEG analysis showed that the absolute theta power of all of the electrodes and the contralateral electrodes was significantly higher in the non-survival group than in the survival group at discharge. Multivariable logistic regression analysis demonstrated that theta power of the contralateral electrodes was an independent predictor of death at discharge and at 6 months. Compared to the GCS and EEG grading, the QEEG index exhibited higher accuracy in predicting non-survival outcomes. CONCLUSIONS: Among QEEG indices, theta power is valuable in predicting non-survival outcome in participants and is superior to visual EEG and GCS.
Authors: Amanda A Vatinno; Annie Simpson; Viswanathan Ramakrishnan; Heather S Bonilha; Leonardo Bonilha; Na Jin Seo Journal: Neurorehabil Neural Repair Date: 2022-03-20 Impact factor: 3.919
Authors: J Lanzone; M A Colombo; S Sarasso; F Zappasodi; M Rosanova; M Massimini; V Di Lazzaro; G Assenza Journal: Clin Neurophysiol Date: 2022-03-08 Impact factor: 4.861