Electroencephalography and Neuroimaging Markers of Poor Prognosis in Hypoxic-Ischemic Brain Injury

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2022-01-01

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Acıbadem Mehmet Ali Aydınlar Üniversitesi

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ABSTRACT Purpose: Hypoxic-ischemic brain injury (HIBI) can cause coma.Several factors may affect the outcome after HIBI and prediction of the prognosis is challenging in clinical practice.Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG) are two reliable tools to predict the possible outcome after brain damage.We aimed to test the utility of MRI and EEG in predicting the outcome by exploring specific lesion and electrophysiological patterns. Method: Patients admitted to the intensive care unit (ICU) due to hypoxic-ischemic brain injury between January 2017 and March 2020 were retrospectively reviewed.Patients over 18 years of age with a history of cardiac arrest or respiratory problems leading to hypoxic-ischemic brain injury were included in the study. Glasgow Coma Score (GCS) was used as a clinical measure for the level of consciousness.All patients had a Glasgow Coma Score (GCS) of <8 and had both MRI and EEG investigations.Patients were classified as having Poor Outcome (PO) and Good Outcome (GO).Poor outcome defines either death or lack of recovery in consciousness (GCS<8).MRI findings that could lead to a coma state were classified as “MRI-positive”, otherwise were classified as “MRI-negative”. Modified Hockaday Scale was used for grading of EEG. Results: Nineteen patients with HIBI were included. In the MRI-positive group, 87.5% of the patients had poor outcome whereas the remaining 12.5% had good outcome. In the MRI-negative group, 45.5% of the patients had poor outcome whereas the remaining 54.5% had good outcome. According to the Modified Hockaday EEG Grading System, 91% of the patients with a score of Grade 4 and above had poor outcome whereas only the remaining 9% had good outcome. Conclusion: Although MRI is a valuable clinical marker, EEG seems to be more reliable for predicting prognosis in HIBI.The modified Hockaday scale can be useful for determining the cut-off points for the prediction of poor prognosis.

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