Prognostic significance of specific EEG patterns after cardiac arrest in a Lisbon Cohort

• Main Authors: Beatriz Guedes, Manuel Manita, Ana Rita Peralta, Ana Catarina Franco, Luís Bento, Carla Bentes
• Format: Article
• Language: English
• Published: Elsevier 2020-01-01
• Series: Clinical Neurophysiology Practice
• Subjects: Cardiac Arrest; Outcome; EEG Pattern; Highly Malignant; Malignant; Benign
• Online Access: http://www.sciencedirect.com/science/article/pii/S2467981X20300214

Objective: To evaluate if EEG patterns considered highly malignant are reliable predictors not only of poor neurological outcome but also reliable predictors of death. Methods: Retrospectively, EEGs from Cardiac Arrest (CA) patients of two teaching hospitals in Lisbon were classified into 3 groups: highly malignant, malignant, and benign groups. Outcome was assessed at 6 months after CA by CPC (Cerebral Performance Categories) scale. We evaluated the accuracy of these patterns to predict poor neurological outcome and death. Results: We included 106 patients for analysis. All patients with a highly malignant EEG (n = 37) presented a poor neurological outcome. Those patterns were also associated with death. Malignant EEG patterns were not associated with poor neurological outcome. Benign EEG patterns were associated with good neurological recovery (p < 0.0001). Conclusion: Highly malignant EEG patterns were strongly associated with poor neurological outcome and can be considered to be predictors of death. Significance: This study increased the knowledge about the value of EEG as a tool in outcome prediction of patients after cardiac arrest.