Frederic Zubler1, Christa Koenig2, Andreas Steimer2, Stephan M Jakob3, Kaspar A Schindler2, Heidemarie Gast2. 1. Department of Neurology, Bern University Hospital, University of Bern, Bern, Switzerland. Electronic address: frederic.zubler@gmail.com. 2. Department of Neurology, Bern University Hospital, University of Bern, Bern, Switzerland. 3. Department of Intensive Care Medicine, Bern University Hospital, University of Bern, Bern, Switzerland.
Abstract
OBJECTIVE: Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. METHODS: In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS: Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS: EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE: Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.
OBJECTIVE: Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatosepatients. METHODS: In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS: Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS: EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE: Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.
Authors: Frank A Rasulo; Philip Hopkins; Francisco A Lobo; Pierre Pandin; Basil Matta; Carla Carozzi; Stefano Romagnoli; Anthony Absalom; Rafael Badenes; Thomas Bleck; Anselmo Caricato; Jan Claassen; André Denault; Cristina Honorato; Saba Motta; Geert Meyfroidt; Finn Michael Radtke; Zaccaria Ricci; Chiara Robba; Fabio S Taccone; Paul Vespa; Ida Nardiello; Massimo Lamperti Journal: Neurocrit Care Date: 2022-07-27 Impact factor: 3.532
Authors: Michael Müller; Andrea O Rossetti; Rebekka Zimmermann; Vincent Alvarez; Stephan Rüegg; Matthias Haenggi; Werner J Z'Graggen; Kaspar Schindler; Frédéric Zubler Journal: Crit Care Date: 2020-12-07 Impact factor: 9.097