The International Cardiac Arrest Research (I-CARE) Consortium Electroencephalography Database

Edilberto Amorim; Wei-Long Zheng; Mohammad M Ghassemi; Mahsa Aghaeeaval; Pravinkumar Kandhare; Vishnu Karukonda; Jong Woo Lee; Susan T Herman; Adithya Sivaraju; Nicolas Gaspard; Jeannette Hofmeijer; Michel J A M van Putten; Reza Sameni; Matthew A Reyna; Gari D Clifford; M Brandon Westover

doi:10.1101/2023.08.28.23294672

The International Cardiac Arrest Research (I-CARE) Consortium Electroencephalography Database

medRxiv [Preprint]. 2023 Aug 28:2023.08.28.23294672. doi: 10.1101/2023.08.28.23294672.

Authors

Edilberto Amorim^{1

2}, Wei-Long Zheng³, Mohammad M Ghassemi⁴, Mahsa Aghaeeaval¹, Pravinkumar Kandhare¹, Vishnu Karukonda¹, Jong Woo Lee⁵, Susan T Herman⁶, Adithya Sivaraju⁷, Nicolas Gaspard^{7

8}, Jeannette Hofmeijer^{9

10}, Michel J A M van Putten^{9

11}, Reza Sameni¹², Matthew A Reyna¹², Gari D Clifford^{12

13}, M Brandon Westover¹⁴

Affiliations

¹ Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA.
² Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
³ Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, CN.
⁴ Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, USA.
⁵ Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts, USA.
⁶ Department of Neurology, Barrow Neurological Institute, Comprehensive Epilepsy Center, Phoenix, Arizona, USA.
⁷ Department of Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
⁸ Department of Neurology, Universite Libre de Bruxelles, Brussels, Belgium.
⁹ Clinical Neurophysiology Group, University of Twente, Enschede, The Netherlands.
¹⁰ Department of Neurology, Rijnstate Hospital, Arnhem, The Netherlands.
¹¹ Department of Neurology and Clinical Neurophysiology, Medisch Spectrum Twente, The Netherlands.
¹² Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, Georgia, USA.
¹³ Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, Georgia, USA.
¹⁴ Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

Abstract

Objective: To develop a harmonized multicenter clinical and electroencephalography (EEG) database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest.

Design: Multicenter cohort, partly prospective and partly retrospective.

Setting: Seven academic or teaching hospitals from the U.S. and Europe.

Patients: Individuals aged 16 or older who were comatose after return of spontaneous circulation following a cardiac arrest who had continuous EEG monitoring were included.

Interventions: not applicable.

Measurements and main results: Clinical and EEG data were harmonized and stored in a common Waveform Database (WFDB)-compatible format. Automated spike frequency, background continuity, and artifact detection on EEG were calculated with 10 second resolution and summarized hourly. Neurological outcome was determined at 3-6 months using the best Cerebral Performance Category (CPC) scale. This database includes clinical and 56,676 hours (3.9 TB) of continuous EEG data for 1,020 patients. Most patients died (N=603, 59%), 48 (5%) had severe neurological disability (CPC 3 or 4), and 369 (36%) had good functional recovery (CPC 1-2). There is significant variability in mean EEG recording duration depending on the neurological outcome (range 53-102h for CPC 1 and CPC 4, respectively). Epileptiform activity averaging 1 Hz or more in frequency for at least one hour was seen in 258 (25%) patients (19% for CPC 1-2 and 29% for CPC 3-5). Burst suppression was observed for at least one hour in 207 (56%) and 635 (97%) patients with CPC 1-2 and CPC 3-5, respectively.

Conclusions: The International Cardiac Arrest Research (I-CARE) consortium database provides a comprehensive real-world clinical and EEG dataset for neurophysiology research of comatose patients after cardiac arrest. This dataset covers the spectrum of abnormal EEG patterns after cardiac arrest, including epileptiform patterns and those in the ictal-interictal continuum.

Keywords: EEG; database; heart arrest; hypoxic-ischemic encephalopathy; machine learning.

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Preprint

Abstract

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