The International Cardiac Arrest Research (I-CARE) Consortium Electroencephalography Database
Amorim, E.; Zheng, W.-L.; Ghassemi, M. M.; Aghaeeaval, M.; Kandhare, P.; Karukonda, V.; Lee, J. W.; Herman, S. T.; Sivaraju, A.; Gaspard, N.; Hofmeijer, J.; van Putten, M. J.; Sameni, R.; Reyna, M. A.; Clifford, G. D.; Westover, M. B.
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ObjectiveTo develop a harmonized multicenter clinical and electroencephalography (EEG) database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest. DesignMulticenter cohort, partly prospective and partly retrospective. SettingSeven academic or teaching hospitals from the U.S. and Europe. PatientsIndividuals aged 16 or older who were comatose after return of spontaneous circulation following a cardiac arrest who had continuous EEG monitoring were included. Interventionsnot applicable. Measurements and Main ResultsClinical 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. ConclusionsThe 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.
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