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Abstract Details

COVID-19 Patient's Background Frequency on EEG Predictive of Hospital Discharge Disposition
Epilepsy/Clinical Neurophysiology (EEG)
P2 - Poster Session 2 (11:45 AM-12:45 PM)
10-006
To determine whether background frequency on encephalogram (EEG) was associated with hospital discharge disposition in COVID-19 patients.
Neurological complications, including encephalopathy, have been reported up to 80% of hospitalized COVID-19 patients. It is unclear how encephalopathy during acute illness is related to clinical outcomes in COVID-19 patients.
Subjects were drawn from hospitalized patients who received an EEG at single tertiary center between March 2020 and February 2021. Included were adult subjects with confirmed COVID-19 during hospitalization who were not in the intensive care unit at the time of EEG evaluation. Clinical outcome measured was disposition upon discharge, graded as variables: 0-home, 1-acute rehabilitation, 2-subacute rehabilitation, 3-long term acute care hospital, and 4-death. Background frequency on EEG was used as a measure of encephalopathy severity and was assessed in occipital channels. EEG and medical records were reviewed retrospectively. We used two-independent t test for univariate analysis. Significant variables were then analyzed with multivariate linear regression in SPSS. Study was approved by the University of Chicago IRB.

A total of 50 subjects were included. Reasons for EEG were concern for seizure (n=14, 28.0%), altered mental status (n=33, 66.0%), and others (n=3, 6.0%). According to WHO COVID-19 severity scale, on admission 37 (74%) patients had ambulatory disease, 11 (22%) had moderate disease, and 2 (4.0%) severe disease. Thirteen (26.0%) patients received COVID-19 treatment, 4 (8.0%) with steroid. Sodium upon admission, history of epilepsy, cefepime use, intubation, and EEG background frequency were all significant predictors of disposition with univariate analysis (p <0.05). Multivariate analysis showed only intubation (B 1.347, p=0.03) and background frequency on EEG (B -0.282, p <0.001) as independent predictors of disposition.

EEG background frequency was a predictor of discharge disposition in COVID-19 patients, and patient with low background frequencies were less likely to be discharged home.

Authors/Disclosures
Wonhee Lee, MD (University of Chicago Hospitals)
PRESENTER 		Dr. Lee has nothing to disclose.
Kaitlin Seibert, MD Dr. Seibert has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Eli Lilly. The institution of Dr. Seibert has received research support from Retirement Research Foundation. The institution of Dr. Seibert has received research support from Center for Healthcare Delivery Science and Innovation. Dr. Seibert has received personal compensation in the range of $500-$4,999 for serving as a Consultant with Eli Lilly. Dr. Seibert has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant with NeurologyLive.
Alexandra Eid, MD (George Washington University) Dr. Eid has nothing to disclose.
Amy Espinal, MD (The University of Chicago) Dr. Espinal has nothing to disclose.
Sumayyah Abumurad, MBBS (Irbid specialty hospital) Dr. Abumurad has nothing to disclose.
Sara A. Klein, MD (Novant Health Neurology) Dr. Klein has nothing to disclose.
Fabiane Lima, MD (SCPMG) No disclosure on file
Shasha Wu, MD, PhD (University of Chicago) Dr. Wu has nothing to disclose.
No disclosure on file
James X. Tao, MD, PhD Dr. Tao has nothing to disclose.
Naoum P. Issa, MD, PhD (University of Chicago) The institution of Dr. Issa has received research support from NIH. Dr. Issa has received intellectual property interests from a discovery or technology relating to health care. Dr. Issa has received personal compensation in the range of $0-$499 for serving as a Study Section Member with NIH. Dr. Issa has a non-compensated relationship as a Scientific advisory board member with Theta Neurotech that is relevant to AAN interests or activities.