Patient characteristics and compliance with positive airway pressure therapy during New York City's 2020 COVID-19 pandemic stay-at-home orders: The NYU comprehensive epilepsy center-sleep center telemedicine experience.

Objectives: We sought to evaluate the success of telemedicine during New York City's COVID-19 pandemic stay-at-home period, and understand the distribution of sleep complaints seen. We also compared positive airway pressure (PAP) therapy compliance for a random patient sample to determine whether the pandemic influenced PAP usage. Methods: Encounters from the stay-at-home period were reviewed for patient characteristics and clinician impressions, and were compared to administrative data from the prior 2.5 months ("control" period). PAP compliance was compared between the periods for a randomly selected group of forty patients. Results: The telemedicine show rate was 89.37%. Sleep apnea then insomnia were the predominant diagnoses. Insomnia complaints were higher during the stay-at-home period. PAP compliance and AHI were similar between the periods. Conclusions: Sleep apnea and insomnia were common complaints; insomnia was significantly more common during the pandemic. PAP compliance was similar between the two periods for a randomly selected cohort.

Continuous EEG findings in patients with COVID-19 infection admitted to a New York academic hospital system.

OBJECTIVE: There is evidence for central nervous system complications of coronavirus disease 2019 (COVID-19) infection, including encephalopathy. Encephalopathy caused by or arising from seizures, especially nonconvulsive seizures (NCS), often requires electroencephalography (EEG) monitoring for diagnosis. The prevalence of seizures and other EEG abnormalities among COVID-19-infected patients is unknown. METHODS: Medical records and EEG studies of patients hospitalized with confirmed COVID-19 infections over a 2-month period at a single US academic health system (four hospitals) were reviewed to describe the distribution of EEG findings including epileptiform abnormalities (seizures, periodic discharges, or nonperiodic epileptiform discharges). Factors including demographics, remote and acute brain injury, prior history of epilepsy, preceding seizures, critical illness severity scores, and interleukin 6 (IL-6) levels were compared to EEG findings to identify predictors of epileptiform EEG abnormalities. RESULTS: Of 111 patients monitored, most were male (71%), middle-aged or older (median age 64 years), admitted to an intensive care unit (ICU; 77%), and comatose (70%). Excluding 11 patients monitored after cardiac arrest, the most frequent EEG finding was moderate generalized slowing (57%), but epileptiform findings were observed in 30% and seizures in 7% (4% with NCS). Three patients with EEG seizures did not have epilepsy or evidence of acute or remote brain injury, although all had clinical seizures prior to EEG. Only having epilepsy (odds ratio [OR] 5.4, 95% confidence interval [CI] 1.4-21) or seizure(s) prior to EEG (OR 4.8, 95% CI 1.7-13) was independently associated with epileptiform EEG findings. SIGNIFICANCE: Our study supports growing evidence that COVID-19 can affect the central nervous system, although seizures are unlikely a common cause of encephalopathy. Seizures and epileptiform activity on EEG occurred infrequently, and having a history of epilepsy or seizure(s) prior to EEG testing was predictive of epileptiform findings. This has important implications for triaging EEG testing in this population.