Background. Interest in electroencephalographic (EEG) coronavirus disease 2019 (COVID-19) findings has been growing, especially in the search for a specific-features EEG of encephalopathy. Methods. We made a retrospective analysis of 29 EEGs recorded in 15 patients with COVID-19 and neurological symptoms. We classified the EEGs as “Acute EEG” and “follow-up EEG.” We did a statistical analysis between voltage and respiratory status of the patient, stay or not in the intensive care unit (ICU), days of stay in the ICU, sedative drugs, pharmacological treatment, type of symptoms predominating, and outcome. Results. We found EEG abnormalities in all patients studied. We observed the amplitude of background <20 µV at 93% of “acute EEG,” versus only 21.4% of “follow-up EEG.” The average voltage went from 12.33 ± 5.09 µV in the acute EEGs to 32.8 ± 20.13 µV in the follow-up EEGs. A total of 60% of acute EEGs showed an intermittent focal rhythmic. We have not found a statistically significant association between voltage of acute EEG and nonneurological clinical status (including respiratory) that may interfere with the EEG findings. Conclusions. Nonspecific diffuse slowing EEG pattern in COVID-19 is the most common finding reported, but we found in addition to that, as a distinctive finding, low voltage EEG, that could explain the low prevalence of epileptic activity published in these patients. A metabolic/hypoxic mechanism seems unlikely on the basis of our EEG findings. This pattern in other etiologies is reminiscent of severe encephalopathy states associated with poor prognosis. However, an unreactive low voltage pattern in COVID-19 patients is not necessarily related to poor prognosis.

Introduction. Non-convulsive status epilepticus (NCSE) has been traditionally a challenging electroencephalographic (EEG) diagnosis. For this reason, Salzburg consensus criteria (SCC) have been proposed to facilitate correct diagnosis. Methods. We retrospectively reanalyzed 41 cases referred to our department (from 2016 to 2018) under the suspicion of NCSE. In this study, we compared the original description (standard criteria) versus the updated description (SCC) of the same EEG. Results. Originally, 15 patients were diagnosed as NCSE (37%) and 26 patients as no NCSE (63%), using the standard criteria. Then, we analyzed EEGs according to the SCC, which led to the following results: 9 patients fulfilled the criteria for definite NCSE (22%), 20 patients were diagnosed as possible NCSE (49%) and 12 patients were diagnosed as no NCSE (29%). Subsequently, when we analyze the outcome of possible NCSE cases, we note that 50% of these patients presented mild-poor outcome (neurological deficits, deceased). Indeed, we observed worse outcomes in patients previously diagnosed as no NCSE and untreated, specifically post-anoxic cases. Conclusions. Salzburg criteria seem to be a useful tool to support NCSE diagnosis, introducing the category of possible NCSE. In our study, we observed that it contributes to improving the prognosis and management of the patients. However, more prospective studies are needed to demonstrate the accuracy of SCC.

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