Babak Razavi

Utility of electroencephalography: Experience from a U.S. tertiary care medical center.

OBJECTIVE To investigate the utility of electroencephalography (EEG) for evaluation of patients with altered mental status (AMS). METHODS We retrospectively reviewed 200 continuous EEGs (cEEGs) obtained in ICU and non-ICU wards and 100 spot EEGs (sEEGs) obtained from the emergency department (ED) of a large tertiary medical center. Main outcomes were access time (from study request to hookup), and diagnostic yield (percentage of studies revealing significant abnormality). RESULTS Access time, mean±SD (maximum), was 3.5±3.2 (20.8) hours in ICU, 4.8±5.0 (25.6) hours in non-ICU, and 2.7±3.6 (23.9) hours in ED. Access time was not significantly different for stat requests or EEGs with seizure activity. While the primary indication for EEG monitoring was to evaluate for seizures as the cause of AMS, only 8% of cEEGs and 1% of sEEGs revealed seizures. Epileptiform discharges were detected in 45% of ICU, 24% of non-ICU, and 9% of ED cases, while 2% of ICU, 15% of non-ICU, and 45% of ED cases were normal. CONCLUSIONS Access to EEG is hampered by significant delays, and in emergency settings, the conventional EEG system detects seizures only in a minority of cases. SIGNIFICANCE Our findings underscore the inefficiencies of current EEG infrastructure for accessing diagnostically important information, as well as the need for more prospective data describing the relationship between EEG access time and EEG findings, clinical outcomes, and cost considerations.

Detecting silent seizures by their sound

The traditional approach to interpreting electroencephalograms (EEGs) requires physicians with formal training to visually assess the waveforms. This approach can be less practical in critical settings where a trained EEG specialist is not readily available to review the EEG and diagnose ongoing subclinical seizures, such as nonconvulsive status epilepticus.

Diagnostic utility of eight-channel EEG for detecting generalized or hemispheric seizures and rhythmic periodic patterns

Highlights • Current practice lacks rapid detection tools to screen for seizures.• High agreement exists between neurologists’ diagnoses using full and reduced montage EEG.• Reduced channel EEG can be used to screen for generalized or hemispheric or rhythmic and periodic abnormalities.

The clinical utility of qualitative electroencephalography during tilt table testing – A retrospective study

OBJECTIVE To assess electroencephalography (EEG) changes during tilt table testing in syncope and other orthostatic syndromes. METHODS We retrospectively reviewed consecutive tilt table studies with simultaneous EEG from April 2014 to May 2016 at our center. All patients had video EEG during tilt table. All patients had at least 10 min of head up tilt unless they had syncope or did not tolerate the study. Video EEG was interpreted by epileptologists. RESULTS Eighty-seven patients met the inclusion criteria. Mean age was 45 years, and 55 were women. Seven patients (∼8%) had syncope during tilt table, 11 patients (∼12%) had significant neurogenic orthostatic hypotension and a separate group of 11 patients (∼12%) had significant orthostatic tachycardia. Valsalva responses were abnormal in 7 of the 11 patients with orthostatic hypotension, suggesting an underlying neurogenic orthostatic hypotension. Visually discernable EEG changes were seen in only 3 patients (∼43%) who had syncope and in 1 patient (∼9%) with orthostatic tachycardia. CONCLUSIONS Qualitative EEG analysis based on visual inspection during tilt table study revealed abnormalities in less than half the patients with syncope and a very small fraction with orthostatic tachycardia. SIGNIFICANCE Routine qualitative EEG recording might not be clinically useful during tilt table studies.

T23. Individuals without EEG training can detect subclinical seizures and seizure-like activity by listening to sonified EEG

Introduction The traditional approach to interpreting EEG requires physicians with formal training to visually assess the waveforms. This approach can be less practical in critical settings where a trained EEG specialist may not be readily available to diagnose subclinical seizures, such as non-convulsive status epilepticus, in patients with altered mental status. As a proof of concept, we designed the current study to explore whether individuals without EEG training can detect ongoing seizures by simply listening to one channel of sonified EEG instead of viewing 20+ channels of EEG. Methods We selected 84, 15-s long, EEG samples to represent various conditions commonly seen in the ICU. Our reference standard was defined by unanimous agreement of 3 epileptologists reviewing visually displayed EEGs in double banana montage. Samples were classified as seizure (focal or generalized, n = 7), seizure-like (LPD, GPD, or burst suppression, n = 25), or non-periodic non-rhythmic (normal or focal/generalized slowing, n = 52). EEG data were then converted to sound files (separating left and right hemispheres to 168 clips, also 15 s long) using a novel sonification method. After a brief training video, medical students (n = 34) and nurses (n = 30) were asked to indicate each audio sample as “seizure” or “non-seizure”. We then compared their performance (sensitivity and specificity; reported as mean ± SD) with that of EEG experts [epilepsy attendings with >10 years of experience (n = 2) and epilepsy fellows (n = 7)] and some of the medical students (n = 29) who also diagnosed the same EEGs on visual display. Our prediction was that students and nurses without EEG training would be able to detect seizures in sonified EEGs with high sensitivity while they will be able to differentiate non-seizure or non-seizure-like events from seizure or seizure-like events with high specificity. Results Non-experts listening to single-channel sonified EEGs detected seizures with remarkable sensitivity (students: 98 ± 5%; nurses: 95 ± 14%) compared to experts or non-experts reviewing the same EEGs on visual display (attendings: 100%; fellows: 90 ± 11%; students: 76 ± 19%). If the EEGs contained seizures or seizure-like activity, non-experts listening to sonified EEGs rated them as seizures with high specificity (students: 85 ± 9%; nurses: 82 ± 12%) compared to experts or non-experts viewing the EEGs visually (attendings: 95 ± 1%; fellows: 91 ± 7%; students: 65 ± 20%). Conclusion Our study is the first of its kind to confirm that individuals without EEG training, such as medical students and nurses, can detect ongoing seizures or seizure-like rhythmic periodic activity by merely listening to short duration of sonified EEG. While sonification of EEG cannot replace the traditional approaches to EEG interpretation, it provides a meaningful triage tool for fast assessment of patients with suspected subclinical seizures.

S80. Utility of reduced montage EEG in detecting seizures or seizure-like activity

Introduction Standard scalp EEG is used to detect a wide range of cerebral pathologies. However, its utility in emergency and resource-limited settings may be impeded by delays in setup and interpretation. Past studies have investigated reduced channel arrays as screening tools, but inferred a lower utility in detecting epileptiform abnormalities. The current study tested the utility of reduced (8-channel) montage (rm-EEG) covering the lateral hemispheres compared to full (18-channel) montage (fm-EEG) for detection of generalized and hemispheric seizures and seizure-like patterns by neurologists with extensive EEG training, neurology residents with minimal EEG training, and medical students without EEG training. Methods Forty neurologists (7 epileptologists, 13 epilepsy fellows, 20 neurology residents) from 7 institutions and 42 medical students from Stanford University were presented 44 samples of EEG recordings (15-s long) as both fm-EEG and rm-EEG formats in a random order. Samples represented seizures ( n  = 8), seizure-like activity (lateralized or generalized periodic discharges or burst suppression, n  = 12) or non-rhythmic, non-periodic patterns (normal or slowing, n  = 24) as determined by majority agreement among 3 senior epileptologists with >10 years of training (Fleiss’ kappa 0.79). Both physicians and students were asked to determine whether each sample represented seizure activity (yes/no), while epileptologists and residents were also asked to specify any and all pathological activity present in each sample. We calculated the overall accuracy of fm-EEG and rm-EEG, as well as their sensitivity and specificity for seizures and seizure-like activity; differences were assessed using paired t -tests. Results EEG samples were evaluated with almost identical accuracy using fm-EEG (epileptologists: 88%; residents: 75%; students: 57%) and rm-EEG (epileptologists: 84%, p  = 0.156; residents: 75%, p  = 0.086; students: 57%, p  = 0.461). While epileptologists identified hemispheric or generalized seizure activity with high sensitivity using fm-EEG (99%) and rm-EEG (94%, p  = 0.172), individuals with minimal or no EEG experience demonstrated lower sensitivity using rm-EEG (residents: 79%; students: 45%) compared to fm-EEG (residents: 91%, p  = 0.031; students: 62%, p  = 0.048). However, specificity for seizures/seizure-like activity was greater using rm-EEG (epileptologists: 91%; residents: 84%; students: 73%) compared to fm-EEG (epileptologists: 85%, p  = 0.015; residents: 77%, p  = 0.018; students: 63%, p Conclusion Our study demonstrates that a reduction from 18 to 8 channels does not degrade the sensitivity for generalized and hemispheric seizures, and yet provide more specific information for ruling in such epileptic activity even when read by individuals with minimal or no EEG experience. On the basis of these findings, we suggest that a restricted channel configuration can be used for faster diagnosis of generalized and hemispheric seizures that ought to be detected and treated expeditiously.