Log In

Forgot Password?

OR

Not a member? Continue as a nonmember.

Become a Member

By becoming a member of the AAN, you can receive exclusive information to help you at every stage of your career. Benefits include:

Join Now See All Benefits

Loading... please wait

Abstract Details

Temporal dynamics of triphasic waves and generalized periodic discharges
Epilepsy/Clinical Neurophysiology (EEG)
P10 - Poster Session 10 (8:00 AM-9:00 AM)
9-012

Distinguishing epileptiform generalized periodic discharges (GPDs) and triphasic waves (TWs) can be challenging (Foreman et al., 2016), and consequential since groups may benefit from anti-seizure medications differently. Discharge regularity is an important feature recapitulated in computational models of TWs (Song et al., 2019) and GPDs (Ruijter et al., 2017). Recent analysis of GPDs in patients after cardiac arrest have shown that regularity of GPD duration, morphology, and amplitude, based on visual scoring, portend worse prognoses (Nadjar et al., 2022). This suggests that variability of discharges could be a quantifiable tool in distinguishing GPDs from TWs.

To quantitatively compare triphasic waves and generalized periodic discharges on scalp EEG.

We retrospectively collected inpatient EEG recordings marked to show GPDs and TWs from Harborview Medical Center between 11/2020 and 5/2021. The best derivation of a 30 second artifact free period on average reference montage was low pass filtered (0-15hz) for analysis. After visually identifying discharges, interdischarge intervals (IDIs) were calculated based on maximal deflection of each discharge. For each EEG, variance of IDIs was normalized by median IDI, to calculate a regularity index (RI). RI of GPDs and TWs were compared with a one-tailed Wilcoxon rank sum test.

24 EEGs with TWs and 33 EEGs with GPDs were studied. Median RI for TWs was 0.438 with a variance of 3.08. Median RI for GPDs was 0.368 with a variance of 4.31. Groups were not statistically different (p=0.08). Excluding EEGs of following cardiac arrest, 23 EEGs with TWs and 10 EEGs with GPDs were studied. Median RI of TWs was 0.430 with variance of 3.14. Median RI of GPDs was 3.14 with variance of 13.7. Groups were not statistically different (p=0.27).

Comparison of normalized variability in IDI does not distinguish TWs from GPDs but may have utility in the context of other clinical data.

Authors/Disclosures
George Plummer, MD (University of Washington)
PRESENTER
Dr. Plummer has nothing to disclose.
Ryan Raut, PhD Dr. Raut has nothing to disclose.
Bingni Brunton, PhD (University of Washington) Dr. Brunton has received personal compensation for serving as an employee of University of Washington. The institution of Dr. Brunton has received research support from National Science Foundation . The institution of Dr. Brunton has received research support from Air Force Office of Scientific Research. The institution of Dr. Brunton has received research support from National Science Foundation.
Shahin Hakimian, MD (UW Regional Epilepsy Center At Harborview) Dr. Hakimian has received personal compensation in the range of $500-$4,999 for serving as a Consultant for OptumRx. Dr. Hakimian has stock in Various.