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. 2014 Feb;20(1):32-9.
doi: 10.1007/s12028-013-9912-4.

Sensitivity of compressed spectral arrays for detecting seizures in acutely ill adults

Affiliations

Sensitivity of compressed spectral arrays for detecting seizures in acutely ill adults

Craig A Williamson et al. Neurocrit Care. 2014 Feb.

Abstract

Background: Continuous EEG recordings (cEEGs) are increasingly used in evaluation of acutely ill adults. Pre-screening using compressed data formats, such as compressed spectral array (CSA), may accelerate EEG review. We tested whether screening with CSA can enable detection of seizures and other relevant patterns.

Methods: Two individuals reviewed the CSA displays of 113 cEEGs. While blinded to the raw EEG data, they marked each visually homogeneous CSA segment. An independent experienced electroencephalographer reviewed the raw EEG within 60 s on either side of each mark and recorded any seizures (and isolated epileptiform discharges, periodic epileptiform discharges (PEDs), rhythmic delta activity (RDA), and focal or generalized slowing). Seizures were considered to have been detected if the CSA mark was within 60 s of the seizure. The electroencephalographer then determined the total number of seizures (and other critical findings) for each record by exhaustive, page-by-page review of the entire raw EEG.

Results: Within each of the 39 cEEG recordings containing seizures, one CSA reviewer identified at least one seizure, while the second CSA reviewer identified 38/39 patients with seizures. The overall detection rate was 89.0 % of 1,190 total seizures. When present, an average of 87.9 % of seizures were detected per individual patient. Detection rates for other critical findings were as follows: epileptiform discharges, 94.0 %; PEDs, 100 %; RDA, 97.9 %; focal slowing, 100 %; and generalized slowing, 100 %.

Conclusions: CSA-guided review can support sensitive screening of critical pathological information in cEEG recordings. However, some patients with seizures may not be identified.

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Conflict of interest statement

Drs. Williamson, Wahlster, Shafi and Westover declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1. Seizures and Artifact in CSA Displays
Compressed Spectral Array (CSA) displays, demonstrating a seizure (A) and muscle artifact (C). Each CSA displays 2 hours of EEG data. X-axis:time, Y-Axis:frequency (0-20Hz), Z axis: power with black representing lowest and white highest power. From top-to-bottom, the individual segments represent: left lateral power (Fp1-F7, F7-T3, T3-T5, T5-O1), left parasaggital power (Fp1-F3, F3-C3, C3-P3, P3-O1), right lateral power (Fp2-F8, F8-T4, T4-T6, T6-O2), right parasaggital power (Fp1-F4, F3-C4, C4-P4, P4-O2) and the relative asymmetry index. For the relative asymmetry index, red represents increased right-sided power and blue increased left-sided power. (A) Five seizures are present, marked by arrows (B) Section of the EEG corresponding to the EEG segment marked by the thick arrow, demonstrating seizure onset. (C) CSA display with several segments with muscle artifact, each marked by an arrow corresponding to where a CSA reviewer placed a mark. (D) Section of the EEG corresponding to the CSA segment marked by the thick arrow, displaying muscle artifact.
Figure 2
Figure 2. Examples of Seizures Missed By CSA Screening
Case 1 (A, B): A very focal right temporal seizure (onset marked by black arrows), lasting 20 sec, with no significant change in the CSA background, missed by both reviewers. Case 2 (C,D): A right frontotemporal seizure lasting 83 sec. This seizure was marked by reviewer 2 near the seizure onset (thick black arrow), but was ‘missed’ by reviewer 2 (thin black arrow) whose nearest CSA mark occurred 90 sec after the end of the seizure.
Figure 3
Figure 3. Sensitivity of CSA Screening for Seizures
The sensitivity (% of seizures present which were detected) for each of the two CSA reviewers is displayed on the y-axis vs. the number of seizures present in each cEEG recording (x-axis). The number of seizures is displayed on a logarithmic scale in order to provide better visualization of each data point.

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