Non-expert use of quantitative EEG displays for seizure identification in the adult neuro-intensive care unit

Deri̇ci̇oğlu, Neşe; Yetim, Ezgi; Baş, Demet Funda; Bilgen, Nuray; Çağlar, Gülşen; Arsava, Ethem Murat; Topçuoğlu, Mehmet Akif

doi:10.1016/j.eplepsyres.2014.10.013

Cited by 53 publications

(60 citation statements)

References 22 publications

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“…In particular, Topjian et al limited their patient population to pediatric patients who had suffered cardiac arrest, so the images were likely much less heterogeneous. Dericioglu et al noted similar false-positive rates of one seizure per two-hours of EEG, but the two nurses in this study had much higher sensitivities (Dericioglu et al , 2015). To ensure that nurses and neurophysiologists were presented with EEGs that reflect the wide variety of patterns seen in ICU practice, the current study used a challenging set of images that included many cases with significant artifact as well as periodic patterns on the ictal-interictal continuum (see supplementary material for the complete test images).…”

Section: Discussionsupporting

confidence: 42%

“…In a similar but smaller study, Dericioglu et al evaluated the ability of a critical care neurology fellow, one neurology resident and two Neuro-ICU nurses to detect seizures using aEEG and CDSA. They reported a sensitivity ranging from 88% to 99% and a specificity of 89 to 95%, with an overall false-positive rate of 1 per 2 hours of EEG (Dericioglu et al , 2015). …”

Section: Discussionmentioning

confidence: 99%

“…Compressed spectral arrays (CSA) are a common way to visualize EEG trends and have been used in most prior studies of the use of qEEG for seizure detection in adults (Moura et al , 2014; Williamson et al , 2014; Dericioglu et al , 2015; Swisher et al , 2015; Topjian et al , 2015). CSA is produced by applying spectral estimation techniques to continuous EEG data, thereby producing a three-dimensional compressed spectrogram with time on the x-axis, frequency on the y-axis, and EEG power on the z-axis (Bickford et al , 1972; Bricolo et al , 1978).…”

Section: Introductionmentioning

confidence: 99%

“…A handful of studies have also evaluated the sensitivity of CSA alone for detecting seizures by physicians and ICU nurses (Stewart et al , 2010; Pensirikul et al , 2013; Dericioglu et al , 2015; Swisher et al , 2015; Topjian et al , 2015). Of all members of the care team, ICU nurses have the most frequent patient interaction and are typically charged with alerting physicians to changes in vital signs, neurological status, cardiac telemetry and other monitored systems.…”

Section: Introductionmentioning

confidence: 99%

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Performance of Spectrogram-Based Seizure Identification of Adult EEGs by Critical Care Nurses and Neurophysiologists

Amorim

Williamson

Moura

et al. 2017

Journal of Clinical Neurophysiology

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SUMMARY Introduction Continuous EEG screening using spectrograms or compressed spectral arrays (CSAs) by neurophysiologists has shorter review times with minimal loss of sensitivity for seizure detection when compared with visual analysis of raw EEG. Limited data is available on the performance characteristics of CSA-based seizure detection by neurocritical care nurses. Methods This is a prospective, cross-sectional study that was conducted in two academic neurocritical care units and involved thirty-three neurointensive care unit nurses and four neurophysiologists. Results All nurses underwent a brief training session prior to testing. Forty two-hour CSA segments of continuous EEG were reviewed and rated for the presence of seizures. Two experienced clinical neurophysiologists blinded to the CSA data performed conventional visual analysis of the raw EEG and served as the gold standard. The overall accuracy was 55.7% among nurses and 67.5% among neurophysiologists. Nurse seizure detection sensitivity was 73.8%, and the false-positive rate was 1-per-3.2 hours. Sensitivity and false alarm rate for the neurophysiologists was 66.3% and 1-per-6.4 hours, respectively. Inter-rater agreement for seizure screening was fair for nurses (Gwet’s AC1 statistic: 43.4%) and neurophysiologists (AC1: 46.3%). Conclusions Training nurses to perform seizure screening utilizing continuous EEG CSA displays is feasible and associated with moderate sensitivity. Nurses and neurophysiologists had comparable sensitivities, but nurses had a higher false-positive rate. Further work is needed to improve sensitivity and reduce false-alarm rates.

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Section: Discussionsupporting

confidence: 42%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Performance of Spectrogram-Based Seizure Identification of Adult EEGs by Critical Care Nurses and Neurophysiologists

Amorim

Williamson

Moura

et al. 2017

Journal of Clinical Neurophysiology

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“…One study that included 5 neuroscience nurses who received a 15 minute training tutorial had a sensitivity for seizure detection on CDSA and aEEG of 87%, but with a specificity of 61.6%(35). Furthermore, a study including 2 neurointensive care nurses who underwent a 5–6 hour training had a sensitivity of 92–99% and specificity of 89–90% for seizure detection on aEEG and CDSA used together (36). While our study has a lower sensitivity for seizure detection, it remains unclear as to whether or not duration of training impacts accuracy.…”

Section: Discussionmentioning

confidence: 99%

Seizure Detection by Critical Care Providers Using Amplitude-Integrated Electroencephalography and Color Density Spectral Array in Pediatric Cardiac Arrest Patients

Pont‐Thibodeau

Sánchez

Jawad

et al. 2017

Pediatric Critical Care Medicine

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Objective Determine the accuracy and confidence of CCM providers to identify seizures using amplitude-integrated EEG (aEEG) versus aEEG combined with Color Density Spectral Array electroencephalography (aEEG+CDSA) Design tutorial and questionnaire. Subjects Pediatric critical care providers (attendings, fellows, nurses). Interventions A standardized powerpoint tutorial on aEEG and CDSA followed by classification of 100 aEEG images and 100 aEEG combined with CDSA as displaying seizures or not displaying seizures. Measurements and Main Results EEG tracings were obtained from children monitored with continuous EEG after cardiac arrest. The gold standard for seizure identification was continuous EEG interpretation by a pediatric electroencephalographer. The same EEG tracings were used to generate images containing only aEEG or aEEG+CDSA. Twenty-three CCM providers underwent a 30-minute tutorial on aEEG and CDSA interpretation. They were then asked to determine if there were seizures on 100 aEEG images and 100 aEEG+CDSA. aEEG seizure detection sensitivity was 77% (95%CI: 73%–80%), specificity of 65% (95%CI: 62%–67%), negative predictive value (NPV) of 88% (95%CI: 86%–90%) and positive predictive value (PPV) of 46% (95%CI: 43%–49%). For aEEG+CDSA, sensitivity was 77% (95%CI: 74%–81%), specificity of 68% (95%CI: 66%–71%), NPV of 89% (95%CI: 87%–90%) and PPV of 49% (95%CI: 46%–52%). Sensitivity for status epilepticus detection was 77% (95%CI: 71%–82%) with aEEG and 75% (95%CI: 69%–81%) with aEEG+CDSA. The addition of CDSA to aEEG did not improve seizure detection. However, 87% of CCM providers qualitatively felt that combining both modalities increased their ability to detect seizures. Conclusions aEEG and aEEG+CDSA offer reasonable sensitivity and NPV for seizure detection by CCM providers. aEEG+CDSA did not improve seizure detection over aEEG alone, although CCM providers felt more confident using both tools combined. aEEG and CDSA require further evaluation as a tool for screening for seizures and should only be used in conjunction with professional cEEG review.

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Successful treatment of non‐convulsive status epilepticus diagnosed using bedside monitoring by a combination of amplitude‐integrated and two‐channel simplified electroencephalography

Egawa

Hifumi

Kawakita

et al. 2015

Acute Medicine & Surgery

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Case: A 66-year-old man developed disturbed consciousness and right hemiparesis with transient convulsions in the right arm.Bedside monitoring using a combination of amplitude-integrated electroencephalography and two-channel simplified electroencephalography revealed intermittent episodes of 1-3 Hz δ waves lasting for approximately 5 min, consistent with non-convulsive status epilepticus. Fosphenytoin (22.5 mg/kg/day) and levetiracetam (1,000 mg) prevented right arm convulsions but did not restore consciousness. The two-channel simplified electroencephalography also showed an intermittent periodic δ wave pattern in the Fp1-C3 channel. Conventional electroencephalography revealed a polymorphic δ activity that was abolished by 2.5 mg diazepam, thus confirming the diagnosis of non-convulsive status epilepticus. Outcome:The patient recovered completely with the antiepileptic drug combination. Conclusion: Immediate initiation of bedside monitoring using amplitude-integrated electroencephalography and two-channel simplified electroencephalography allows early detection of non-convulsive status epilepticus in patients with disturbed consciousness, which considerably improves the prognosis.

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Non-expert use of quantitative EEG displays for seizure identification in the adult neuro-intensive care unit

Cited by 53 publications

References 22 publications

Performance of Spectrogram-Based Seizure Identification of Adult EEGs by Critical Care Nurses and Neurophysiologists

Performance of Spectrogram-Based Seizure Identification of Adult EEGs by Critical Care Nurses and Neurophysiologists

Seizure Detection by Critical Care Providers Using Amplitude-Integrated Electroencephalography and Color Density Spectral Array in Pediatric Cardiac Arrest Patients

Successful treatment of non‐convulsive status epilepticus diagnosed using bedside monitoring by a combination of amplitude‐integrated and two‐channel simplified electroencephalography

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