Journal of Clinical Neurophysiology最新文献

Purpose: High-frequency oscillation (HFO) in scalp electroencephalography is a promising new noninvasive prognostic epilepsy biomarker, but further data are needed to ascertain the utility of this parameter. The present work investigated the association between epileptic activity and scalp HFO in pediatric patients with various types of epilepsy, using multivariable regression models to correct for possible confounding factors.

Methods: The authors analyzed 97 subjects who were divided into groups with active epilepsy (within 1 year of seizure), seizure-free epilepsy (>1 year without seizure), and nonepilepsy. Regarding the frequency of seizure occurrence as an indicator of epileptic activity, we categorized subjects into four groups (Daily/Weekly, Monthly, Yearly, and Rarely).

Results: Multiple linear regression analysis showed that the scalp HFO detection rate was significantly higher in patients with active epilepsy than in those with nonepilepsy (β [95% confidence interval] = 2.77 [1.79-4.29]; P < 0.001). The association between scalp HFO detection rate and frequency of seizure occurrence was highest in the Daily/Weekly group (β [95% confidence interval] = 3.38 [1.57-7.27]; P = 0.002), followed by Monthly and Yearly groups (β [95% confidence interval] = 2.42 [1.02-5.73]; P = 0.046 and 0.36 [0.16-0.83]; P = 0.017). In addition, HFO duration, number of peaks, and number of channels detected were significantly higher in patients with active epilepsy.

Conclusions: Pediatric patients with active epilepsy and high frequency of seizure occurrence exhibited a higher scalp HFO detection rate. These results may help to establish HFO detectable by noninvasive scalp electroencephalography as a biomarker of active epilepsy in pediatric patients.

Purpose: To evaluate the clinical and electrographic characteristics of critically ill pediatric patients with lateralized rhythmic delta activity (LRDA) and compare them with patients with lateralized periodic discharges (LPDs).

Methods: This was a retrospective study examining consecutive critically ill pediatric patients (1 month-18 years) with LRDA or LPDs monitored on continuous electroencephalography. Clinical, radiologic, and electrographic characteristics; disease severity; and acute sequelae were compared between the two groups.

Results: Of 668 pediatric patients monitored on continuous electroencephalography during the study period, 12 (1.79%) patients had LRDA and 15 (2.24%) had LPDs. The underlying etiologies were heterogeneous with no difference in the acuity of brain MRI changes between both groups. Lateralized rhythmic delta activity and LPDs were concordant with the side of MRI abnormality in most patients [85.7% (LRDA) and 83.3% (LPD)]. There was no difference in the measures of disease severity between both groups. Seizures were frequent in both groups (42% in the LRDA group and 73% in the LPD group). Patients in the LPD group had a trend toward requiring a greater number of antiseizure medications for seizure control (median of 4 vs. 2 in the LRDA group, p = 0.09), particularly those patients with LPDs qualifying as ictal-interictal continuum compared with those without ictal-interictal continuum ( p = 0.02).

Conclusions: Lateralized rhythmic delta activity and LPDs are uncommon EEG findings in the pediatric population. Seizures occur commonly in patients with these patterns. Seizures in patients with LPDs, especially those qualifying as ictal-interictal continuum, showed a trend toward being more refractory. Larger studies are needed in the future to further evaluate these findings.

Purpose: Seizures occur in up to 40% of neonates with neonatal encephalopathy. Earlier identification of seizures leads to more successful seizure treatment, but is often delayed because of limited availability of continuous EEG monitoring. Clinical variables poorly stratify seizure risk, and EEG use to stratify seizure risk has previously been limited by need for manual review and artifact exclusion. The goal of this study is to compare the utility of automatically extracted quantitative EEG (qEEG) features for seizure risk stratification.

Methods: We conducted a retrospective analysis of neonates with moderate-to-severe neonatal encephalopathy who underwent therapeutic hypothermia at a single center. The first 24 hours of EEG underwent automated artifact removal and qEEG analysis, comparing qEEG features for seizure risk stratification.

Results: The study included 150 neonates and compared the 36 (23%) with seizures with those without. Absolute spectral power best stratified seizure risk with area under the curve ranging from 63% to 71%, followed by range EEG lower and upper margin, median and SD of the range EEG lower margin. No features were significantly more predictive in the hour before seizure onset. Clinical examination was not associated with seizure risk.

Conclusions: Automatically extracted qEEG features were more predictive than clinical examination in stratifying neonatal seizure risk during therapeutic hypothermia. qEEG represents a potential practical bedside tool to individualize intensity and duration of EEG monitoring and decrease time to seizure recognition. Future work is needed to refine and combine qEEG features to improve risk stratification.

Purpose: To investigate the effects of ketamine on patients with refractory status epilepticus after cardiac arrest.

Methods: In this retrospective cohort, selected EEG segments from patients after cardiac arrest were classified into different EEG patterns (based on background continuity and burden of epileptiform discharges) and spectral profiles (based on the presence of frequency components). For patients who received ketamine, EEG data were compared before, during, and after ketamine infusion; for the no-ketamine group, EEG data were compared at three separated time points during recording. Ketamine usage was determined by clinical providers. Electrographic improvement in epileptiform activity was scored, and the odds ratio was calculated using the Fisher exact test. Functional outcome measures at time of discharge were also examined.

Results: Of a total of 38 patients with postcardiac arrest refractory status epilepticus, 13 received ketamine and 25 did not. All patients were on ≥2 antiseizure medications including at least one sedative infusion (midazolam). For the ketamine group, eight patients had electrographic improvement, compared with only two patients in the no-ketamine group, with an odds ratio of 7.19 (95% confidence interval 1.16-44.65, P value of 0.0341) for ketamine versus no ketamine. Most of the patients who received ketamine had myoclonic status epilepticus, and overall neurologic outcomes were poor with no patients having a favorable outcome.

Conclusions: For postarrest refractory status epilepticus, ketamine use was associated with electrographic improvement, but with the available data, it is unclear whether ketamine use or EEG improvement can be linked to better functional recovery.

Purpose: We evaluated the correlation between quantitative background activities on electroencephalography (EEG) and serum neuron specific enolase (NSE) in patients with hypoxic-ischemic encephalopathy as well as a diagnostic value of prognostication.

Methods: This retrospective cohort study enrolled patients with return of spontaneous circulation after cardiac arrest from March 2010 to March 2020. The inclusion criteria were (1) older than the age of 16 years and (2) patients who had both EEG and NSE. The median time for EEG and NSE were 3 days (interquartile range 2-5 days) and 3 days (interquartile range 2-4 days), respectively. The quantification of background activity was conducted with the suppression ratio (SR). We used a machine learning (eXtreme Gradient Boosting algorithm) to evaluate whether the SR could improve the accuracy of prognostication.

Results: We enrolled 151 patients. The receiver operating characteristic analysis revealed a cut-off value of serum NSE and the SR for poor outcome, serum NSE (>31.9 μg/L, area under curve [AUC] = 0.88), and the SR (>21.5%, AUC = 0.75 in the right hemisphere, >34.4%, AUC = 0.76 in the left hemisphere). There was a significant positive correlation between the severity of SR and the level of NSE ( ρ = 0.57, p < 0.0001 for the right hemisphere, ρ = 0.58, p < 0.0001 for the left hemisphere). The SR showed an excellent diagnostic value for predicting poor outcome (93% specificity, 60% sensitivity in the right hemisphere and 93% specificity, 58% sensitivity in the left hemisphere). With machine learning analysis, there was an increment in distinguishing the neurological outcome by adding SR on clinical factors.

Conclusions: The SR showed a positive correlation with the level of serum NSE. The diagnostic value of the SR for predicting poor outcome was excellent, suggesting that it can be a possible biomarker for neuroprognostication in patients with hypoxic-ischemic encephalopathy.

Purpose: Electroencephalography (EEG) is commonly used in neurology, but there is variability in how neurologists interpret EEGs, potentially from variability in EEG teaching. Little is known about how EEG teaching is done to prepare neurologists for professional practice.

Methods: We interviewed a group of EEG experts to characterize their teaching practices around continuous EEG (cEEG). We used signature pedagogy as a framework to analyze and interpret the data.

Results: We identified pervasive and characteristic forms of cEEG teaching. Teaching is based on apprenticeship, relying on "learning by doing" in the context of real-life clinical practice. There are habitual steps that learners take to anchor teaching, which typically occurs during rounds. There is a common language and core knowledge that trainees need to master early in their training.

Conclusions: There are pervasive characteristic forms of cEEG teaching. These findings can help facilitate instructional design and implementation of complementary or enhanced cEEG teaching practices.

Purpose: Surgical resection of magnetoencephalography (MEG) dipole clusters, reconstructed from interictal epileptiform discharges, is associated with favorable seizure outcomes. However, the relation of MEG cluster resection to the surgical resection volume is not known nor is it clear whether this association is direct and causal, or it may be mediated by the resection volume or other predictive factors. This study aims to clarify these open questions and assess the diagnostic accuracy of MEG in our center.

Methods: We performed a retrospective cohort study of 68 patients with drug-resistant epilepsy who underwent MEG followed by resective epilepsy surgery and had at least 12 months of postsurgical follow-up.

Results: Good seizure outcomes were associated with monofocal localization (χ 2 = 6.94, P = 0.001; diagnostic odds ratio = 10.2) and complete resection of MEG clusters (χ 2 = 22.1, P < 0.001; diagnostic odds ratio = 42.5). Resection volumes in patients with and without removal of MEG clusters were not significantly different ( t = 0.18, P = 0.86; removed: M = 20,118 mm 3 , SD = 10,257; not removed: M = 19,566 mm 3 , SD = 10,703). Logistic regression showed that removal of MEG clusters predicts seizure-free outcome independent of the resection volume and other prognostic factors ( P < 0.001).

Conclusions: Complete resection of MEG clusters leads to favorable seizure outcomes without affecting the volume of surgical resection and independent of other prognostic factors. MEG can localize the epileptogenic zone with high accuracy. MEG interictal epileptiform discharges mapping should be used whenever feasible to improve postsurgical seizure outcomes.

Purpose: Continuous electroencephalography (cEEG) is recommended for hospitalized patients with cerebrovascular diseases and suspected seizures or unexplained neurologic decline. We sought to (1) identify areas of practice variation in cEEG utilization, (2) determine predictors of cEEG utilization, (3) evaluate whether cEEG utilization is associated with outcomes in patients with cerebrovascular diseases.

Methods: This cohort study of the Premier Healthcare Database (2014-2020), included hospitalized patients age > 18 years with cerebrovascular diseases (identified by ICD codes). Continuous electroencephalography was identified by International Classification of Diseases (ICD)/Current Procedural Terminology (CPT) codes. Multivariable lasso logistic regression was used to identify predictors of cEEG utilization and in-hospital mortality. Propensity score-matched analysis was performed to determine the relation between cEEG use and mortality.

Results: 1,179,471 admissions were included; 16,777 (1.4%) underwent cEEG. Total number of cEEGs increased by 364% over 5 years (average 32%/year). On multivariable analysis, top five predictors of cEEG use included seizure diagnosis, hospitals with >500 beds, regions Northeast and South, and anesthetic use. Top predictors of mortality included use of mechanical ventilation, vasopressors, anesthetics, antiseizure medications, and age. Propensity analysis showed that cEEG was associated with lower in-hospital mortality (Average Treatment Effect -0.015 [95% confidence interval -0.028 to -0.003], Odds ratio 0.746 [95% confidence interval, 0.618-0.900]).

Conclusions: There has been a national increase in cEEG utilization for hospitalized patients with cerebrovascular diseases, with practice variation. cEEG utilization was associated with lower in-hospital mortality. Larger comparative studies of cEEG-guided treatments are indicated to inform best practices, guide policy changes for increased access, and create guidelines on triaging and transferring patients to centers with cEEG capability.

Objectives: Our study aimed to compare signal characteristics of subdural electrodes (SDE) and depth stereo EEG placed within a 5-mm vicinity in patients with drug-resistant epilepsy. We report how electrode design and placement collectively affect signal content from a shared source between these electrode types.

Methods: In subjects undergoing invasive intracranial EEG evaluation at a surgical epilepsy center from 2012 to 2018, stereo EEG and SDE electrode contacts placed within a 5-mm vicinity were identified. Of these, 24 contacts (12 pairs) met our criteria for signal-to-noise ratio and data availability for final analysis. We used Welch method to analyze the correlation of power spectral densities of EEG segments, root mean square of 1-second windows, and fast-Fourier transform to calculate coherence across conventional frequency bands.

Results: We observed a median distance of 3.7 mm between the electrode contact pairs. Time-aware analysis highlighted the coherence's strength primarily in the high-gamma band, where the median (r) was 0.889. In addition, the median power ratios between the SDE and stereo EEG signal was 1.99. This ratio decreased from high-gamma to infra-low frequencies, with medians of 2.07 and 0.97, respectively. The power spectral densities for the stereo EEG and SDE electrodes demonstrated a strong correlation, with a median correlation coefficient (r) of 0.99 and an interquartile range from 0.915 to 0.996.

Conclusions: Signals captured by standard subdural and depth (intracranial EEG) electrodes within a 5-mm radius exhibit band-specific coherence and are not identical. The association was most pronounced in the high-gamma band, with coherence decreasing with lower frequencies. Our findings underscore the combined effects of electrode size, design, placement, preferred bandwidth, and the nature of the activity source on signal recording. Particularly, SDE employed herein may offer advantages for high-frequency signals, but the impact of electrode size on recordings necessitates careful consideration in context-specific situations.

Significance: The findings relate to surgical epilepsy care and may inform the design of brain-computer interface.