Systematic review of seizure-onset patterns in stereo-electroencephalography: Current state and future directions.

OBJECTIVE: Increasing evidence suggests that the seizure-onset pattern (SOP) in stereo-electroencephalography (SEEG) is important for localizing the "true" seizure onset. Specifically, SOPs with low-voltage fast activity (LVFA) are associated with seizure-free outcome (Engel I). However, several classifications and various terms corresponding to the same pattern have been reported, challenging its use in clinical practice. METHOD: Following the Preferred Reporting Items of Systematic reviews and Meta-Analyses (PRISMA) guideline, we performed a systematic review of studies describing SOPs along with accompanying figures depicting the reported SOP in SEEG. RESULTS: Of 1799 studies, 22 met the selection criteria. Among the various SOPs, we observed that the terminology for low frequency periodic spikes exhibited the most variability, whereas LVFA is the most frequently used term of this pattern. Some SOP terms were inconsistent with standard EEG terminology. Finally, there was a significant but weak association between presence of LVFA and seizure-free outcome. CONCLUSION: Divergent terms were used to describe the same SOPs and some of these terms showed inconsistencies with the standard EEG terminology. Additionally, our results confirmed the link between patterns with LVFA and seizure-free outcomes. However, this association was not strong. SIGNIFICANCE: These results underline the need for standardization of SEEG terminology.

Focal epilepsy impacts rapid eye movement sleep microstructure.

STUDY OBJECTIVES: Whereas there is plenty of evidence on the influence of epileptic activity on non-rapid eye movement (NREM) sleep macro- and micro-structure, data on the impact of epilepsy on rapid eye movement (REM) sleep remains sparse. Using high-density electroencephalography (HD-EEG), we assessed global and focal disturbances of sawtooth waves (STW) as cortically generated sleep oscillations of REM sleep in patients with focal epilepsy. METHODS: Twenty-two patients with drug-resistant focal epilepsy (13 females; mean age, 32.6 ± 10.7 years; 12 temporal lobe epilepsy) and 12 healthy controls (3 females; 24.0 ± 3.2 years) underwent combined overnight HD-EEG and polysomnography. STW rate, duration, frequency, power, spatial extent, IED rates and sleep homeostatic properties were analyzed. RESULTS: STW rate and duration were reduced in patients with focal epilepsy compared to healthy controls (rate: 0.64/min ± 0.46 vs. 1.12/min ± 0.41, p = .005, d = -0.98; duration: 3.60 s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = -1.01). Not surprisingly given the fronto-central maximum of STW, the reductions were driven by extratemporal lobe epilepsy patients (rate: 0.45/min ± 0.31 vs. 1.12/min ± 0.41, p = .0004, d = -1.35; duration: 3.49 s ± 0.92 vs. 4.57 ± 1.00, p = .017, d = -0.99) and were more pronounced in the first vs. the last sleep cycle (rate first cycle patients vs. controls: 0.60/min ± 0.49 vs. 1.10/min ± 0.55, p = .016, d = -0.90, rate last cycle patients vs. controls: 0.67/min ± 0.51 vs. 0.99/min ± 0.49, p = .11, d = -0.62; duration first cycle patients vs. controls: 3.60s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = -1.01, duration last cycle patients vs. controls: 3.66s ± 0.84 vs. 4.51 ± 1.26, p = .039, d = -0.80). There was no regional decrease of STWs in the region with the epileptic focus vs. the contralateral side (all p > .05). CONCLUSION: Patients with focal epilepsy and in particular extratemporal lobe epilepsy show a global reduction of STW activity in REM sleep. This may suggest that epilepsy impacts cortically generated sleep oscillations even in REM sleep when epileptic activity is low.

Diagnostic utility of specific abnormal EEG patterns in children for determining epilepsy phenotype and presence of structural brain abnormalities.

Objective: Estimate sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of EEG findings: centrotemporal spikes, photoparoxysmal response, asymmetric photic driving, and asymmetric sleep spindles, for epilepsy phenotype and presence of structural brain abnormalities. Methods: In this case-control study we reviewed children referred for EEG over a 4-year period, with at least one of centrotemporal spikes, photoparoxysmal response, asymmetric photic driving, or asymmetric sleep spindles. This cohort was analyzed in combination with a research database of pediatric patients with seizures. Results: Centrotemporal spikes had 100% sensitivity for childhood epilepsy with centrotemporal spikes or atypical childhood epilepsy with centrotemporal spikes, but lower specificity (70%) and PPV (58%). Photoparoxysmal response had high specificity (92%) and NPV (92%) for genetic generalized epilepsy. Asymmetric photic driving had low sensitivity for structural brain abnormalities (17%), with specificity 80%. In contrast, asymmetric sleep spindles had much higher sensitivity and specificity, 44% and 97%, respectively. Conclusions: Although centrotemporal spikes are classically associated with childhood epilepsy with centrotemporal spikes, these discharges are seen in other conditions. Photoparoxysmal response is highly indicative of a genetic generalized epilepsy, though may be seen in other epilepsy phenotypes. Relative attenuation of sleep spindles is a more reliable indicator of structural brain malformation than asymmetric photic driving. Significance: The quantitative diagnostic utility of EEG findings should be considered when incorporating these results into clinical decision-making.

Serious Cardiac Arrhythmias Detected by Subcutaneous Long-term Cardiac Monitors in Patients With Drug-Resistant Epilepsy.

BACKGROUND AND OBJECTIVES: Epilepsy is associated with an increased risk of cardiovascular disease and premature mortality, including sudden unexpected death in epilepsy (SUDEP). Serious cardiac arrythmias might go undetected in routine epilepsy and cardiac investigations. METHODS: This prospective cohort study aimed to detect cardiac arrhythmias in patients with chronic drug-resistant epilepsy (≥5 years duration) using subcutaneous cardiac monitors for a minimum follow-up duration of 12 months. Participants with known cardiovascular disease or those with abnormal 12-lead ECGs were excluded. The device was programmed to automatically record episodes of tachycardia ≥140 beats per minute (bpm), bradycardia ≤40 bpm for ≥3 seconds, or asystole ≥3 seconds. FINDINGS: Thirty-one patients underwent subcutaneous cardiac monitoring for a median recording duration of 2.2 years (range 0.5-4.2). During this time, 28 patients (90.3%) had episodes of sustained (≥30 seconds) sinus tachycardia, 8/31 (25.8%) had sinus bradycardia, and 3 (9.7%) had asystole. Three patients (9.7%) had serious cardiac arrhythmias requiring additional cardiac interventions. Among them, 2 patients had prolonged sinus arrest and ventricular asystole (>6 seconds), leading to pacemaker insertion in one, and another patient with epileptic encephalopathy had multiple episodes of recurrent nonsustained polymorphic ventricular tachycardia and bundle branch conduction abnormalities. The time to first detection of a clinically significant cardiac arrhythmia ranged between 1.2 and 26.9 months following cardiac monitor insertion. DISCUSSION: Implantable cardiac monitors detected a high incidence of clinically significant cardiac arrhythmias in patients with chronic drug-resistant epilepsy, which may contribute to the incidence of premature mortality, including SUDEP.

Age-related evolution of EEG in Dravet syndrome: Meta-analysis of 155 patients.

PURPOSE: Dravet syndrome is an early-onset developmental and epileptic encephalopathy caused by pathogenic SCN1A variants in 80-90% of patients. EEG is initially normal, but abnormalities, both generalized and focal, may develop later. There is a limited understanding of typical EEG evolution in Dravet syndrome. METHODS: We searched Pubmed in July 2020 for studies including: ≥ 1 patient with Dravet syndrome clinical diagnosis and SCN1A pathogenic variant, and for each such patient, a description of ≥ 1 EEG and age at the time of the EEG. For each study, we evaluated for bias in patient selection. We also reviewed our research database for Dravet patients with available EEG reports. We extracted demographic data and EEG abnormalities reported (generalized/focal epileptiform abnormalities, focal/diffuse slowing). We determined the earliest ages at which different abnormalities were seen, as well as the percentage of reported abnormalities for different age ranges. RESULTS: We included 247 EEGs from 155 patients (from 31 studies and our research database). The earliest reported ages of generalized epileptiform discharges, focal epileptiform discharges, diffuse background slowing, and focal slowing, were six months, four months, four months, and four months, respectively. In patients 0-12 months, EEG was abnormal in 43%, but this rose to 90% for the 1-2 year-old group, and remained at approximately the same level for the remainder of the age groups. CONCLUSION: Our results help clarify the relationship between age and EEG in Dravet syndrome; however, findings should be interpreted with caution given the inherent potential biases in the study design.

Can seizure-related heart rate differentiate epileptic from psychogenic nonepileptic seizures?

OBJECTIVES: We aimed to (1) determine if seizure-related heart rate (HR) differentiates epileptic seizures (ES) from psychogenic nonepileptic seizures (PNES); (2) define the most useful point of the following HR measurements: preictal, ictal-onset, maximal-ictal, or postictal; and (3) delineate the optimal HR cutoff points (absolute HR and relative HR increase) to differentiate ES from PNES. METHODS: All video-electroencephalography (VEEG) recorded at an Australian tertiary hospital from May 2009 to November 2015 were retrospectively reviewed. Baseline (during rest and wakefulness), 1-min preictal, ictal-onset, maximal-ictal, and 1-min postictal HR were measured for each ES and PNES event. Events lasting <10 s or with uninterpretable electrocardiogram (ECG) due to artifacts were excluded. Receiver operating characteristic curve analysis was performed to assess the diagnostic accuracy of HR reflected by the area under the curve (AUC). RESULTS: Video-electroencephalography of 341 ES and 265 PNES from 130 patients were analyzed. The AUC for preictal, ictal-onset, maximal-ictal, and postictal HR were found to have poor differentiation between all types of ES and PNES. However, comparing bilateral tonic-clonic ES and PNES, AUC for absolute maximal-ictal HR was 0.84 (95% confidence interval [CI]: 0.73-0.95) and for absolute postictal HR was 0.90 (95% CI: 0.81-1.00) indicating good diagnostic discrimination. Using Youden's index to diagnose tonic-clonic ES, the optimal cutoff point for absolute maximal-ictal HR was 114 bpm (sensitivity: 84%, specificity: 82%) and for absolute postictal HR was 90 bpm (sensitivity: 91%, specificity: 82%). CONCLUSION: These findings suggest that seizure-related HR is useful in differentiating bilateral tonic-clonic ES from PNES. Based on the AUC, the best diagnostic measurements are maximal-ictal and postictal HR.

Seizures by the clock: Temporal patterns of psychogenic nonepileptic seizures.

We hypothesized that (1) the occurrence of psychogenic nonepileptic seizures (PNES) is modulated by the interaction between the 24-hour clock and the sleep-wake cycle and (2) the pattern of modulation in PNES differs from epileptic seizures (ES). We sought to test our hypotheses in a cohort of patients diagnosed with PNES or ES in the setting of an epilepsy monitoring unit (EMU). We retrospectively reviewed consecutive video-EEG (VEEG) recordings of patients who underwent monitoring at the EMU of a tertiary hospital. The seizure type (PNES vs ES), onset time, and the state (sleep vs awake) were tabulated. The relationship between the onset time, the state of arousal, and the occurrence of PNES was determined using logistic regression analysis. To determine if the nature of the relationship between the state of arousal and PNES differed according to the onset time, an interaction between the onset time and the state of arousal was also fitted to the model. We studied a total of 754 seizures (ES, 437; PNES, 317) from 135 patients consisting of 71 (52.6%) females and 64 (47.4%) males with the median age of 39years (range, 18-91). We found a significant association between the state of arousal and PNES with the odds of being PNES four times higher when patients were awake (OR: 4.27, 95% CI: 2.44-7.48; p<0.0001) compared with when they were asleep. The analysis further revealed a significant interaction between the onset time and the state of arousal (p=0.004). The odds of being PNES were significantly higher if the seizure occurred when the patient was awake at night. These patterns possibly indicate the complex interaction between the sleep-wake cycle and the 24-hour time cycle in the generation of PNES.

How reliable is ictal duration to differentiate psychogenic nonepileptic seizures from epileptic seizures?

We sought to investigate (1) differences in ictal duration between psychogenic nonepileptic seizures (PNES) and epileptic seizures (ES), (2) the odds of being PNES when seizures last ≥5min, and (3) the value of ictal duration as a diagnostic test to differentiate PNES from ES. We retrospectively reviewed video-EEG recordings and tabulated ictal durations of all PNES and ES. We estimated the mean ictal durations of PNES and ES using linear mixed models. The odds of being PNES when seizures last ≥5min were estimated using logistic regression. We used receiver operating characteristics (ROC) curves to study the overall diagnostic accuracy of ictal duration in differentiating PNES from ES. We studied 441 ES and 341 PNES recorded from 138 patients. The mean ictal duration of PNES (148.7s, 95% CI: 115.2-191.8) was significantly longer (p<0.001) than that of ES (47.7s, 95% CI: 37.6-60.6). The odds of being PNES was about 24 times higher (Odds ratio: 23.8, 95% CI: 7.9-71.3) when the ictal duration was ≥5min. The ROC curve yielded an area under the curve of 0.80 (95% CI 0.73-0.88). Youden's index identified 123.5s as the optimal threshold to diagnose PNES with 65% sensitivity and 93% specificity. Our results indicate that ictal duration is a useful test to raise suspicion of PNES. When a seizure lasts ≥5min, it is 24 times more likely to be PNES with the potential risk of misdiagnosis as status epilepticus.