Duration of epileptic seizure types: A data-driven approach.

OBJECTIVE: To determine the duration of epileptic seizure types in patients who did not undergo withdrawal of antiseizure medication. METHODS: From a large, structured database of 11 919 consecutive, routine video-electroencephalograpy (EEG) recordings, labeled using the SCORE (Standardized Computer-Based Organized Reporting of EEG) system, we extracted and analyzed 2742 seizures. For each seizure type we determined median duration and range after removal of outliers (2.5-97.5 percentile). We used surface electromyography (EMG) for accurate measurement of short motor seizures. RESULTS: Myoclonic seizures last <150 ms, epileptic spasms 0.4-2 s, tonic seizures 1.5-36 s, atonic seizures 0.1-12,5 s, when measured using surface EMG. Generalized clonic seizures last 1-24 s. Typical absence seizures are rarely longer than 30 s (2.75-26.5 s) and atypical absences last 2-100 s. In our patients, the duration of focal aware (median: 27 s; 1.25-166 s) and impaired awareness seizures (median: 42.5 s; 9.5-271 s) was shorter than reported previously in patients undergoing withdrawal of antiseizure medication. All focal seizures terminated within 10 min. Median duration of generalized tonic-clonic seizures was 79.5 s (57-102 s) and of focal-to-bilateral tonic-clonic seizures was 103.5 (77.5-237 s). All tonic-clonic seizures terminated within 5 min. SIGNIFICANCE: This comprehensive list of seizure durations provides important information for characterizing seizures and diagnosing patients with epilepsy. The upper limits of seizure durations are helpful in early recognition of imminent status epilepticus.

Seizure detection using heart rate variability: A prospective validation study.

Although several validated seizure detection algorithms are available for convulsive seizures, detection of nonconvulsive seizures remains challenging. In this phase 2 study, we have validated a predefined seizure detection algorithm based on heart rate variability (HRV) using patient-specific cutoff values. The validation data set was independent from the previously published data set. Electrocardiography (ECG) was recorded using a wearable device (ePatch) in prospectively recruited patients. The diagnostic gold standard was inferred from video-EEG monitoring. Because HRV-based seizure detection is suitable only for patients with marked ictal autonomic changes, we defined responders as the patients who had a>50 beats/min ictal change in heart rate. Eleven of the 19 included patients with seizures (57.9%) fulfilled this criterion. In this group, the algorithm detected 20 of the 23 seizures (sensitivity: 87.0%). The algorithm detected all but one of the 10 recorded convulsive seizures and all of the 8 focal impaired awareness seizures, and it missed 2 of the 4 focal aware seizures. The median sensitivity per patient was 100% (in nine patients all seizures were detected). The false alarm rate was 0.9/24 h (0.22/night). Our results suggest that HRV-based seizure detection has high performance in patients with marked autonomic changes.

Seizure detection based on heart rate variability using a wearable electrocardiography device.

OBJECTIVE: To assess the feasibility and accuracy of seizure detection based on heart rate variability (HRV) using a wearable electrocardiography (ECG) device. Noninvasive devices for detection of convulsive seizures (generalized tonic-clonic and focal to bilateral tonic-clonic seizures) have been validated in phase 2 and 3 studies. However, detection of nonconvulsive seizures still needs further research, since currently available methods have either low sensitivity or an extremely high false alarm rate (FAR). METHODS: In this phase 2 study, we prospectively recruited patients admitted to long-term video-EEG monitoring (LTM). ECG was recorded using a dedicated wearable device. Seizures were automatically detected using HRV parameters computed off-line, blinded to all other data. We compared the performance of 26 automated algorithms with the seizure time-points marked by experts who reviewed the LTM recording. Patients were classified as responders if >66% of their seizures were detected. RESULTS: We recruited 100 consecutive patients and analyzed 126 seizures (108 nonconvulsive and 18 convulsive) from 43 patients who had seizures during monitoring. The best-performing HRV algorithm combined a measure of sympathetic activity with a measure of how quickly HR changes occurred. The algorithm identified 53.5% of the patients with seizures as responders. Among responders, detection sensitivity was 93.1% (95% CI: 86.6%-99.6%) for all seizures and 90.5% (95% CI: 77.4%-97.3%) for nonconvulsive seizures. FAR was 1.0/24 h (0.11/night). Median seizure detection latency was 30 s. Typically, patients with prominent autonomic nervous system changes were responders: An ictal change of >50 heartbeats per minute predicted who would be responder with a positive predictive value of 87% and a negative predictive value of 90%. SIGNIFICANCE: The automated HRV algorithm, using ECG recorded with a wearable device, has high sensitivity for detecting seizures, including the nonconvulsive ones. FAR was low during the night. This approach is feasible in patients with prominent ictal autonomic changes.

Seizure provocation in EEG recordings: A data-driven approach.

OBJECTIVE: Recording seizures on video-EEG has a high diagnostic value. However, bilateral convulsive seizures constitute a risk for the patients. Our aim was to investigate the diagnostic yield and associated risks of provocation methods in short-term video-EEGs. METHODS: We extracted data on seizures and provocation methods from a large database of short-term video-EEGs with standardized annotations using SCORE (Standardized Computer-based Organized reporting of EEG). RESULTS: 2742 paroxysmal clinical episodes were recorded in 11 919 consecutive EEGs. Most epileptic seizures (54%) were provoked. Hyperventilation provoked most of typical absence seizures (55%), intermittent photic stimulation (IPS) provoked myoclonic seizures (25%) and most of bilateral convulsive seizures (55%), while 43% of focal seizures were precipitated by sleep. All but one of the 16 bilateral convulsive seizures were provoked by IPS or sleep. Latency between start of generalized photoparoxysmal EEG response and bilateral convulsive seizures were ≤3 s in all but one patient. SIGNIFICANCE: The large, structured database provides evidence for the diagnostic utility of various provocation methods in short-term video-EEGs. The risk of bilateral convulsive seizures is relatively small, but it cannot be prevented by stopping IPS after 3 s. A priori knowledge about seizure semiology helps planning patient-tailored provocation strategy in short-term video-EEGs.

EEG normal variants: A prospective study using the SCORE system.

Objective: To determine the prevalence and characteristics of normal variants in EEG recordings in a large cohort, and provide readers with typical examples of all normal variants for educational purposes. Methods: Using the SCORE EEG system (Standardized Computer-Based Organized Reporting of EEG), we prospectively extracted EEG features in consecutive patients. In this dataset, we analyzed 3050 recordings from 2319 patients (mean age 38.5 years; range: 1-89 years). Results: The distribution of the normal variants was as follows: sharp transients 19.21% (including wicket spikes), rhythmic temporal theta of drowsiness 6.03%, temporal slowing of the old 2.89%, slow fused transients 2.59%, 14-and 6-Hz bursts 1.83%, breach rhythm 1.25%, small sharp spikes 1.05%, 6-Hz spike and slow wave 0.69% and SREDA 0.03%. Conclusions: The most prevalent normal variants are the sharp transients, which must not be over-read as epileptiform discharges. Significance: EEG readers must be familiar with the normal variants to avoid misdiagnosis and misclassification of patients referred to clinical EEG recordings.

Magnetic evoked potential polyphasia in idiopathic/genetic generalized epilepsy: An endophenotype not associated with treatment response.

OBJECTIVE: Increased Motor Evoked Potential (MEP) polyphasia was recently described in idiopathic/genetic generalized epilepsy (IGE). Here, we studied the association of MEP polyphasia with treatment response and other clinical characteristics in patients with IGE. METHODS: MEPs were recorded from the biceps brachii, flexor carpi radialis and interosseus dorsalis muscles bilaterally during tonic contraction in IGE patients (n = 72) and historical controls (n = 54) after single pulse transcranial magnetic stimulation. Detailed clinical data was available for all IGE patients; predefined endpoint was the association of MEP polyphasia with treatment response. RESULTS: The mean number of phases was higher in the interosseus dorsalis muscle (2.33 vs. 2.13, p = 0.002) in IGE patients as compared to normal controls, as was the proportion of MEPs with more than two phases in at least one test (59.4% vs. 30%, p < 0.002). MEP polyphasia did not differ between IGE patients and controls in the biceps brachii or the flexor carpi radialis muscles and was not associated with treatment response. Extensive exploratory analyses unveiled fewer phases under valproic acid treatment (p = 0.04) but no additional associations of MEP polyphasia in the interosseous muscle with other clinical characteristics. CONCLUSION: MEP polyphasia is a subclinical symptom of IGE patients but is not associated with treatment response or other routinely assessed clinical characteristics. SIGNIFICANCE: MEP polyphasia is a fixed feature of IGE not modified by clinical variables.

Photoparoxysmal response and its characteristics in a large EEG database using the SCORE system.

OBJECTIVE: To characterize photoparoxysmal EEG response (PPR) using a standardized protocol of intermittent photic stimulation (IPS) and standardized definitions for PPR, classified into six types. METHODS: Using the SCORE system (Standardized Computer-Based Organized Reporting of EEG) we prospectively built a large database of standardized EEG annotations. In this study, we extracted the features related to PPR from the structured dataset consisting of 10,671 EEG recordings with IPS, from 7,188 patients. RESULTS: The standardized IPS protocol elicited PPR in 375 recordings (3.5%), in 288 patients (4%), with a preponderance among young (11-20 years) and female patients (67%). PPR was persistent in patients with multiple recordings. The most frequent type of PPR was activation of preexisting epileptogenic area (58%), followed by generalized-PPR limited to the stimulus train (22%). We could not find any recording with self-sustained posterior response. Seizures were elicited in 27% of patients with PPR, most often myoclonic seizures and absences, in patients with self-sustained generalized PPR. CONCLUSIONS: The most common type of PPR was accentuation of preexisting epileptogenic area. Self-sustained posterior response could not be documented. Self-sustained generalized-PPR had the highest association with seizures. SIGNIFICANCE: Using standardized stimulation protocol and definitions for PPR types, IPS provides high diagnostic yield.

Modulation in time of the interictal spiking pattern related to epileptic seizures.

OBJECTIVE: To test the hypothesis that significant changes in the occurrence of interictal epileptiform electroencephalography (EEG) discharges (EDs) are associated with seizures: while some EDs are pro-convulsive, increasing at seizure-occurrence, others are protective, showing decrease related to seizures. METHODS: We analyzed 102 consecutive, long-term video-EEG monitoring sessions, from 98 patients. Using a semi-automated spike-detection method, we quantified the occurrence of EDs, grouped according to their location and morphology (clusters) and we constructed graphical representation of data, showing changes in time of the spiking patterns (spike-histograms). We compared the spike-histograms with the time-points of the seizures (pre-, peri- and postictal changes). RESULTS: Totally 179 ED-clusters were identified. Modulation of the spiking pattern, associated with seizures, was observed in 66 clusters (37%), from 47 patients (48%). Most of these changes (40 clusters; 61%) were related to increase in the spiking-pattern. CONCLUSIONS: Changes in spiking-pattern were associated with more than one third of the EDs. Both increasing and decreasing patterns were observed. SIGNIFICANCE: EDs are more often pro-convulsive, with increasing spiking patterns associated with seizures. However, in more than one third of the ED clusters modulated by seizures, the spiking pattern decreased, raising the possibility of an anticonvulsive function of these discharges.