Generalized tonic-clonic seizures are accompanied by changes of interrelations within the autonomic nervous system.

PURPOSE: A seizure is a strong central stimulus that affects multiple subsystems of the autonomic nervous system (ANS), and results in different interactions across ANS modalities. Here, we aimed to evaluate whether multimodal peripheral ANS measures demonstrate interactions before and after seizures as compared to controls to provide the basis for seizure detection and forecasting based on peripheral ANS signals. METHODS: Continuous electrodermal activity (EDA), heart rate (HR), peripheral body temperature (TEMP), and respiratory rate (RR) calculated based on blood volume pulse were acquired by a wireless multi-sensor device. We selected 45 min of preictal and 60 min of postictal data and time-matched segments for controls. Data were analyzed over 15-min windows. For unimodal analysis, mean values over each time window were calculated for all modalities and analyzed by Friedman's two-way analysis of variance. RESULTS: Twenty-one children with recorded generalized tonic-clonic seizures (GTCS), and 21 age- and gender-matched controls were included. Unimodal results revealed no significant effect for RR and TEMP, but EDA (p = 0.002) and HR (p < 0.001) were elevated 0-15 min after seizures. The averaged bimodal correlation across all pairs of modalities changed for 15-min windows in patients with seizures. The highest correlations were observed immediately before (0.85) and the lowest correlation immediately after seizures. Overall, average correlations for controls were higher. SIGNIFICANCE: Multimodal ANS changes related to GTCS occur within and across autonomic nervous system modalities. While unimodal changes were most prominent during postictal segments, bimodal correlations increased before seizures and decreased postictally. This offers a promising avenue for further research on seizure detection, and potentially risk assessment for seizure recurrence and sudden unexplained death in epilepsy.

Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit.

Background: Using machine learning to combine wrist accelerometer (ACM) and electrodermal activity (EDA) has been shown effective to detect primarily and secondarily generalized tonic-clonic seizures, here termed as convulsive seizures (CS). A prospective study was conducted for the FDA clearance of an ACM and EDA-based CS-detection device based on a predefined machine learning algorithm. Here we present its performance on pediatric and adult patients in epilepsy monitoring units (EMUs). Methods: Patients diagnosed with epilepsy participated in a prospective multi-center clinical study. Three board-certified neurologists independently labeled CS from video-EEG. The Detection Algorithm was evaluated in terms of Sensitivity and false alarm rate per 24 h-worn (FAR) on all the data and on only periods of rest. Performance were analyzed also applying the Detection Algorithm offline, with a less sensitive but more specific parameters configuration ("Active mode"). Results: Data from 152 patients (429 days) were used for performance evaluation (85 pediatric aged 6-20 years, and 67 adult aged 21-63 years). Thirty-six patients (18 pediatric) experienced a total of 66 CS (35 pediatric). The Sensitivity (corrected for clustered data) was 0.92, with a 95% confidence interval (CI) of [0.85-1.00] for the pediatric population, not significantly different (p > 0.05) from the adult population's Sensitivity (0.94, CI: [0.89-1.00]). The FAR on the pediatric population was 1.26 (CI: [0.87-1.73]), higher (p < 0.001) than in the adult population (0.57, CI: [0.36-0.81]). Using the Active mode, the FAR decreased by 68% while reducing Sensitivity to 0.95 across the population. During rest periods, the FAR's were 0 for all patients, lower than during activity periods (p < 0.001). Conclusions: Performance complies with FDA's requirements of a lower bound of CI for Sensitivity higher than 0.7 and of a FAR lower than 2, for both age groups. The pediatric FAR was higher than the adult FAR, likely due to higher pediatric activity. The high Sensitivity and precision (having no false alarms) during sleep might help mitigate SUDEP risk by summoning caregiver intervention. The Active mode may be advantageous for some patients, reducing the impact of the FAR on daily life. Future work will examine the performance and usability outside of EMUs.

Association between semiologic, autonomic, and electrographic seizure characteristics in children with generalized tonic-clonic seizures.

INTRODUCTION: Generalized tonic-clonic seizures (GTCS) are associated with elevated electrodermal activity (EDA) and postictal generalized electroencephalographic suppression (PGES), markers that may indicate sudden unexpected death in epilepsy (SUDEP) risk. This study investigated the association of GTCS semiology, EDA, and PGES in children with epilepsy. METHODS: Patients admitted to the Boston Children's Hospital long-term video-EEG monitoring unit wore a sensor that records EDA. We selected patients with at least one GTCS and reviewed video-EEGs for semiology, tonic and clonic phase duration, total clinical seizure duration, electrographic onset, offset, and PGES. We grouped patients into three semiology classes: GTCS 1: bilateral symmetric tonic arm extension, GTCS 2: no specific tonic arm extension or flexion, GTCS 3: unilateral or asymmetrical arm extension, tonic arm flexion or posturing that does not fit into GTCS 1 or 2. We analyzed the correlation between semiology, EDA, and PGES, and measured the area under the curve (AUC) of the ictal EDA (seizure onset to one hour after), subtracting baseline EDA (one-hour seizure-free before seizure onset). Using generalized estimating equation (GEE) and linear regression, we analyzed all seizures and single episodes per patient. RESULTS: We included 30 patients (median age 13.8 ±â€¯3.6 years, 46.7% females) and 53 seizures. With GEE, GTCS 1 was associated with longer PGES duration compared to GTCS 2 (Estimate (ß) = -26.32 s, 95% Confidence Interval (CI): -36.46 to -16.18, p < 0.001), and the presence of PGES was associated with greater EDA change (ß = 429604 µS, 95% CI: 3550.96 to 855657.04, p = 0.048). With single-episode analysis, GTCS 1 had greater EDA change than GTCS 2 ((ß = -601339 µS, 95% CI: -1167016.56 to -35661.44, p = 0.047). EDA increased with PGES presence (ß = 637500 µS, 95% CI: 183571.84 to 1091428.16, p = 0.01) and duration (ß = 16794 µS, 95% CI: 5729.8 to 27858.2, p = 0.006). Patients with GTCS 1 had longer PGES duration compared to GTCS 2 (ß = -30.53 s, 95% CI: -44.6 to -16.46, p < 0.001) and GTCS 3 (ß = -22.07 s, 95% CI: -38.95 to -5.19, p = 0.016). CONCLUSION: In children with epilepsy, PGES correlates with greater ictal EDA. GTCS 1 correlated with longer PGES duration and may indirectly correlate with greater ictal EDA. Our study suggests potential applications in monitoring and preventing SUDEP in these patients.

Photoplethysmography: A measure for the function of the autonomic nervous system in focal impaired awareness seizures.

OBJECTIVES: Photoplethysmography (PPG) reflects variations of blood perfusion in tissues, which may signify seizure-related autonomic changes. The aim of this study is to assess the variability of PPG signals and their value in detecting peri-ictal changes in patients with focal impaired awareness seizures (FIASs). METHODS: PPG data were recorded using a wearable sensor placed on the wrist or ankle of children with epilepsy admitted for long-term video-electroencephalographic monitoring. We analyzed PPG data in four different periods: seizure-free, preictal, ictal, and postictal. Multiple features were automatically extracted from the PPG signal-frequency, duration, amplitude, increasing and decreasing slopes, smoothness, and area under the curve (AUC)-and were used to identify preictal, ictal, or postictal changes by comparing them with seizure-free periods and with each other using a linear mixed-effects model. RESULTS: We studied PPG in 11 patients (18 FIASs), including seizure-free, preictal, and postictal periods, and a subset of eight patients (12 FIASs) including the ictal period. Compared to the seizure-free period, we found significant changes in PPG (1) during the ictal period across all features; (2) during the preictal period in amplitude, duration, increasing slope, and AUC; and (3) during the postictal period in decreasing slope. SIGNIFICANCE: Specific PPG changes can be seen before, during, and after FIASs. The peri-ictal changes in the PPG features of patients with FIASs suggest potential applications of PPG monitoring for seizure detection.

Photoplethysmographic evaluation of generalized tonic-clonic seizures.

OBJECTIVE: Photoplethysmography (PPG) is an optical technique measuring variations of blood perfusion in peripheral tissues. We evaluated alterations in PPG signals in relationship to the occurrence of generalized tonic-clonic seizures (GTCSs) in patients with epilepsy to evaluate the feasibility of seizure detection. METHODS: During electroencephalographic (EEG) long-term monitoring, patients wore portable wristband sensor(s) on their wrists or ankles recording PPG signals. We analyzed PPG signals during three time periods, which were defined with respect to seizures detected on EEG: (1) baseline (>30 minutes prior to seizure), (2) preseizure period, and (3) postseizure period. Furthermore, we selected five random control segments during seizure-free periods. PPG features, including frequency, amplitude, duration, slope, smoothness, and area under the curve, were automatically calculated. We used a linear mixed-effect model to evaluate changes in PPG features between different time periods in an attempt to identify signal changes that detect seizures. RESULTS: We prospectively enrolled 174 patients from the epilepsy monitoring unit at Boston Children's Hospital. Twenty-five GTCSs were recorded from 13 patients. Data from the first recorded GTCS of each patient were included in the analysis. We observed an increase in PPG frequency during pre- and postseizure periods that was higher than the changes during seizure-free periods (frequency increase: preseizure = 0.22 Hz, postseizure = 0.58 Hz vs changes during seizure-free period = 0.05 Hz). The PPG slope decreased significantly by 56.71 nW/s during preseizure periods compared to seizure-free periods. Additionally, the smoothness increased significantly by 0.22 nW/s during the postseizure period compared to seizure-free periods. SIGNIFICANCE: Monitoring of PPG signals may assist in the detection of GTCSs in patients with epilepsy. PPG may serve as a promising biomarker for future seizure detection systems and may contribute to future seizure prediction systems.

Multicenter clinical assessment of improved wearable multimodal convulsive seizure detectors.

OBJECTIVE: New devices are needed for monitoring seizures, especially those associated with sudden unexpected death in epilepsy (SUDEP). They must be unobtrusive and automated, and provide false alarm rates (FARs) bearable in everyday life. This study quantifies the performance of new multimodal wrist-worn convulsive seizure detectors. METHODS: Hand-annotated video-electroencephalographic seizure events were collected from 69 patients at six clinical sites. Three different wristbands were used to record electrodermal activity (EDA) and accelerometer (ACM) signals, obtaining 5,928 h of data, including 55 convulsive epileptic seizures (six focal tonic-clonic seizures and 49 focal to bilateral tonic-clonic seizures) from 22 patients. Recordings were analyzed offline to train and test two new machine learning classifiers and a published classifier based on EDA and ACM. Moreover, wristband data were analyzed to estimate seizure-motion duration and autonomic responses. RESULTS: The two novel classifiers consistently outperformed the previous detector. The most efficient (Classifier III) yielded sensitivity of 94.55%, and an FAR of 0.2 events/day. No nocturnal seizures were missed. Most patients had <1 false alarm every 4 days, with an FAR below their seizure frequency. When increasing the sensitivity to 100% (no missed seizures), the FAR is up to 13 times lower than with the previous detector. Furthermore, all detections occurred before the seizure ended, providing reasonable latency (median = 29.3 s, range = 14.8-151 s). Automatically estimated seizure durations were correlated with true durations, enabling reliable annotations. Finally, EDA measurements confirmed the presence of postictal autonomic dysfunction, exhibiting a significant rise in 73% of the convulsive seizures. SIGNIFICANCE: The proposed multimodal wrist-worn convulsive seizure detectors provide seizure counts that are more accurate than previous automated detectors and typical patient self-reports, while maintaining a tolerable FAR for ambulatory monitoring. Furthermore, the multimodal system provides an objective description of motor behavior and autonomic dysfunction, aimed at enriching seizure characterization, with potential utility for SUDEP warning.

HHV-6 and seizure: A systematic review and meta-analysis.

Human herpesvirus-6 (HHV-6) is a common infection in childhood. This systematic review aims to assess the relationship between HHV-6 infection and seizure disorders based on available literature. MEDLINE database was searched using a search strategy. We included studies that were published after 1993 in English, and described patients with HHV-6 infection and accompanying seizure or status epilepticus. We identified 503 articles, and included 147 studies. Meta-analysis results showed a 0.21 detection rate of HHV-6 in febrile seizure patients. In the febrile seizure group (110 cases), 76 patients had simple and 34 had complex febrile seizures. Patients with "HHV-6 infection and status epilepticus" had a mean age of 16.24 months. In children with febrile illnesses, a higher index of clinical suspicion for HHV-6 infection may be required. Further studies including CSF and brain tissue may be needed to validate relationships between HHV6 infection and epilepsy. J. Med. Virol. 89:161-169, 2017. © 2016 Wiley Periodicals, Inc.

Quality of reporting randomized controlled trials (RCTs) in diabetes in Iran; a systematic review.

OBJECTIVE: To determine the quality of randomized controlled clinical trial (RCT) reports in diabetes research in Iran. DESIGN: Systematized review. METHODS: We included RCTs conducted on diabetes mellitus in Iran. Animal studies, educational interventions, and non-randomized trials were excluded. We excluded duplicated publications reporting the same groups of participants and intervention. Two independent reviewers identify all eligible articles specifically designed data extraction form. We searched through international databases; Scopus, ProQuest, EBSCO, Science Direct, Web of Science, Cochrane Library, PubMed; and national databases (In Persian language) such as Magiran, Scientific Information Database (SID) and IranMedex from January 1995 to January of 2013 Two investigators assessed the quality of reporting by CONSORT 2010 (Consolidated Standards of Reporting Trials) checklist statemen.t,. Discrepancies were resolved by third reviewer consulting. RESULTS: One hundred and eight five (185) studies were included and appraised. Half of them (55.7 %) were published in Iranian journals. Most (89.7 %) were parallel RCTs, and being performed on type2 diabetic patients (77.8 %). Less than half of the CONSORT items (43.2 %) were reported in studies, totally. The reporting of randomization and blinding were poor. A few studies 15.1 % mentioned the method of random sequence generation and strategy of allocation concealment. And only 34.8 % of trials report how blinding was applied. CONCLUSIONS: The findings of this study show that the quality of RCTs conducted in Iran in diabetes research seems suboptimal and the reporting is also incomplete however an increasing trend of improvement can be seen over time. Therefore, it is suggested Iranian researchers pay much more attention to design and methodological quality in conducting and reporting of diabetes RCTs.