The yield of long-term electrocardiographic recordings in refractory focal epilepsy.

OBJECTIVE: To determine the incidence of clinically relevant arrhythmias in refractory focal epilepsy and to assess the potential of postictal arrhythmias as risk markers for sudden unexpected death in epilepsy (SUDEP). METHODS: We recruited people with refractory focal epilepsy without signs of ictal asystole and who had at least one focal seizure per month and implanted a loop recorder with 2-year follow-up. The devices automatically record arrhythmias. Subjects and caregivers were instructed to make additional peri-ictal recordings. Clinically relevant arrhythmias were defined as asystole ≥ 6 seconds; atrial fibrillation < 55 beats per minute (bpm), or > 200 bpm and duration > 30 seconds; persistent sinus bradycardia < 40 bpm while awake; and second- or third-degree atrioventricular block and ventricular tachycardia/fibrillation. We performed 12-lead electrocardiography (ECG) and tilt table testing to identify non-seizure-related causes of asystole. RESULTS: We included 49 people and accumulated 1060 months of monitoring. A total of 16 474 seizures were reported, of which 4679 were captured on ECG. No clinically relevant arrhythmias were identified. Three people had a total of 18 short-lasting (<6 seconds) periods of asystole, resulting in an incidence of 2.91 events per 1000 patient-months. None of these coincided with a reported seizure; one was explained by micturition syncope. Other non-clinically relevant arrhythmias included paroxysmal atrial fibrillation (n = 2), supraventricular tachycardia (n = 1), and sinus tachycardia with a right bundle branch block configuration (n = 1). SIGNIFICANCE: We found no clinically relevant arrhythmias in people with refractory focal epilepsy during long-term follow-up. The absence of postictal arrhythmias does not support the use of loop recorders in people at high SUDEP risk.

The difficulty of diagnosing NCSE in clinical practice; external validation of the Salzburg criteria.

To improve the diagnostic accuracy of electroencephalography (EEG) criteria for nonconvulsive status epilepticus (NCSE), external validation of the recently proposed Salzburg criteria is paramount. We performed an external, retrospective, diagnostic accuracy study of the Salzburg criteria, using EEG recordings from patients with and without a clinical suspicion of having NCSE. Of the 191 EEG recordings, 12 (12%) was classified as an NCSE according to the reference standard. In the validation cohort, sensitivity was 67% and specificity was 89%. The positive predictive value was 47% and the negative predictive value was 95%. Ten patients in the control group (n = 93) were false positive, resulting in a specificity of 89.2%. The interrater agreement between the reference standards and between the scorers of the Salzburg criteria was moderate; disagreement occurred mainly in patients with an epileptic encephalopathy. The Salzburg criteria showed a lower diagnostic accuracy in our external validation study than in the original design, suggesting that they cannot replace the current practice of careful weighing of both clinical and EEG information on an individual basis.

Epileptic seizures associated with syncope: Ictal bradycardia and ictal asystole.

INTRODUCTION: Heart rate decrease during epileptic seizures is rare and should be considered in patients with unusual or refractory episodes of syncope or in patients with a history suggestive of both epilepsy and syncope. We systematically reviewed the literature to better understand the clinical signs and risk factors of ictal heart rate decreases. MATERIAL AND METHODS: We performed a literature-search on "ictal bradycardia" and "ictal asystole" in Pubmed and added papers from the references and personal archives. Articles relating to animal studies, seizures without ictal decrease of heart rate, cases without simultaneous electroencephalography (EEG) and electrocardiography (ECG), convulsive syncopes, or cases with bradycardia before seizure onset and articles written in other languages than English, Dutch, German, French, or Spanish were excluded. Full texts of the remaining articles were screened for cases of ictal bradycardia or ictal asystole. Cases were selected on the basis of a self-designed quality score. The relationship of RR wave interval of at least 5 s, signs of syncope, and EEG signs of ischemia were analyzed with chi-square test and identifying 95% confidence intervals. RESULTS: Ictal bradycardia and ictal asystole predominantly occurred during focal seizures with loss of awareness (proportion in the combined group of bradycardia and asystole (p1 + 2) = 0.85) in people with mainly left lateralized (p1 + 2 = 0.64; p = 0.001) temporal lobe seizures (p1 + 2 = 0.91). Seizures with ictal asystole typically started with a heart rate decrease. During ictal asystole in the majority of cases, not only the clinical signs of syncope occurred (change of proportion (Δp) = 0.67; 95% CI: 0.48-0.86; p < 0.0001), i.e., interrupting the seizure semiology, but also the characteristic EEG signs of ischemia (Δp = 0.50; 95% CI: 0.26-0.74; p < 0.001). We found a statistically significant relation between signs of syncope and EEG signs of ischemia (Δp = -0.37; 95% CI: (-0.64)-(-0.10); p < 0.01) but not between duration of asystole (5 s) and either signs of syncope (Δp = -0.36; 95% CI: (-0.77)-0.05; p = 0.03) or EEG signs of ischemia (Δp = -0.37; 95% CI: (-1.07)-0.33; p = 0.16). CONCLUSION: In the ictal bradycardia syndrome, signs of syncope disrupt the semiology of ongoing seizures and are associated with EEG signs of brain ischemia and the duration of the cardiac arrhythmia.

Design and methods of the 'monitoring outcomes of psychiatric pharmacotherapy' (MOPHAR) monitoring program - a study protocol.

BACKGROUND: At many outpatient departments for psychiatry worldwide, standardized monitoring of the safety of prescribed psychotropic drugs is not routinely performed in daily clinical practice. Therefore it is unclear to which extent the drugs used by psychiatric outpatients are prescribed effectively and safely. These issues warrant structured monitoring of medication use, (pre-existing) co-morbidities, effectiveness and side effects during psychiatric outpatient treatment. Improvement of monitoring practices provides an opportunity to ensure that somatic complications and adverse drug effects are detected and dealt with in a timely manner. Structural support for data collection and follow-up tests seems essential for improvement of monitoring practices in psychiatric outpatients. The implementation of a structured somatic monitoring program as part of routine clinical practice, as we describe in this study protocol, may be a solution. METHODS: In order to address these issues, we developed the innovative program 'Monitoring Outcomes of Psychiatric Pharmacotherapy (MOPHAR)'. MOPHAR is an infrastructure for implementation of standardized routine outcome monitoring (ROM; including standardized monitoring of treatment effect), monitoring of adverse psychotropic medication effects in psychiatric outpatients, encompassing both somatic adverse effects (e.g. metabolic disturbances) and subjective adverse effects (e.g. sedation or sexual side effects) and medication reconciliation. DISCUSSION: In the MOPHAR monitoring program, a nurse performs general and psychotropic drug-specific somatic screenings and provides the treating mental health care providers with more and better information on somatic monitoring for treatment decisions. Given our experience regarding implementation of the MOPHAR program, we expect that the MOPHAR program is feasible and beneficial for patients in any MHS organisation. This paper describes the objectives, target population, setting and the composition and roles of the treatment team. It also indicates what measurements are performed at which time points during outpatient treatment in the MOPHAR monitoring program, as well as the research aspects of this project. TRIAL REGISTRATION: MOPHAR research has been prospectively registered with the Netherlands Trial Register on 19th of November 2014. ( NL4779 ).

Movement-based seizure detection.

This is a critical review and comment on the use of movement detection in epileptic seizures. The detection of rhythmic movement components, such as the clonic part of tonic-clonic seizures, is essential in all seizure detection based on movement sensors. Of the many available movement sensor types, accelerometric sensors are used most often. Eleven video-electroencephalographic (EEG) and 1 field study have been carried out. The results of these clinical trials depend on the population, study design, and seizure evolution. In video-EEG monitoring units, sensitivity for tonic-clonic seizures varied from 31% to 95%, and positive predictive value from 4% to 60%. In a field trial in a residential adult population with intellectual disability, sensitivity was 14% and positive predictive value was 82%, whereas in patients admitted to an epilepsy clinic, a bed sensor had a sensitivity of 84% (no positive predictive value was given). The algorithms using the "rhythmic movement" component at the end of a tonic-clonic seizure are reliable (few false-positive alarms) but miss less typical seizure patterns that are mostly present in people with associated brain development disturbances. Other modalities (heart rate and electromyography) are needed to increase the detection performance. Advanced accelerometric techniques allow us to gain greater insight into seizure evolution patterns, possibilities for neuromodulation, and the influence of antiepileptic drugs on specific seizure components.

Automated video-based detection of nocturnal convulsive seizures in a residential care setting.

People with epilepsy need assistance and are at risk of sudden death when having convulsive seizures (CS). Automated real-time seizure detection systems can help alert caregivers, but wearable sensors are not always tolerated. We determined algorithm settings and investigated detection performance of a video algorithm to detect CS in a residential care setting. The algorithm calculates power in the 2-6 Hz range relative to 0.5-12.5 Hz range in group velocity signals derived from video-sequence optical flow. A detection threshold was found using a training set consisting of video-electroencephalogaphy (EEG) recordings of 72 CS. A test set consisting of 24 full nights of 12 new subjects in residential care and additional recordings of 50 CS selected randomly was used to estimate performance. All data were analyzed retrospectively. The start and end of CS (generalized clonic and tonic-clonic seizures) and other seizures considered desirable to detect (long generalized tonic, hyperkinetic, and other major seizures) were annotated. The detection threshold was set to the value that obtained 97% sensitivity in the training set. Sensitivity, latency, and false detection rate (FDR) per night were calculated in the test set. A seizure was detected when the algorithm output exceeded the threshold continuously for 2 seconds. With the detection threshold determined in the training set, all CS were detected in the test set (100% sensitivity). Latency was ≤10 seconds in 78% of detections. Three/five hyperkinetic and 6/9 other major seizures were detected. Median FDR was 0.78 per night and no false detections occurred in 9/24 nights. Our algorithm could improve safety unobtrusively by automated real-time detection of CS in video registrations, with an acceptable latency and FDR. The algorithm can also detect some other motor seizures requiring assistance.

BEATVIC, a body-oriented resilience therapy using kickboxing exercises for people with a psychotic disorder: a feasibility study.

BACKGROUND: People with a psychotic disorder have an increased risk of becoming the victim of a crime. To prevent victimization a body-oriented resilience therapy using kickboxing exercises was developed. This study aims to explore the feasibility of the therapy, to improve the therapy protocol and to explore suitable outcomes for a RCT. METHODS: Twenty-four adults with a psychotic disorder received 20 weekly group sessions in which potential risk factors for victimization and strategies for dealing with them were addressed. Sessions were evaluated weekly. During pre and post assessment participants completed questionnaires on, among other, victimization, aggression regulation and social functioning. RESULTS: The short recruitment period indicates the interest in such an intervention and the willingness of clients to participate. Mean attendance was 85.3 and 88% of the participants completed fifteen or more sessions. The therapy protocol was assessed as adequate and exercises as relevant with some small improvements to be made. The victimization and aggression regulation questionnaires were found to be suitable outcome measurements for a subsequent RCT. CONCLUSION: The results support the feasibility of the BEATVIC therapy. Participants subjectively evaluated the intervention as helpful in their attempt to gain more self-esteem and assertiveness. With some minor changes in the protocol the effects of BEATVIC can be tested in a RCT. TRIAL REGISTRATION: The trial registration number (TRN) is 35949 (date submitted 09/11/2018). Retrospectively registered.

Non-EEG based ambulatory seizure detection designed for home use: What is available and how will it influence epilepsy care?

OBJECTIVE: This study aimed to (1) evaluate available systems and algorithms for ambulatory automatic seizure detection and (2) discuss benefits and disadvantages of seizure detection in epilepsy care. METHODS: PubMed and EMBASE were searched up to November 2014, using variations and synonyms of search terms "seizure prediction" OR "seizure detection" OR "seizures" AND "alarm". RESULTS: Seventeen studies evaluated performance of devices and algorithms to detect seizures in a clinical setting. Algorithms detecting generalized tonic-clonic seizures (GTCSs) had varying sensitivities (11% to 100%) and false alarm rates (0.2-4/24 h). For other seizure types, detection rates were low, or devices produced many false alarms. Five studies externally validated the performance of four different devices for the detection of GTCSs. Two devices were promising in both children and adults: a mattress-based nocturnal seizure detector (sensitivity: 84.6% and 100%; false alarm rate: not reported) and a wrist-based detector (sensitivity: 89.7%; false alarm rate: 0.2/24 h). SIGNIFICANCE: Detection of seizure types other than GTCSs is currently unreliable. Two detection devices for GTCSs provided promising results when externally validated in a clinical setting. However, these devices need to be evaluated in the home setting in order to establish their true value. Automatic seizure detection may help prevent sudden unexpected death in epilepsy or status epilepticus, provided the alarm is followed by an effective intervention. Accurate seizure detection may improve the quality of life (QoL) of subjects and caregivers by decreasing burden of seizure monitoring and may facilitate diagnostic monitoring in the home setting. Possible risks are occurrence of alarm fatigue and invasion of privacy. Moreover, an unexpectedly high seizure frequency might be detected for which there are no treatment options. We propose that future studies monitor benefits and disadvantages of seizure detection systems with particular emphasis on QoL, comfort, and privacy of subjects and impact of false alarms.

Diagnostic accuracy of audio-based seizure detection in patients with severe epilepsy and an intellectual disability.

UNLABELLED: We evaluated the performance of audio-based detection of major seizures (tonic-clonic and long generalized tonic) in adult patients with intellectual disability living in an institute for residential care. METHODS: First, we checked in a random sample (n=17, 102 major seizures) how many patients have recognizable sounds during these seizures. In the second part of this trial, we followed 10 patients (who had major seizures with recognizable sounds) during four weeks with an acoustic monitoring system developed by CLB ('CLB-monitor') and video camera. In week 1, we adapted the sound detection threshold until, per night, a maximum of 20 sounds was found. During weeks 2-4, we selected the epilepsy-related sounds and performed independent video verification and labeling ('snoring', 'laryngeal contraction') of the seizures. The video images were also fully screened for false negatives. In the third part, algorithms in the CLB-monitor detected one specific sound (sleep-related snoring) to illustrate the value of automatic sound recognition. RESULTS: Part 1: recognizable sounds (louder than whispering) occurred in 23 (51%) of the 45 major seizures, 20 seizures (45%) were below this threshold, and 2 (4%) were without any sound. Part 2: in the follow-up group (n=10, 112 major seizures; mean: 11.2, range: 1-30), we found a mean sensitivity of 0.81 (range: 0.33-1.00) and a mean positive predictive value of 0.40 (range: 0.06-1.00). All false positive alarms (mean value: 1.29 per night) were due to minor seizures. We missed 4 seizures (3%) because of lack of sound and 10 (9%) because of sounds below the system threshold. Part 3: the machine-learning algorithms in the CLB-monitor resulted in an overall accuracy for 'snoring' of 98.3%. CONCLUSIONS: Audio detection of major seizures is possible in half of the patients. Lower sound detection thresholds may increase the proportion of suitable candidates. Human selection of seizure-related sounds has a high sensitivity and moderate positive predictive value because of minor seizures which do not need intervention. Algorithms in the CLB-monitor detect seizure-related sounds and may be used alone or in multimodal systems.

BEATVIC, a body-oriented resilience training with elements of kickboxing for individuals with a psychotic disorder: study protocol of a multi-center RCT.

BACKGROUND: Individuals with a psychotic disorder are at an increased risk of becoming victim of a crime or other forms of aggression. Research has revealed several possible risk factors (e.g. impaired social cognition, aggression regulation problems, assertiveness, self-stigma, self-esteem) for victimization in patients with a psychotic disorder. To address these risk factors and prevent victimization, we developed a body-oriented resilience training with elements of kickboxing: BEATVIC. The present study aims to evaluate the effectiveness of the intervention. METHODS/DESIGN: Seven mental health institutions in the Netherlands will participate in this study. Participants will be randomly assigned to either the BEATVIC training or the control condition: social activation. Follow-ups are at 6, 18 and 30 months. Short term effects on risk factors for victimization will be examined, since these are direct targets of the intervention and are thought to be mediators of victimization, the primary outcome of the intervention. The effect on victimization will be investigated at follow-up. In a subgroup of patients, fMRI scans will be made before and after the intervention period in order to assess potential neural changes associated with the effects of the training. DISCUSSION: This study is the first to examine the effectiveness of an intervention targeted at victimization in psychosis. Methodological issues of the study are addressed in the discussion of this paper. TRIAL REGISTRATION: Current Controlled Trials: ISRCTN21423535 . Retrospectively registered 30-03-2016.

Practical Implications of Metacognitively Oriented Psychotherapy in Psychosis: Findings From a Pilot Study.

In preparation for a multicenter randomized controlled trial, a pilot study was conducted investigating the feasibility and acceptance of a shortened version (12 vs. 40 sessions) of an individual metacognitive psychotherapy (Metacognitive Reflection and Insight Therapy [MERIT]). Twelve participants with a diagnosis of schizophrenia were offered 12 sessions of MERIT. Effect sizes were calculated for changes from baseline to treatment end for metacognitive capacity measured by the Metacognition Assessment Scale-Abbreviated. Nine of twelve patients finished treatment. However, nonsignificant moderate to large effect sizes were obtained on the primary outcome measure. This study is among the first to suggest that patients with schizophrenia will accept metacognitive therapy and evidence improvements in metacognitive capacity. Despite limitations typical to a pilot study, including a small sample size and lack of a control group, sufficient evidence of efficacy was obtained to warrant further investigation.

Accelerometer-based quantitative analysis of axial nocturnal movements differentiates patients with Parkinson's disease, but not high-risk individuals, from controls.

INTRODUCTION: There is a need for prodromal markers to diagnose Parkinson's disease (PD) as early as possible. Knowing that most patients with overt PD have abnormal nocturnal movement patterns, we hypothesised that such changes might occur already in non-PD individuals with a potentially high risk for future development of the disease. METHODS: Eleven patients with early PD (Hoehn & Yahr stage ≤2.5), 13 healthy controls and 33 subjects with a high risk of developing PD (HR-PD) were investigated. HR-PD was defined by the occurrence of hyperechogenicity of the substantia nigra in combination with prodromal markers (eg, slight motor signs, olfactory dysfunction). A triaxial accelerometer was used to quantify nocturnal movements during two nights per study participant. Outcome measurements included mean acceleration, and qualitative axial movement parameters, such as duration and speed. RESULTS: Mean acceleration of nocturnal movements was lower in patients with PD compared to controls. Frequency and speed of axial movements did not differ between patients with PD and controls, but mean size and duration were lower in PD. The HR-PD group did not significantly differ from the control group in any of the parameters analysed. CONCLUSIONS: Compared with controls, patients with PD had an overall decreased mean acceleration, as well as smaller and shorter nocturnal axial movements. These changes did not occur in our potential HR-PD individuals, suggesting that relevant axial movement alterations during sleep have either not developed or cannot be detected by the means applied in this at-risk cohort.

Using photoplethysmography in heart rate monitoring of patients with epilepsy.

Heart rate is a useful neurophysiological sign when monitoring seizures in patients with epilepsy. In an ambulatory setting, heart rate is measured with ECG involving electrodes on the skin. This method is uncomfortable which is burdensome for patients and is sensitive to motion artifacts, which decrease the usability of measurements. In this study, green light photoplethysmography, an optical technique arising from the fitness industry, was evaluated for usefulness in a medical setting. Simultaneous overnight measurements of HR with a commercially available optical heart rate (OHR) sensor and with ECG (HRECG) were performed in 7 patients with epilepsy. Overall, there was no significant difference between OHR and HRECG in random 10-minute periods during wakefulness (p=0.69) and sleep (p=1.00). The Bland-Altman analysis showed negligible mean differences. Limits of agreement were higher during wakefulness and during the occurrence of two seizures possibly because of less reliable HRECG measurements due to motion artifacts. Optical heart rate seems less sensitive to these motion artifacts, and measurements are more user-friendly. The optical heart rate sensor may fill the gap of systems for ambulatory heart rate monitoring and can be especially useful in the context of seizure detection in patients with epilepsy.

Actigraphy as a diagnostic aid for REM sleep behavior disorder in Parkinson's disease.

BACKGROUND: Rapid eye movement (REM) sleep behavior disorder (RBD) is a common parasomnia in Parkinson's disease (PD) patients. The current International Classification of Sleep Disorders (ICSD-II) requires a clinical interview combined with video polysomnography (video-PSG) to diagnose. The latter is time consuming and expensive and not always feasible in clinical practice. Here we studied the use of actigraphy as a diagnostic tool for RBD in PD patients. METHODS: We studied 45 consecutive PD patients (66.7% men) with and without complaints of RBD. All patients underwent one night of video-PSG and eight consecutive nights of actigraphy. Based on previous studies, the main outcome measure was the total number of bouts classified as "wake", compared between patients with (PD + RBD) and without RBD (PD- RBD). RESULTS: 23 (51.1%) patients had RBD according to the ICSD-II criteria. The total number of wake bouts was significantly higher in RBD patients (PD + RBD 73.2 ± 40.2 vs. PD-RBD 48.4 ± 23.3, p = .016). A cut off of 95 wake bouts per night resulted in a specificity of 95.5%, a sensitivity of 20.1% and a positive predictive value of 85.7%. Seven patients were suspected of RBD based on the interview alone, but not confirmed on PSG; six of whom scored below 95 wake bouts per night on actigraphy. CONCLUSION: PD patients with RBD showed a significantly higher number of bouts scored as "wake" using actigraphy, compared to patients without RBD. In clinical practice, actigraphy has a high specificity, but low sensitivity in the diagnosis of RBD. The combination of actigraphy and previously reported RBD questionnaires may be a promising method to diagnose RBD in patients with PD.

Pitfalls in EEG Analysis in Patients With Nonconvulsive Status Epilepticus: A Preliminary Study.

Objective: Electroencephalography (EEG) interpretations through visual (by human raters) and automated (by computer technology) analysis were still not reliable for the diagnosis of nonconvulsive status epilepticus (NCSE). This study aimed to identify typical pitfalls in the EEG analysis and make suggestions as to how those pitfalls might be avoided. Methods: We analyzed the EEG recordings of individuals who had clinically confirmed or suspected NCSE. Epileptiform EEG activity during seizures (ictal discharges) was visually analyzed by 2 independent raters. We investigated whether unreliable EEG visual interpretations quantified by low interrater agreement can be predicted by the characteristics of ictal discharges and individuals' clinical data. In addition, the EEG recordings were automatically analyzed by in-house algorithms. To further explore the causes of unreliable EEG interpretations, 2 epileptologists analyzed EEG patterns most likely misinterpreted as ictal discharges based on the differences between the EEG interpretations through the visual and automated analysis. Results: Short ictal discharges with a gradual onset (developing over 3 s in length) were liable to be misinterpreted. An extra 2 min of ictal discharges contributed to an increase in the kappa statistics of >0.1. Other problems were the misinterpretation of abnormal background activity (slow-wave activities, other abnormal brain activity, and the ictal-like movement artifacts), continuous interictal discharges, and continuous short ictal discharges. Conclusion: A longer duration criterion for NCSE-EEGs than 10 s that is commonly used in NCSE working criteria is recommended. Using knowledge of historical EEGs, individualized algorithms, and context-dependent alarm thresholds may also avoid the pitfalls.

The cognitive effects of interictal epileptiform EEG discharges and short nonconvulsive epileptic seizures.

PURPOSE: Educational difficulties or even severe cognitive deterioration is seen in many childhood epilepsy syndromes. Many of those cognitive deficits are related directly to the brain disorder underlying the epilepsy syndrome. However, in other types of epilepsy, the epileptic seizures and/or epileptiform activity can be the dominant factor. This is especially unknown for the more "subtle" short nonconvulsive seizure types. For this reason, we analyzed a new cohort of children. METHODS: A cross-sectional study of 188 children with epilepsy. Electroencephalography (EEG)-video recordings and cognitive testing were performed simultaneously. The results of children with short nonconvulsive seizures during a 2-h testing session were compared with all children with epilepsy without seizures during the 2-h cognitive testing session and with controls without epilepsy. In a second analysis the cognitive effects of frequency of epileptiform EEG discharges were analyzed. KEY FINDINGS: The cognitive effects of short nonconvulsive seizures were large, ranging from 0.5 to 1 standard deviation and concerned global cognitive function, speed of central information processing, and memory function. In children without seizures during cognitive testing, the occurrence of frequent epileptiform discharges showed more subtle effects. These effects were independent from the occurrence of short nonconvulsive seizures. SIGNIFICANCE: We concluded that although the effect is less pronounced in number of areas involved and magnitude, the type of association between frequent epileptiform activity (>1% of the time) and cognitive function in children with epilepsy is comparable to the association between short nonconvulsive seizures and cognitive function.

Multimodal nocturnal seizure detection: Do we need to adapt algorithms for children?

OBJECTIVE: To assess the performance of a multimodal seizure detection device, first tested in adults (sensitivity 86%, PPV 49%), in a pediatric cohort living at home or residential care. METHODS: In this multicenter, prospective, video-controlled cohort-study, nocturnal seizures were detected by heartrate and movement changes in children with epilepsy and intellectual disability. Participants with a history of >1 monthly major motor seizure wore Nightwatch bracelet at night for 3 months. Major seizures were defined as tonic-clonic, generalized tonic >30 s, hyperkinetic, or clusters (>30 min) of short myoclonic or tonic seizures. The video of all events (alarms and nurse diaries) and about 10% of whole nights were reviewed to classify major seizures, and minor or no seizures. RESULTS: Twenty-three participants with focal or generalized epilepsy and nightly motor seizures were evaluated during 1511 nights, with 1710 major seizures. First 1014 nights, 4189 alarms occurred with average of 1.44/h, showing average sensitivity of 79.9% (median 75.4%) with mean PPV of 26.7% (median 11.1%) and false alarm rate of 0.2/hour. Over 90% of false alarms in children was due to heart rate (HR) part of the detection algorithm. To improve this rate, an adaptation was made such that the alarm was only triggered when the wearer was in horizontal position. For the remaining 497 nights, this was tested prospectively, 384 major seizures occurred. This resulted in mean PPV of 55.5% (median 58.1%) and a false alarm rate 0.08/h while maintaining a comparable mean sensitivity of 79.4% (median 93.2%). SIGNIFICANCE: Seizure detection devices that are used in bed which depend on heartrate and movement show similar sensitivity in children and adults. However, children do show general higher false alarm rate, mostly triggered while awake. By correcting for body position, the false alarms can be limited to a level that comes close to that in adults.

Association between the 1291-C/G polymorphism in the adrenergic α-2a receptor and the metabolic syndrome.

The prevalence of the metabolic syndrome is increased in patients with schizophrenia compared with the general population. The strong interindividual differences in susceptibility to developing the metabolic syndrome suggests that the genetic makeup is a modulating factor. Part of the genetic puzzle can possibly be explained by variations in the gene coding for the adrenergic α-2a receptor (ADRA2A) because this receptor plays an important role in lipolysis. Three studies have found an association between the α-2a 1291-C/G polymorphism and antipsychotic induced weight gain, with conflicting results between whites and Asians. No studies have been published investigating the association between the 1291-C/G polymorphism and the metabolic syndrome. The primary objective of this cross-sectional study was to investigate the association between the ADRA2A 1291-C/G polymorphism and the metabolic syndrome in 470 patients using antipsychotic drugs. There was no significant association between carriership of the variant 1291-G allele and prevalence of the metabolic syndrome (odds ratio, 0.73; 95% confidence interval, 0.49-1.15). Exploratory analysis showed an association between carriership of the variant 1291-G allele and a reduced prevalence of the metabolic syndrome in patients not currently using antipsychotics (odds ratio, 0.05; 95% confidence interval, 0.003-0.97; P = 0.048). In conclusion, this study shows that the ADRA2A 1291-C/G polymorphism does not seem to be a strong predictor for long-term occurrence of the metabolic syndrome in antipsychotic using patients. Studies investigating this association using a prospective, or retrospective, design, as well as studies investigating this association in a nonpsychiatric population, are warranted.

False alarms reduction in non-convulsive status epilepticus detection via continuous EEG analysis.

OBJECTIVE: Frequent false alarms from computer-assisted monitoring systems may harm the safety of patients with non-convulsive status epilepticus (NCSE). In this study, we aimed at reducing false alarms in the NCSE detection based on preventing from three common errors: over-interpretation of abnormal background activity, dense short ictal discharges and continuous interictal discharges as ictal discharges. APPROACH: We analyzed 10 participants' hospital-archived 127-hour electroencephalography (EEG) recordings with 310 ictal discharges. To reduce the false alarms caused by abnormal background activity, we used morphological features extracted by visibility graph methods in addition to time-frequency features. To reduce the false alarms caused by over-interpreting short ictal discharges and interictal discharges, we created two synthetic classes-'Suspected Non-ictal' and 'Suspected Ictal'-based on the misclassified categories and constructed a synthetic 4-class dataset combining the standard two classes-'Non-ictal' and 'Ictal'-to train a 4-class classifier. Precision-recall curves were used to compare our proposed 4-class classification model and the standard 2-class classification model with or without the morphological features in the leave-one-out cross validation stage. The sensitivity and precision were primarily used as performance metrics for the detection of a seizure event. MAIN RESULTS: The 4-class classification model improved the performance of the standard 2-class model, in particular increasing the precision by 15% at an 80% sensitivity level when only time-frequency features were used. Using the morphological features, the 4-class classification model achieved the best performances: a sensitivity of 93% ± 12% and a precision of 55% ± 30% in the group level. 100% accuracy was reached in a participant's 4.3-hour recording with 5 ictal discharges. SIGNIFICANCE: False alarms in the NCSE detection were remarkably reduced using the morphological features and the proposed 4-class classification model.

HTR2C gene polymorphisms and the metabolic syndrome in patients with schizophrenia: a replication study.

In a previous study, we found an association between 5-hydroxytryptamine (serotonin) receptor 2C (HTR2C) polymorphisms and the occurrence of the metabolic syndrome in patients using antipsychotics. In the current study, we set out to replicate our findings in another sample of patients and to explore in a pooled analysis of both samples the influence of the effect of individual antipsychotics. Data for this cross-sectional study came from 2 different samples, the original sample (n = 112) and the replication sample (n = 164). Primary end point was the prevalence of the metabolic syndrome as classified by a modified version of the National Cholesterol Education Program's Adult Treatment Panel III. Primary determinants were polymorphisms in the promoter region of the HTR2C gene [HTR2C:c.1-142948(GT)n, rs3813929 (-759 C/T), and rs518147 (-697 G/C)] and an intragenic polymorphism (rs1414334:C>G). The variants of HTR2C:c.1-142948(GT)n (odds ratio [OR], 1.69; 95% confidence interval [CI], 0.75-3.81) and rs1414334 (OR, 2.35; 95% CI, 0.96-5.77) were not significantly associated with the metabolic syndrome in the replication sample but did show significance in the pooled analysis (OR, 2.09; 95% CI, 1.12-3.91; and OR, 2.35; 95% CI, 1.19-4.62, respectively). The variant rs1414334 C allele was specifically associated with the metabolic syndrome in patients using clozapine (OR, 9.20; 95% CI, 1.95-43.45) or risperidone (OR, 5.35; 95% CI, 1.26-22.83). This study extends previous findings to a larger sample of patients and implicates specific antipsychotic drugs. The increased risk for the metabolic syndrome is particularly strong in carriers of the rs1414334 C allele using clozapine or risperidone.