Minimum clinical utility standards for wearable seizure detectors: A simulation study.

OBJECTIVE: Epilepsy management employs self-reported seizure diaries, despite evidence of seizure underreporting. Wearable and implantable seizure detection devices are now becoming more widely available. There are no clear guidelines about what levels of accuracy are sufficient. This study aimed to simulate clinical use cases and identify the necessary level of accuracy for each. METHODS: Using a realistic seizure simulator (CHOCOLATES), a ground truth was produced, which was then sampled to generate signals from simulated seizure detectors of various capabilities. Five use cases were evaluated: (1) randomized clinical trials (RCTs), (2) medication adjustment in clinic, (3) injury prevention, (4) sudden unexpected death in epilepsy (SUDEP) prevention, and (5) treatment of seizure clusters. We considered sensitivity (0%-100%), false alarm rate (FAR; 0-2/day), and device type (external wearable vs. implant) in each scenario. RESULTS: The RCT case was efficient for a wide range of wearable parameters, though implantable devices were preferred. Lower accuracy wearables resulted in subtle changes in the distribution of patients enrolled in RCTs, and therefore higher sensitivity and lower FAR values were preferred. In the clinic case, a wide range of sensitivity, FAR, and device type yielded similar results. For injury prevention, SUDEP prevention, and seizure cluster treatment, each scenario required high sensitivity and yet was minimally influenced by FAR. SIGNIFICANCE: The choice of use case is paramount in determining acceptable accuracy levels for a wearable seizure detection device. We offer simulation results for determining and verifying utility for specific use case and specific wearable parameters.

Myocarditis in anti-synthetase syndrome: clinical features and diagnostic modalities.

OBJECTIVES: Myocarditis is an overlooked manifestation of anti-synthetase syndrome (ASS). Our study describes the clinical and instrumental features of ASS-myocarditis and evaluates the diagnostic performance of cardiac magnetic resonance (CMR) with mapping techniques. METHODS: Data from ASS-patients were retrospectively analyzed. CMR data of patients diagnosed with myocarditis, including late gadolinium enhancement (LGE), T2-ratio, T1-mapping, extra-cellular volume (ECV) and T2-mapping, were reviewed. Myocarditis was defined by the presence of symptoms of heart involvement with increased high-sensitive troponin T (hs-TnT) and/or NT-proBNP and at least an instrumental abnormality. Clinical features of ASS patients with and without myocarditis were compared. A p value<0.05 was considered. RESULTS: Among a cohort of 43 ASS-patients (median age 58[48.0-66.0] years; females 74.4%; anti-Jo1 53.5%), 13(30%) were diagnosed with myocarditis. In 54% of patients, myocarditis was diagnosed at clinical onset. All ASS-myocarditis patients had at least one CMR abnormality: increased ECV in all cases, presence of LGE, increased T1 and T2-mapping in 91%. The 2009-Lake Louis criteria (LLC) were satisfied by 6 patients, the 2018-LLC by 10. With the updated LLC, the sensitivity for myocarditis improved from 54.6% to 91.0%. ASS-patients with myocarditis were more frequently males(53% vs 13%;p=0.009) with fever(69% vs 17%;p=0.001), and had higher hs-TnT (88.0[23.55-311.5] vs 9.80[5.0-23.0]ng/L; p < 0.001), NT-proBNP(525.5[243.5-1575.25] vs 59.0[32.0-165.5;p=0.013]pg/ml;p=0.013) and C-reactive protein(CRP)(7.0[1.7-15.75] vs 1.85[0.5-2.86]mg/L;p=0.011) compared to those without myocarditis. CONCLUSION: In ASS, myocarditis is frequent, even at clinical onset. ASS-patients with myocarditis frequently presented with fever and increased CRP, suggesting the existence of an inflammatory phenotype. The use of novel CMR mapping techniques may increase the diagnostic sensitivity for myocarditis in ASS.

Imaging for the assessment of the arrhythmogenic potential of mitral valve prolapse.

Mitral valve prolapse (MVP) is the most common valve disease in the western world and recently emerged as a possible substrate for sudden cardiac death (SCD). It is estimated an annual risk of sudden cardiac death of 0.2 to 1.9% mostly caused by complex ventricular arrhythmias (VA). Several mechanisms have been recognized as potentially responsible for arrhythmia onset in MVP, resulting from the combination of morpho-functional abnormality of the mitral valve, structural substrates (regional myocardial hypertrophy, fibrosis, Purkinje fibers activity, inflammation), and mechanical stretch. Echocardiography plays a central role in MVP diagnosis and assessment of severity of regurgitation. Several abnormalities detectable by echocardiography can be prognostic for the occurrence of VA, from morphological alteration including leaflet redundancy and thickness, mitral annular dilatation, and mitral annulus disjunction (MAD), to motion abnormalities detectable with "Pickelhaube" sign. Additionally, speckle-tracking echocardiography may identify MVP patients at higher risk for VA by detection of increased mechanical dispersion. On the other hand, cardiac magnetic resonance (CMR) has the capability to provide a comprehensive risk stratification combining the identification of morphological and motion alteration with the detection of myocardial replacement and interstitial fibrosis, making CMR an ideal method for arrhythmia risk stratification in patients with MVP. Finally, recent studies have suggested a potential role in risk stratification of new techniques such as hybrid PET-MR and late contrast enhancement CT. The purpose of this review is to provide an overview of the mitral valve prolapse syndrome with a focus on the role of imaging in arrhythmic risk stratification. CLINICAL RELEVANCE STATEMENT: Mitral valve prolapse is the most frequent valve condition potentially associated with arrhythmias. Imaging has a central role in the identification of anatomical, functional, mechanical, and structural alterations potentially associated with a higher risk of developing complex ventricular arrhythmia and sudden cardiac death. KEY POINTS: • Mitral valve prolapse is a common valve disease potentially associated with complex ventricular arrhythmia and sudden cardiac death. • The mechanism of arrhythmogenesis in mitral valve prolapse is complex and multifactorial, due to the interplay among multiple conditions including valve morphological alteration, mechanical stretch, myocardial structure remodeling with fibrosis, and inflammation. • Cardiac imaging, especially echocardiography and cardiac magnetic resonance, is crucial in the identification of several features associated with the potential risk of serious cardiac events. In particular, cardiac magnetic resonance has the advantage of being able to detect myocardial fibrosis which is currently the strongest prognosticator.

Cardiac magnetic resonance findings in acute and post-acute COVID-19 patients with suspected myocarditis.

INTRODUCTION: Cardiac injury is commonly reported in COVID-19 patients, resulting associated to pre-existing cardiovascular disease, disease severity, and unfavorable outcome. Aim is to report cardiac magnetic resonance (CMR) findings in patients with myocarditis-like syndrome during the acute phase of SARS-CoV-2 infection (AMCovS) and post-acute phase (cPACS). METHODS: Between September 2020 and January 2022, 39 consecutive patients (24 males, 58%) were referred to our department to perform a CMR for the suspicion of myocarditis related to AMCovS (n = 17) and cPACS (n = 22) at multimodality evaluation (clinical, laboratory, ECG, and echocardiography). CMR was performed for the assessment of volume, function, edema and fibrosis with standard sequences and mapping techniques. CMR diagnosis and the extension and amount of CMR alterations were recorded. RESULTS: Patients with suspected myocarditis in acute and post-COVID settings were mainly men (10 (59%) and 12 (54.5%), respectively) with older age in AMCovS (58 [48-64]) compared to cPACS (38 [26-53]). Myocarditis was confirmed by CMR in most of cases: 53% of AMCovS and 50% of cPACS with negligible LGE burden (3 [IQR, 1-5] % and 2 [IQR, 1-4] %, respectively). Myocardial infarction was identified in 4/17 (24%) patients with AMCovS. Cardiomyopathies were identified in 12% (3/17) and 27% (6/22) of patients with AMCovS and cPACS, including DCM, HCM and mitral valve prolapse. CONCLUSIONS: In patients with acute and post-acute COVID-19 related suspected myocarditis, CMR improves diagnostic accuracy characterizing ischemic and non-ischemic injury and unraveling subclinical cardiomyopathies.

Cardiovascular involvement in Erdheim-Chester diseases is associated with myocardial fibrosis and atrial dysfunction.

PURPOSE: Erdheim-Chester disease (ECD) is a rare multisystem histiocytosis, whose cardiovascular involvement has not been systematically characterized so far. We aimed to systematically (qualitatively and quantitatively) describe the features of cardiovascular involvement in a large cohort of ECD patients and to evaluate its impact on myocardial fibrosis extension and cardiac function. MATERIAL AND METHODS: Among 54 patients with biopsy-proven ECD, 29 patients (59 ± 12 years, 79% males) underwent 1.5-T CMR using a standardized protocol for qualitative and quantitative assessment of disease localization, evaluation of atrial and ventricular function, and assessment of non-dense and dense myocardial fibrosis. RESULTS: The right atrioventricular (AV) groove was the most commonly affected cardiac site (76%) followed by the right atrial walls (63%), thoracic aorta (59%), and superior vena cava (38%). Right AV groove involvement, encasing the right ventricular artery, was associated with non-dense myocardial fibrosis in the infero-septal (20/26 patients) and the inferior (14/26 patients) mid-basal left ventricular (LV) wall. In two patients with right AV groove localization, LGE revealed myocardial infarction in the same myocardial segments. Three out of five patients with left AV groove involvement had non-dense LGE on the lateral LV mid-basal wall. Bulky right atrial pseudomass was associated with atrial dysfunction and superior and inferior vena cava stenosis. CONCLUSIONS: In ECD patients, AV groove localization is associated with LV wall fibrosis in the downstream coronary territories, suggesting hemodynamic alterations due to coronary encasement. Conversely, atrial pseudomass ECD localizations impact on atrial contractility causing atrial dysfunction and are associated with atrio-caval junction stenosis.

Cardiac magnetic resonance in systemic sclerosis myocarditis: the value of T2 mapping to detect myocardial inflammation.

OBJECTIVES: Myocarditis in SSc is associated with a poor prognosis. Cardiac magnetic resonance (CMR) is the non-invasive diagnostic modality of choice for SSc myocarditis. Our study investigates the performance of the mapping techniques included in the revised Lake Louise criteria (LLC) for the identification of SSc myocarditis. METHODS: CMR data (right and left ventricular function and morphology, early and late gadolinium enhancement [LGE], T2 ratio, and T1 mapping, extracellular volume [ECV] and T2 mapping) of SSc patients diagnosed with myocarditis were reviewed. Myocarditis was defined by the presence of symptoms of SSc heart involvement with increased high-sensitive troponin T (hs-TnT) and/or NT-proBNP and at least an abnormality at 24 h ECG Holter and/or echocardiography and/or CMR. A P-value < 0.05 was considered as statistically significant. RESULTS: Nineteen patients (median age 54 [46-70] years; females 78.9%; diffuse SSc 52.6%; anti-Scl70+ 52.6%) were identified: 11 (57.9%) had echocardiographic, and 8 (42.8%) 24 h ECG Holter abnormalities. All patients had at least one CMR abnormality: LGE in 18 (94.7%), increased ECV in 10 (52.6%) and T2 mapping >50 ms in 15 (78.9%). Median T1 and T2 mapping were 1085 [1069-1110] ms and 53.1 [52-54] ms, respectively. T1 mapping directly correlated with NT-proBNP (r = 0.620; P = 0.005), ESR (r = 0.601; P = 0.008), CRP (r = 0.685; P = 0.001) and skin score (r = 0.507; P = 0.027); ECV correlated with NT-proBNP serum levels (r = 0.702; P = 0.001). No correlations emerged between T2 mapping and other parameters. Ten patients satisfied the 2009 LLC, 17 the 2018 LLC. With the new criteria including T2 mapping, the sensitivity improved from 52.6% to 89.5%. CONCLUSION: The CMR mapping techniques improve the sensitivity to detect myocardial inflammation in patients with SSc heart involvement. The evaluation of T2 mapping increases diagnostic accuracy for the recognition of myocardial inflammation in SSc.

Noninvasive mobile EEG as a tool for seizure monitoring and management: A systematic review.

In the last two decades new noninvasive mobile electroencephalography (EEG) solutions have been developed to overcome limitations of conventional clinical EEG and to improve monitoring of patients with long-term conditions. Despite the availability of mobile innovations, their adoption is still very limited. The aim of this study is to review the current state-of-the-art and highlight the main advantages of adopting noninvasive mobile EEG solutions in clinical trials and research studies of people with epilepsy or suspected seizures. Device characteristics are described, and their evaluation is presented. Two authors independently performed a literature review in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A combination of different digital libraries was used (Embase, MEDLINE, Global Health, PsycINFO and https://clinicaltrials.gov/). Twenty-three full-text, six conference abstracts, and eight webpages were included, where a total of 14 noninvasive mobile solutions were identified. Published studies demonstrated at different levels how EEG recorded via mobile EEG can be used for visual detection of EEG abnormalities and for the application of automatic-detection algorithms with acceptable specificity and sensitivity. When the quality of the signal was compared with scalp EEG, many similarities were found in the background activities and power spectrum. Several studies indicated that the experience of patients and health care providers using mobile EEG was positive in different settings. Ongoing trials are focused mostly on improving seizure-detection accuracy and also on testing and assessing feasibility and acceptability of noninvasive devices in the hospital and at home. This review supports the potential clinical value of noninvasive mobile EEG systems and their advantages in terms of time, technical support, cost, usability, and reliability when applied to seizure detection and management. On the other hand, the limitations of the studies confirmed that future research is needed to provide more evidence regarding feasibility and acceptability in different settings, as well as the data quality and detection accuracy of new noninvasive mobile EEG solutions.

Diagnostic yield and limitations of in-hospital documentation in patients with epilepsy.

OBJECTIVE: To determine the diagnostic yield of in-hospital video-electroencephalography (EEG) monitoring to document seizures in patients with epilepsy. METHODS: Retrospective analysis of electronic seizure documentation at the University Hospital Freiburg (UKF) and at King's College London (KCL). Statistical assessment of the role of the duration of monitoring, and subanalyses on presurgical patient groups and patients undergoing reduction of antiseizure medication. RESULTS: Of more than 4800 patients with epilepsy undergoing in-hospital recordings at the two institutions since 2005, seizures with documented for 43% (KCL) and 73% (UKF).. Duration of monitoring was highly significantly associated with seizure recordings (p < .0001), and presurgical patients as well as patients with drug reduction had a significantly higher diagnostic yield (p < .0001). Recordings with a duration of >5 days lead to additional new seizure documentation in only less than 10% of patients. SIGNIFICANCE: There is a need for the development of new ambulatory monitoring strategies to document seizures for diagnostic and monitoring purposes for a relevant subgroup of patients with epilepsy in whom in-hospital monitoring fails to document seizures.

Electrodermal activity response during seizures: A systematic review and meta-analysis.

INTRODUCTION: Wearable devices for continuous seizure monitoring have drawn increasing attention in the field of epilepsy research. One of the parameters recorded by these devices is electrodermal activity (EDA). The aim of this study was to systematically review the literature to estimate the incidence of electrodermal response during seizures. METHODS: We searched all articles recording concurrent EDA and EEG activity during the pre-ictal, ictal, and postictal periods in children and adults with epilepsy. Studies reporting the total number of seizures and number of seizures with an EDA response were included for a random-effects meta-analysis. RESULTS: Nineteen studies, including 550 participants and 1115 seizures were reviewed. All studies demonstrated an EDA increase during the ictal and postictal periods, while only three reported pre-ictal EDA responses. The meta-analysis showed a pooled EDA response incidence of 82/100 seizures (95% CI 70-91). Tonic-clonic seizures (both generalized tonic-clonic seizures (GTCS) and focal to bilateral tonic-clonic seizures (FBTCS)) elicited a more pronounced (higher and longer-lasting) EDA response when compared with focal seizures (excluding FBTCS). DISCUSSION: Epileptic seizures produce an electrodermal response detectable by wearable devices during the pre-ictal, ictal, and postictal periods. Further research is needed to better understand EDA changes and to analyze factors which may influence the EDA response.

Intra- and Inter-Subject Perspectives on the Detection of Focal Onset Motor Seizures in Epilepsy Patients.

Focal onset epileptic seizures are highly heterogeneous in their clinical manifestations, and a robust seizure detection across patient cohorts has to date not been achieved. Here, we assess and discuss the potential of supervised machine learning models for the detection of focal onset motor seizures by means of a wrist-worn wearable device, both in a personalized context as well as across patients. Wearable data were recorded in-hospital from patients with epilepsy at two epilepsy centers. Accelerometry, electrodermal activity, and blood volume pulse data were processed and features for each of the biosignal modalities were calculated. Following a leave-one-out approach, a gradient tree boosting machine learning model was optimized and tested in an intra-subject and inter-subject evaluation. In total, 20 seizures from 9 patients were included and we report sensitivities of 67% to 100% and false alarm rates of down to 0.85 per 24 h in the individualized assessment. Conversely, for an inter-subject seizure detection methodology tested on an out-of-sample data set, an optimized model could only achieve a sensitivity of 75% at a false alarm rate of 13.4 per 24 h. We demonstrate that robustly detecting focal onset motor seizures with tonic or clonic movements from wearable data may be possible for individuals, depending on specific seizure manifestations.

Wearable devices for seizure detection: Practical experiences and recommendations from the Wearables for Epilepsy And Research (WEAR) International Study Group.

The Wearables for Epilepsy And Research (WEAR) International Study Group identified a set of methodology standards to guide research on wearable devices for seizure detection. We formed an international consortium of experts from clinical research, engineering, computer science, and data analytics at the beginning of 2020. The study protocols and practical experience acquired during the development of wearable research studies were discussed and analyzed during bi-weekly virtual meetings to highlight commonalities, strengths, and weaknesses, and to formulate recommendations. Seven major essential components of the experimental design were identified, and recommendations were formulated about: (1) description of study aims, (2) policies and agreements, (3) study population, (4) data collection and technical infrastructure, (5) devices, (6) reporting results, and (7) data sharing. Introducing a framework of methodology standards promotes optimal, accurate, and consistent data collection. It also guarantees that studies are generalizable and comparable, and that results can be replicated, validated, and shared.

Seizure detection at home: Do devices on the market match the needs of people living with epilepsy and their caregivers?

In patients with epilepsy, the potential to prevent seizure-related injuries and to improve the unreliability of seizure self-report have fostered the development and marketing of numerous seizure detection devices for home use. Understanding the requirements of users (patients and caregivers) is essential to improve adherence and mitigate barriers to the long-term use of such devices. Here we reviewed the evidence on the needs and preferences of users and provided an overview of currently marketed devices for seizure detection (medically approved or with published evidence for their performance). We then compared devices with known needs. Seizure-detection devices are expected to improve safety and clinical and self-management, and to provide reassurance to users. Key factors affecting a device's usability relate to its design (attractive appearance, low visibility, low intrusiveness), comfort of use, confidentiality of recorded data, and timely support from both technical and clinical ends. High detection sensitivity and low false alarm rates are paramount. Currently marketed devices are focused primarily on the recording of non-electroencephalography (EEG) signals associated with tonic-clonic seizures, whereas the detection of focal seizures without major motor features remains a clear evidence gap. Moreover, there is paucity of evidence coming from real-life settings. A joint effort of clinical and nonclinical experts, patients, and caregivers is required to ensure an optimal level of acceptability and usability, which are key aspects for a successful continuous monitoring aimed at seizure detection at home.

Post-ictal accelerometer silence as a marker of post-ictal immobility.

OBJECTIVE: Movement-based wearable sensors are used for detection of convulsive seizures. The identification of the absence of motion following a seizure, known as post-ictal immobility (PI), may represent a potential additional application of wearables. PI has been associated with potentially life-threatening complications and with sudden unexpected death in epilepsy (SUDEP). We aimed to assess whether wearable accelerometers (ACCs) could be used as a digital marker of PI. METHOD: Devices with embedded ACCs were worn by patients admitted to an epilepsy monitoring unit. Participants presenting with convulsive seizures were included in the study. PI presence and duration were assessed by experts reviewing video recordings. An algorithm for the automatic detection of post-ictal ACC silence and its duration was developed and the linear pairwise relationship between the automatically detected duration of post-ictal ACC silence and the duration of the expert-labeled PI was analyzed. RESULTS: Twenty-two convulsive seizures were recorded from 18 study participants. Twenty were followed by PI and two by agitation. The automated estimation of post-ictal ACC silence identified all the 20 expert-labeled PI. The regression showed that the duration of the post-ictal ACC silence was correlated with the duration of PI (Pearson r = .92; P < .001), with the age of study participants (Pearson r = .78; P < .001), and with the duration of post-ictal generalized electroencephalography suppression (PGES; Pearson r = .4; P = .033). SIGNIFICANCE: We highlight a novel application of wearables as a way to record post-ictal manifestations associated with an increased risk of SUDEP. The occurrence of a fatal seizure is unpredictable and the continuous, non-invasive, long-term identification of risk factors associated with each individual seizure may assume a great clinical importance.

Signal quality and patient experience with wearable devices for epilepsy management.

Noninvasive wearable devices have great potential to aid the management of epilepsy, but these devices must have robust signal quality, and patients must be willing to wear them for long periods of time. Automated machine learning classification of wearable biosensor signals requires quantitative measures of signal quality to automatically reject poor-quality or corrupt data segments. In this study, commercially available wearable sensors were placed on patients with epilepsy undergoing in-hospital or in-home electroencephalographic (EEG) monitoring, and healthy volunteers. Empatica E4 and Biovotion Everion were used to record accelerometry (ACC), photoplethysmography (PPG), and electrodermal activity (EDA). Byteflies Sensor Dots were used to record ACC and PPG, the Activinsights GENEActiv watch to record ACC, and Epitel Epilog to record EEG data. PPG and EDA signals were recorded for multiple days, then epochs of high-quality, marginal-quality, or poor-quality data were visually identified by reviewers, and reviewer annotations were compared to automated signal quality measures. For ACC, the ratio of spectral power from 0.8 to 5 Hz to broadband power was used to separate good-quality signals from noise. For EDA, the rate of amplitude change and prevalence of sharp peaks significantly differentiated between good-quality data and noise. Spectral entropy was used to assess PPG and showed significant differences between good-, marginal-, and poor-quality signals. EEG data were evaluated using methods to identify a spectral noise cutoff frequency. Patients were asked to rate the usability and comfort of each device in several categories. Patients showed a significant preference for the wrist-worn devices, and the Empatica E4 device was preferred most often. Current wearable devices can provide high-quality data and are acceptable for routine use, but continued development is needed to improve data quality, consistency, and management, as well as acceptability to patients.

Day and night comfort and stability on the body of four wearable devices for seizure detection: A direct user-experience.

PURPOSE: Wearable devices are progressively becoming an available tool for continuous seizure detection. Motivation to use wearables is not only driven by the accuracy and reliability of the performance but also by the form factor, comfort, and stability on the body. We collected direct feedback and device placement-related issues experienced by a cohort of people with epilepsy (PWE) to investigate to what extent available devices are nonintrusive, comfortable, and stable on the body. METHODS: Four models of wearable devices (E4 wrist band, Everion upper arm band, IMEC upper arm band, and Epilog scalp patch electrodes) were worn by PWE who were admitted to two epilepsy monitoring units (EMUs) in London and Freiburg. Participants were periodically reviewed, and accidental displacements of the devices were annotated. Participants' experience was assessed using the Technology Acceptance Model Fast Form (TAM-FF) plus two additional questions on comfort. A thematic analysis was also performed on the free text of the questionnaire. RESULTS: One hundred and fifteen participants were enrolled. The devices had a good stability on the body including during seizures. Overall, all the devices were considered comfortable to be worn, including during sleep. However, devices containing wires and patches demonstrated a lesser degree of stability on the body and were judged less positively. Participants age was correlated with TAM-FF mean scores, and older participants judged the devices less favorably compared with younger participants. DISCUSSION: Removable but securely fitted, wireless, and comfortable designs were considered more appropriate for a continuous monitoring aimed at seizure detection. Some caution may be required when patch electrodes and electrodes glued to the skin or to the scalp are used, as those evaluated in the present study demonstrated a lower level of acceptability and a lower degree of stability to the body, especially at night. These factors could limit a continuous monitoring decreasing the device performance for nocturnal, unsupervised seizures which are at higher risk of lethality.

Patients' experience of wearing multimodal sensor devices intended to detect epileptic seizures: A qualitative analysis.

BACKGROUND: The health management of patients with epilepsy could be improved by wearing devices that reliably detect when epileptic seizures happen. For the devices to be widely adopted, they must be acceptable and easy to use for patients, and their views are very important. Previous studies have collected feedback from patients on hypothetical devices, but very few have examined experience of wearing actual devices. PURPOSE: This study assessed the first-hand experiences of people with epilepsy using wearable devices, continuously over a period of time. The aim was to understand how acceptable and easy they were to use, and whether it is reasonable to expect that people will use them. MATERIALS AND METHODS: Adults with a diagnosis of epilepsy admitted routinely to a hospital epilepsy monitoring unit were asked to wear one, or more, wearable biosensor devices, tested for seizure detection. The devices are designed to continuously monitor and record signals from the body (biosignals). Participants completed semistructured interviews about their experiences of wearing the device(s). A systematic thematic analysis extracted themes from the interviews, focusing on acceptability and usability. Feedback was organized into (1) participants' experiences of the devices, any support they required and reasons for stopping wearing them; (2) their thoughts about using this technology outside a hospital setting. RESULTS: Twenty-one people with epilepsy wore one, or more, wearable devices for an average of 112.81 (SD = 71.83) hours. Participants found the devices convenient, and had no problem wearing them in hospital or sharing the data collected from them with the researchers and medical professionals. However, the presence of wires, bulky size, discomfort, and need for support, moderated experience. Participants' thoughts about wearing them in everyday life were strongly influenced by how visible and perceived accuracy. Willingness to use a smartphone app to complete questionnaires depended on the frequency, number of questions, and support. CONCLUSIONS: Overall, this work provides evidence about the feasibility and acceptability of using wearable devices to monitor seizure activity in people with epilepsy. Key barriers and facilitators to use while in hospital and hypothetical use in everyday life were identified and will be helpful for guiding future implementation.

Patient perspectives on the acceptability of mHealth technology for remote measurement and management of epilepsy: A qualitative analysis.

BACKGROUND: Innovative uses of mobile health (mHealth) technology for real-time measurement and management of epilepsy may improve the care provided to patients. For instance, seizure detection and quantifying related problems will have an impact on quality of life and improve clinical management for people experiencing frequent and uncontrolled seizures. Engaging patients with mHealth technology is essential, but little is known about patient perspectives on their acceptability. The aim of this study was to conduct an in-depth qualitative analysis of what people with uncontrolled epilepsy think could be the potential uses of mHealth technology and to identify early potential barriers and facilitators to engagement in three European countries. METHOD: Twenty people currently experiencing epileptic seizures took part in five focus groups held across the UK, Italy, and Spain. Participants all completed written consent and a demographic questionnaire prior to the focus group commencing, and each group discussion lasted 60-120 min. A coding frame, developed from a systematic review of the previous literature, was used to structure a thematic analysis. We extracted themes and subthemes from the discussions, focusing first on possible uses of mHealth and then the barriers and facilitators to engagement. RESULTS: Participants were interested in mHealth technology as a clinical detection tool, e.g., to aid communication about seizure occurrence with their doctors. Other suggested uses included being able to predict or prevent seizures, and to improve self-management. Key facilitators to engagement were the ability to raise awareness, plan activities better, and improve safety. Key barriers were the potential for increased stigma and anxiety. Using familiar and customizable products could be important moderators of engagement. CONCLUSION: People with uncontrolled epilepsy think that there is a scope for mHealth technology to be useful in healthcare as a detection or prediction tool. The costs will be compared with the benefits when it comes to engagement, and ongoing work with patients and other stakeholders is needed to design practical resources.

Wearable technology in epilepsy: The views of patients, caregivers, and healthcare professionals.

PURPOSE: In recent years, digital technology and wearable devices applied to seizure detection have progressively become available. In this study, we investigated the perspectives of people with epilepsy (PWE), caregivers (CG), and healthcare professionals (HP). We were interested in their current use of digital technology as well as their willingness to use wearables to monitor seizures. We also explored the role of factors influencing engagement with technology, including demographic and clinical characteristics, data confidentiality, need for technical support, and concerns about strain or increased workload. METHODS: An online survey drawing on previous data collected via focus groups was constructed and distributed via a web link. Using logistic regression analyses, demographic, clinical, and other factors identified to influence engagement with technology were correlated with reported use and willingness to use digital technology and wearables for seizure tracking. RESULTS: Eighty-seven surveys were completed, fifty-two (59.7%) by PWE, 13 (14.4%) by CG, and 22 (25.3%) by HP. Responders were familiar with multiple digital technologies, including the Internet, smartphones, and personal computers, and the use of digital services was similar to the UK average. Moreover, age and disease-related factors did not influence access to digital technology. The majority of PWE were willing to use a wearable device for long-term seizure tracking. However, only a limited number of PWE reported current regular use of wearables, and nonusers attributed their choice to uncertainty about the usefulness of this technology in epilepsy care. People with epilepsy envisaged the possibility of understanding their condition better through wearables and considered, with caution, the option to send automatic emergency calls. Despite concerns around accuracy, data confidentiality, and technical support, these factors did not limit PWE's willingness to use digital technology. Caregivers appeared willing to provide support to PWE using wearables and perceived a reduction of their workload and anxiety. Healthcare professionals identified areas of application for digital technologies in their clinical practice, pending an appropriate reorganization of the clinical team to share the burden of data reviewing and handling. CONCLUSIONS: Unlike people who have other chronic health conditions, PWE appeared not to be at risk of digital exclusion. This study highlighted a great interest in the use of wearable technology across epilepsy service users, carers, and healthcare professionals, which was independent of demographic and clinical factors and outpaced data security and technology usability concerns.

Zonisamide for essential tremor.

BACKGROUND: Essential tremor (ET) is one of the most common movement disorders. The treatment is primarily based on pharmacological agents. Although primidone and propranolol are well established treatments in clinical practice, they can be ineffective in 25% to 55% of patients, and can produce serious adverse events in a large percentage of them. For these reasons, it may be worthwhile evaluating the treatment alternatives for ET. Zonisamide has been suggested as a potentially useful agent for the treatment of ET but there is uncertainty about its efficacy and safety. OBJECTIVES: To assess the effect on functional abilities and the safety profile of zonisamide in adults with essential tremor (ET). SEARCH METHODS: We carried out a systematic search, without language restrictions to identify all relevant trials. We searched CENTRAL, MEDLINE, Embase, NICE, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform (ICTRP) to January 2017. We searched BIOSIS Citation Index (2000 to January 2017) for conference proceedings. We handsearched grey literature and examined the reference lists of identified studies and reviews. SELECTION CRITERIA: We included all randomised controlled trials (RCTs) of zonisamide versus placebo or any other treatment. We included studies in which the diagnosis of ET was made according to accepted and validated diagnostic criteria. We excluded studies conducted in patients presenting secondary forms of tremor or reporting only neurophysiological parameters to assess outcomes. DATA COLLECTION AND ANALYSIS: Two review authors independently collected and extracted data using a data collection form. We assessed the risk of bias and the quality of evidence.We used inverse variance methods for continuous outcomes and measurement scales. We compared differences between treatment groups as mean differences. We combined results for dichotomous outcomes using Mantel-Haenszel methods and obtained risk differences to compare treatment groups. We used Review Manager 5 software for data management and analysis. MAIN RESULTS: We only considered one study eligible for this review (20 participants). Assessments of risk of bias for most domains were unclear or low. Adverse events were only reported in participants from the zonisamide group, making it possible that they were aware of treatment group assignment. We are uncertain as to the effects of zonisamide on motor tasks (mean difference (MD) -0.00, 95% confidence interval (CI) -1.51 to 1.51, very low-quality evidence) and functional disabilities (MD -0.30, 95% CI -1.23 to 0.63, very low-quality evidence) when compared with placebo. Three participants in the zonisamide group (30%) and two participants in the placebo group (20%) discontinued the treatment and withdrew from the study for any reason (very low-quality evidence), however the increased risk of withdrawal in the zonisamide group was statistically non-significant (risk difference (RD) 0.1, 95% CI -0.28 to 0.48). Six participants in the zonisamide group (60%) and none of the participants in the placebo group (0%) developed adverse events (AEs), with a RD of 0.60 (95% CI 0.28 to 0.92; very low quality evidence). The most common AEs, experienced with zonisamide treatment, were headache, nausea, fatigue, sleepiness, and diarrhoea. Quality of life was not assessed in the study included. AUTHORS' CONCLUSIONS: Based on currently available data, there is insufficient evidence to assess the efficacy and safety of zonisamide treatment for ET.

Topiramate for essential tremor.

BACKGROUND: Essential tremor (ET) is one of the most common movement disorders. The management is primarily based on pharmacological agents and in clinical practice propranolol and primidone are considered the first-line therapy. However, these treatments can be ineffective in 25% to 55% of people and are frequently associated with serious adverse events (AEs). For these reasons, it is worthwhile evaluating other treatments for ET. Topiramate has been suggested as a potentially useful agent for the treatment of ET but there is uncertainty about its efficacy and safety. OBJECTIVES: To assess the efficacy and safety of topiramate in the treatment of ET. SEARCH METHODS: We carried out a systematic search without language restrictions to identify all relevant trials in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (January 1966 to January 2017), Embase (January 1988 to January 2017), National Institute for Health and Care Excellence (1999 to January 2017), ClinicalTrials.gov (1997 to January 2017) and World Health Organization International Clinical Trials Registry Platform (ICTRP; 2004 to January 2017). We searched BIOSIS Citation Index (2000 to January 2017) for conference proceedings. We handsearched grey literature and the reference lists of identified studies and reviews. SELECTION CRITERIA: We included all randomised controlled trials (RCTs) of topiramate versus placebo/open control or any other treatments. We included studies in which the diagnosis of ET was made according to accepted and validated diagnostic criteria. We excluded studies conducted in people presenting with secondary forms of tremor or reporting only neurophysiological parameters to assess outcomes. DATA COLLECTION AND ANALYSIS: Two review authors independently collected and extracted data using a data collection form. We assessed the risk of bias and the quality of evidence. We used a fixed-effect meta-analysis for data synthesis. MAIN RESULTS: This review included three trials comparing topiramate to placebo (309 participants). They were all at high overall risk of bias. The quality of evidence ranged from very low to low. Compared to placebo, participants treated with topiramate showed a significant improvement in functional disability and an increased risk of withdrawal (risk ratio (RR) 1.78, 95% confidence interval (CI) 1.23 to 2.60). There were more AEs for topiramate-treated participants, particularly paraesthesia, weight loss, appetite decrease and memory difficulty. AUTHORS' CONCLUSIONS: This systematic review highlighted the presence of limited data and very low to low quality evidence to support the apparent efficacy and the occurrence of treatment-limiting AEs in people with ET treated with topiramate. Further research to assess topiramate efficacy and safety on ET is needed.