Digital wearable insole-based identification of knee arthropathies and gait signatures using machine learning.

Gait is impaired in musculoskeletal conditions, such as knee arthropathy. Gait analysis is used in clinical practice to inform diagnosis and monitor disease progression or intervention response. However, clinical gait analysis relies on subjective visual observation of walking as objective gait analysis has not been possible within clinical settings due to the expensive equipment, large-scale facilities, and highly trained staff required. Relatively low-cost wearable digital insoles may offer a solution to these challenges. In this work, we demonstrate how a digital insole measuring osteoarthritis-specific gait signatures yields similar results to the clinical gait-lab standard. To achieve this, we constructed a machine learning model, trained on force plate data collected in participants with knee arthropathy and controls. This model was highly predictive of force plate data from a validation set (area under the receiver operating characteristics curve [auROC] = 0.86; area under the precision-recall curve [auPR] = 0.90) and of a separate, independent digital insole dataset containing control and knee osteoarthritis subjects (auROC = 0.83; auPR = 0.86). After showing that digital insole-derived gait characteristics are comparable to traditional gait measurements, we next showed that a single stride of raw sensor time-series data could be accurately assigned to each subject, highlighting that individuals using digital insoles can be identified by their gait characteristics. This work provides a framework for a promising alternative to traditional clinical gait analysis methods, adds to the growing body of knowledge regarding wearable technology analytical pipelines, and supports clinical development of at-home gait assessments, with the potential to improve the ease, frequency, and depth of patient monitoring.

The way we walk ­ our 'gait' ­ is a key indicator of health. Gait irregularities like limping, shuffling or a slow pace can be signs of muscle or joint problems. Assessing a patient's gait is therefore an important element in diagnosing these conditions, and in evaluating whether treatments are working. Gait is often assessed via a simple visual inspection, with patients being asked to walk back and forth in a doctor's office. While quick and easy, this approach is highly subjective and therefore imprecise. 'Objective gait analysis' is a more accurate alternative, but it relies on tests being conducted in specialised laboratories with large-scale, expensive equipment operated by highly trained staff. Unfortunately, this means that gait laboratories are not accessible for everyday clinical use. In response, Wipperman et al. aimed to develop a low-cost alternative to the complex equipment used in gait laboratories. To do this, they harnessed wearable sensor technologies ­ devices that can directly measure physiological data while embedded in clothing or attached to the user. Wearable sensors have the advantage of being cheap, easy to use, and able to provide clinically useful information without specially trained staff. Wipperman et al. analysed data from classic gait laboratory devices, as well as 'digital insoles' equipped with sensors that captured foot movements and pressure as participants walked. The analysis first 'trained' on data from gait laboratories (called force plates) and then applied the method to gait measurements obtained from digital insoles worn by either healthy participants or patients with knee problems. Analysis of the pressure data from the insoles confirmed that they could accurately predict which measurements were from healthy individuals, and which were from patients. The gait characteristics detected by the insoles were also comparable to lab-based measurements ­ in other words, the insoles provided similar type and quality of data as a gait laboratory. Further analysis revealed that information from just a single step could reveal additional information about the subject's walking. These results support the use of wearable devices as a simple and relatively inexpensive way to measure gait in everyday clinical practice, without the need for specialised laboratories and visits to the doctor's office. Although the digital insoles will require further analytical and clinical study before they can be widely used, Wipperman et al. hope they will eventually make monitoring muscle and joint conditions easier and more affordable.

Rare coding variants in CHRNB2 reduce the likelihood of smoking.

Human genetic studies of smoking behavior have been thus far largely limited to common variants. Studying rare coding variants has the potential to identify drug targets. We performed an exome-wide association study of smoking phenotypes in up to 749,459 individuals and discovered a protective association in CHRNB2, encoding the ß2 subunit of the α4ß2 nicotine acetylcholine receptor. Rare predicted loss-of-function and likely deleterious missense variants in CHRNB2 in aggregate were associated with a 35% decreased odds for smoking heavily (odds ratio (OR) = 0.65, confidence interval (CI) = 0.56-0.76, P = 1.9 × 10-8). An independent common variant association in the protective direction ( rs2072659 ; OR = 0.96; CI = 0.94-0.98; P = 5.3 × 10-6) was also evident, suggesting an allelic series. Our findings in humans align with decades-old experimental observations in mice that ß2 loss abolishes nicotine-mediated neuronal responses and attenuates nicotine self-administration. Our genetic discovery will inspire future drug designs targeting CHRNB2 in the brain for the treatment of nicotine addiction.

Artificial intelligence-based clustering and characterization of Parkinson's disease trajectories.

Parkinson's disease (PD) is a highly heterogeneous disease both with respect to arising symptoms and its progression over time. This hampers the design of disease modifying trials for PD as treatments which would potentially show efficacy in specific patient subgroups could be considered ineffective in a heterogeneous trial cohort. Establishing clusters of PD patients based on their progression patterns could help to disentangle the exhibited heterogeneity, highlight clinical differences among patient subgroups, and identify the biological pathways and molecular players which underlie the evident differences. Further, stratification of patients into clusters with distinct progression patterns could help to recruit more homogeneous trial cohorts. In the present work, we applied an artificial intelligence-based algorithm to model and cluster longitudinal PD progression trajectories from the Parkinson's Progression Markers Initiative. Using a combination of six clinical outcome scores covering both motor and non-motor symptoms, we were able to identify specific clusters of PD that showed significantly different patterns of PD progression. The inclusion of genetic variants and biomarker data allowed us to associate the established progression clusters with distinct biological mechanisms, such as perturbations in vesicle transport or neuroprotection. Furthermore, we found that patients of identified progression clusters showed significant differences in their responsiveness to symptomatic treatment. Taken together, our work contributes to a better understanding of the heterogeneity encountered when examining and treating patients with PD, and points towards potential biological pathways and genes that could underlie those differences.

The Burden of Progressive Supranuclear Palsy on Patients, Caregivers, and Healthcare Systems by PSP Phenotype: A Cross-Sectional Study.

Progressive supranuclear palsy (PSP) is a rare, relentlessly progressive, ultimately fatal neurodegenerative brain disease. The objective of this study was to assess the burden of PSP on patients, caregivers, and healthcare systems by PSP phenotype. Data were drawn from the Adelphi PSP Disease Specific Programme™, a cross-sectional study of neurologists and people living with PSP in the United States of America, France, Germany, Italy, Spain, and the United Kingdom. All people living with PSP with a reported phenotype were included. PSP phenotype was reported for 242 patients (mean age: 70.2 years, 58% male): PSP-Richardson's syndrome, n = 96; PSP-predominant Parkinsonism, n = 88; PSP-predominant corticobasal syndrome, n = 28; PSP-predominant speech/language disorder, n = 12; PSP-progressive gait freezing, n = 9; PSP-predominant frontal presentation, n = 9. Most patients reported impaired cognitive, motor, behavioral and ocular functionality; 67-100% of patients (across phenotypes) had moderate-to-severe disease at the time of data collection. Post-diagnosis, the majority were provided with a visual and/or mobility aid (55-100%, across phenotypes), and/or required home modification to facilitate their needs (55-78%, across phenotypes). Patients required multiple types of healthcare professionals for disease management (mean 3.6-4.4, across phenotypes), and the majority reported receiving care from at least one caregiver (mean 1.3-1.8, across phenotypes). There is a high burden on patients, caregivers, and healthcare systems across all PSP phenotypes. Although phenotypes manifest different symptoms and are associated with different diagnostic pathways, once diagnosed with PSP, patients typically receive similar care.

A pilot study of the Earable device to measure facial muscle and eye movement tasks among healthy volunteers.

The Earable device is a behind-the-ear wearable originally developed to measure cognitive function. Since Earable measures electroencephalography (EEG), electromyography (EMG), and electrooculography (EOG), it may also have the potential to objectively quantify facial muscle and eye movement activities relevant in the assessment of neuromuscular disorders. As an initial step to developing a digital assessment in neuromuscular disorders, a pilot study was conducted to determine whether the Earable device could be utilized to objectively measure facial muscle and eye movements intended to be representative of Performance Outcome Assessments, (PerfOs) with tasks designed to model clinical PerfOs, referred to as mock-PerfO activities. The specific aims of this study were: To determine whether the Earable raw EMG, EOG, and EEG signals could be processed to extract features describing these waveforms; To determine Earable feature data quality, test re-test reliability, and statistical properties; To determine whether features derived from Earable could be used to determine the difference between various facial muscle and eye movement activities; and, To determine what features and feature types are important for mock-PerfO activity level classification. A total of N = 10 healthy volunteers participated in the study. Each study participant performed 16 mock-PerfOs activities, including talking, chewing, swallowing, eye closure, gazing in different directions, puffing cheeks, chewing an apple, and making various facial expressions. Each activity was repeated four times in the morning and four times at night. A total of 161 summary features were extracted from the EEG, EMG, and EOG bio-sensor data. Feature vectors were used as input to machine learning models to classify the mock-PerfO activities, and model performance was evaluated on a held-out test set. Additionally, a convolutional neural network (CNN) was used to classify low-level representations of the raw bio-sensor data for each task, and model performance was correspondingly evaluated and compared directly to feature classification performance. The model's prediction accuracy on the Earable device's classification ability was quantitatively assessed. Study results indicate that Earable can potentially quantify different aspects of facial and eye movements and may be used to differentiate mock-PerfO activities. Specially, Earable was found to differentiate talking, chewing, and swallowing tasks from other tasks with observed F1 scores >0.9. While EMG features contribute to classification accuracy for all tasks, EOG features are important for classifying gaze tasks. Finally, we found that analysis with summary features outperformed a CNN for activity classification. We believe Earable may be used to measure cranial muscle activity relevant for neuromuscular disorder assessment. Classification performance of mock-PerfO activities with summary features enables a strategy for detecting disease-specific signals relative to controls, as well as the monitoring of intra-subject treatment responses. Further testing is needed to evaluate the Earable device in clinical populations and clinical development settings.

Pharmacoresponse in genetic generalized epilepsy: a genome-wide association study.

Aim: Pharmacoresistance is a major burden in epilepsy treatment. We aimed to identify genetic biomarkers in response to specific antiepileptic drugs (AEDs) in genetic generalized epilepsies (GGE). Materials & methods: We conducted a genome-wide association study (GWAS) of 3.3 million autosomal SNPs in 893 European subjects with GGE - responsive or nonresponsive to lamotrigine, levetiracetam and valproic acid. Results: Our GWAS of AED response revealed suggestive evidence for association at 29 genomic loci (p <10-5) but no significant association reflecting its limited power. The suggestive associations highlight candidate genes that are implicated in epileptogenesis and neurodevelopment. Conclusion: This first GWAS of AED response in GGE provides a comprehensive reference of SNP associations for hypothesis-driven candidate gene analyses in upcoming pharmacogenetic studies.

Testing association of rare genetic variants with resistance to three common antiseizure medications.

OBJECTIVE: Drug resistance is a major concern in the treatment of individuals with epilepsy. No genetic markers for resistance to individual antiseizure medication (ASM) have yet been identified. We aimed to identify the role of rare genetic variants in drug resistance for three common ASMs: levetiracetam (LEV), lamotrigine (LTG), and valproic acid (VPA). METHODS: A cohort of 1622 individuals of European descent with epilepsy was deeply phenotyped and underwent whole exome sequencing (WES), comprising 575 taking LEV, 826 LTG, and 782 VPA. We performed gene- and gene set-based collapsing analyses comparing responders and nonresponders to the three drugs to determine the burden of different categories of rare genetic variants. RESULTS: We observed a marginally significant enrichment of rare missense, truncating, and splice region variants in individuals who were resistant to VPA compared to VPA responders for genes involved in VPA pharmacokinetics. We also found a borderline significant enrichment of truncating and splice region variants in the synaptic vesicle glycoprotein (SV2) gene family in nonresponders compared to responders to LEV. We did not see any significant enrichment using a gene-based approach. SIGNIFICANCE: In our pharmacogenetic study, we identified a slightly increased burden of damaging variants in gene groups related to drug kinetics or targeting in individuals presenting with drug resistance to VPA or LEV. Such variants could thus determine a genetic contribution to drug resistance.

Radiprodil, a NR2B negative allosteric modulator, from bench to bedside in infantile spasm syndrome.

OBJECTIVE: Infantile spasm syndrome (ISS) is an epileptic encephalopathy without established treatment after the failure to standard of care based on steroids and vigabatrin. Converging lines of evidence indicating a role of NR2B subunits of the N-methyl-D-aspartate (NMDA) receptor on the onset of spams in ISS patients, prompted us to test radiprodil, a negative allosteric NR2B modulator in preclinical seizure models and in infants with ISS. METHODS: Radiprodil has been tested in three models, including pentylenetetrazole-induced seizures in rats across different postnatal (PN) ages. Three infants with ISS have been included in a phase 1b escalating repeated dose study. RESULTS: Radiprodil showed the largest protective seizure effects in juvenile rats (maximum at PN12, corresponding to late infancy in humans). Three infants resistant to a combination of vigabatrin and prednisolone received individually titrated doses of radiprodil for up to 34 days. Radiprodil was safe and well tolerated in all three infants, and showed the expected pharmacokinetic profile. One infant became spasm-free and two showed clinical improvement without reaching spasm-freedom. After radiprodil withdrawal, the one infant continued to be spasm-free, while the two others experienced seizure worsening requiring the use of the ketogenic diet and other antiepileptic drugs. INTERPRETATION: Radiprodil showed prominent anti-seizure effect in juvenile animals, consistent with the prevalent expression of NR2B subunit of the NMDA receptor at this age in both rodents and humans. The clinical testing, although preliminary, showed that radiprodil is associated with a good safety and pharmacokinetic profile, and with the potential to control epileptic spasms.

Genomic and clinical predictors of lacosamide response in refractory epilepsies.

OBJECTIVE: Clinical and genetic predictors of response to antiepileptic drugs (AEDs) are largely unknown. We examined predictors of lacosamide response in a real-world clinical setting. METHODS: We tested the association of clinical predictors with treatment response using regression modeling in a cohort of people with refractory epilepsy. Genetic assessment for lacosamide response was conducted via genome-wide association studies and exome studies, comprising 281 candidate genes. RESULTS: Most patients (479/483) were treated with LCM in addition to other AEDs. Our results corroborate previous findings that patients with refractory genetic generalized epilepsy (GGE) may respond to treatment with LCM. No clear clinical predictors were identified. We then compared 73 lacosamide responders, defined as those experiencing greater than 75% seizure reduction or seizure freedom, to 495 nonresponders (<25% seizure reduction). No variants reached the genome-wide significance threshold in our case-control analysis. SIGNIFICANCE: No genetic predictor of lacosamide response was identified. Patients with refractory GGE might benefit from treatment with lacosamide.

Drug Development for Rare Paediatric Epilepsies: Current State and Future Directions.

Rare diseases provide a challenge in the evaluation of new therapies. However, orphan drug development is of increasing interest because of the legislation enabling facilitated support by regulatory agencies through scientific advice, and the protection of the molecules with orphan designation. In the landscape of the rare epilepsies, very few syndromes, namely Dravet syndrome, Lennox-Gastaut syndrome and West syndrome, have been subject to orphan drug development. Despite orphan designations for rare epilepsies having dramatically increased in the past 10 years, the number of approved drugs remains limited and restricted to a handful of epilepsy syndromes. In this paper, we describe the current state of orphan drug development for rare epilepsies. We identified a large number of compounds currently under investigation, but mostly in the same rare epilepsy syndromes as in the past. A rationale for further development in rare epilepsies could be based on the match between the drug mechanisms of action and the knowledge of the causative gene mutation or by evidence from animal models. In case of the absence of strong pathophysiological hypotheses, exploratory/basket clinical studies could be helpful to identify a subpopulation that may benefit from the new drug. We provide some suggestions for future improvements in orphan drug development such as promoting paediatric drug investigations, better evaluation of the incidence and the prevalence, together with the natural history data, and the development of new primary outcomes.

Comparative effectiveness of antiepileptic drugs in juvenile myoclonic epilepsy.

OBJECTIVE: To study the effectiveness and tolerability of antiepileptic drugs (AEDs) commonly used in juvenile myoclonic epilepsy (JME). METHODS: People with JME were identified from a large database of individuals with epilepsy, which includes detailed retrospective information on AED use. We assessed secular changes in AED use and calculated rates of response (12-month seizure freedom) and adverse drug reactions (ADRs) for the five most common AEDs. Retention was modeled with a Cox proportional hazards model. We compared valproate use between males and females. RESULTS: We included 305 people with 688 AED trials of valproate, lamotrigine, levetiracetam, carbamazepine, and topiramate. Valproate and carbamazepine were most often prescribed as the first AED. The response rate to valproate was highest among the five AEDs (42.7%), and significantly higher than response rates for lamotrigine, carbamazepine, and topiramate; the difference to the response rate to levetiracetam (37.1%) was not significant. The rates of ADRs were highest for topiramate (45.5%) and valproate (37.5%). Commonest ADRs included weight change, lethargy, and tremor. In the Cox proportional hazards model, later start year (1.10 [1.08-1.13], P < 0.001) and female sex (1.41 [1.07-1.85], P = 0.02) were associated with shorter trial duration. Valproate was associated with the longest treatment duration; trials with carbamazepine and topiramate were significantly shorter (HR [CI]: 3.29 [2.15-5.02], P < 0.001 and 1.93 [1.31-2.86], P < 0.001). The relative frequency of valproate trials shows a decreasing trend since 2003 while there is an increasing trend for levetiracetam. Fewer females than males received valproate (76.2% vs 92.6%, P = 0.001). SIGNIFICANCE: In people with JME, valproate is an effective AED; levetiracetam emerged as an alternative. Valproate is now contraindicated in women of childbearing potential without special precautions. With appropriate selection and safeguards in place, valproate should remain available as a therapy, including as an alternative for women of childbearing potential whose seizures are resistant to other treatments.

Long-term seizure outcomes in patients with drug resistant epilepsy.

PURPOSE: Despite the availability of a broad range of treatments for epilepsy, a significant proportion of patients have ongoing seizures. This study aims to characterize the drug resistant population and to report long-term outcomes of patients undergoing different types of pharmacological and surgical treatment. METHODS: Adult patients with drug resistant epilepsy (DRE) were identified from a largely retrospective database of 900 consecutive patients with epilepsy, recruited from two reference centers for DRE in Belgium. We report treatment trajectories and long-term seizure outcomes in the different treatment groups. RESULTS: 640 patients had DRE. 249 (38.9%) underwent presurgical assessment, followed by surgical treatment in 197 (30.8%), resulting in seizure freedom in 86 (13.4%). 443 patients (69.2%) were treated only with further AED trials, of which 163 (25.5%) became seizure free. In the 391 patients with ongoing seizures (61.1%), mean age was 43.2 years, mean disease duration 23 years and mean number of AED trials 6.9. 291 (74.4%) had tonic-clonic seizures, and 43 (11.0%) had one or more episodes of status epilepticus. Patients with hippocampal sclerosis were significantly more likely to be seizure free, while patients with malformation of cortical development and those with temporal lobe epilepsy of unknown etiology were more likely to have ongoing seizures. CONCLUSION: Our findings demonstrate that - even with adequate access to surgical treatment and further AED trials - 61.1% of patients with DRE had ongoing seizures. This illustrates that there is a scope for ongoing development of novel treatments for DRE.

Genetic variation in CFH predicts phenytoin-induced maculopapular exanthema in European-descent patients.

OBJECTIVE: To characterize, among European and Han Chinese populations, the genetic predictors of maculopapular exanthema (MPE), a cutaneous adverse drug reaction common to antiepileptic drugs. METHODS: We conducted a case-control genome-wide association study of autosomal genotypes, including Class I and II human leukocyte antigen (HLA) alleles, in 323 cases and 1,321 drug-tolerant controls from epilepsy cohorts of northern European and Han Chinese descent. Results from each cohort were meta-analyzed. RESULTS: We report an association between a rare variant in the complement factor H-related 4 (CFHR4) gene and phenytoin-induced MPE in Europeans (p = 4.5 × 10-11; odds ratio [95% confidence interval] 7 [3.2-16]). This variant is in complete linkage disequilibrium with a missense variant (N1050Y) in the complement factor H (CFH) gene. In addition, our results reinforce the association between HLA-A*31:01 and carbamazepine hypersensitivity. We did not identify significant genetic associations with MPE among Han Chinese patients. CONCLUSIONS: The identification of genetic predictors of MPE in CFHR4 and CFH, members of the complement factor H-related protein family, suggest a new link between regulation of the complement system alternative pathway and phenytoin-induced hypersensitivity in European-ancestral patients.

Comparative effectiveness of antiepileptic drugs in patients with mesial temporal lobe epilepsy with hippocampal sclerosis.

OBJECTIVE: Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) is a common epilepsy syndrome that is often poorly controlled by antiepileptic drug (AED) treatment. Comparative AED effectiveness studies in this condition are lacking. We report retention, efficacy, and tolerability in a cohort of patients with MTLE-HS. METHODS: Clinical data were collected from a European database of patients with epilepsy. We estimated retention, 12-month seizure freedom, and adverse drug reaction (ADR) rates for the 10 most commonly used AEDs in patients with MTLE-HS. RESULTS: Seven hundred sixty-seven patients with a total of 3,249 AED trials were included. The highest 12-month retention rates were observed with carbamazepine (85.9%), valproate (85%), and clobazam (79%). Twelve-month seizure freedom rates varied from 1.2% for gabapentin and vigabatrin to 11% for carbamazepine. Response rates were highest for AEDs that were prescribed as initial treatment and lowest for AEDs that were used in a third or higher instance. ADRs were reported in 47.6% of patients, with the highest rates observed with oxcarbazepine (35.7%), topiramate (30.9%), and pregabalin (27.4%), and the lowest rates with clobazam (6.5%), gabapentin (8.9%), and lamotrigine (16.6%). The most commonly reported ADRs were lethargy and drowsiness, dizziness, vertigo and ataxia, and blurred vision and diplopia. SIGNIFICANCE: Our results did not demonstrate any clear advantage of newer versus older AEDs. Our results provide useful insights into AED retention, efficacy, and ADR rates in patients with MTLE-HS.

Multiphasic presentation of Rasmussen's encephalitis.

Rasmussen's encephalitis is a rare, chronic inflammatory disorder of unknown cause, characterised by drug-resistant focal epilepsy that may rarely present in adolescence or adulthood. We present a case of Rasmussen's encephalitis with prominent recurrent fluctuation in symptoms and well-documented fluctuating changes on MRI, adding to the spectrum of diversity of Rasmussen's encephalitis.

Faulty cardiac repolarization reserve in alternating hemiplegia of childhood broadens the phenotype.

Alternating hemiplegia of childhood is a rare disorder caused by de novo mutations in the ATP1A3 gene, expressed in neurons and cardiomyocytes. As affected individuals may survive into adulthood, we use the term 'alternating hemiplegia'. The disorder is characterized by early-onset, recurrent, often alternating, hemiplegic episodes; seizures and non-paroxysmal neurological features also occur. Dysautonomia may occur during hemiplegia or in isolation. Premature mortality can occur in this patient group and is not fully explained. Preventable cardiorespiratory arrest from underlying cardiac dysrhythmia may be a cause. We analysed ECG recordings of 52 patients with alternating hemiplegia from nine countries: all had whole-exome, whole-genome, or direct Sanger sequencing of ATP1A3. Data on autonomic dysfunction, cardiac symptoms, medication, and family history of cardiac disease or sudden death were collected. All had 12-lead electrocardiogram recordings available for cardiac axis, cardiac interval, repolarization pattern, and J-point analysis. Where available, historical and prolonged single-lead electrocardiogram recordings during electrocardiogram-videotelemetry were analysed. Half the cohort (26/52) had resting 12-lead electrocardiogram abnormalities: 25/26 had repolarization (T wave) abnormalities. These abnormalities were significantly more common in people with alternating hemiplegia than in an age-matched disease control group of 52 people with epilepsy. The average corrected QT interval was significantly shorter in people with alternating hemiplegia than in the disease control group. J wave or J-point changes were seen in six people with alternating hemiplegia. Over half the affected cohort (28/52) had intraventricular conduction delay, or incomplete right bundle branch block, a much higher proportion than in the normal population or disease control cohort (P = 0.0164). Abnormalities in alternating hemiplegia were more common in those ≥16 years old, compared with those <16 (P = 0.0095), even with a specific mutation (p.D801N; P = 0.045). Dynamic, beat-to-beat or electrocardiogram-to-electrocardiogram, changes were noted, suggesting the prevalence of abnormalities was underestimated. Electrocardiogram changes occurred independently of seizures or plegic episodes. Electrocardiogram abnormalities are common in alternating hemiplegia, have characteristics reflecting those of inherited cardiac channelopathies and most likely amount to impaired repolarization reserve. The dynamic electrocardiogram and neurological features point to periodic systemic decompensation in ATP1A3-expressing organs. Cardiac dysfunction may account for some of the unexplained premature mortality of alternating hemiplegia. Systematic cardiac investigation is warranted in alternating hemiplegia of childhood, as cardiac arrhythmic morbidity and mortality are potentially preventable.

Does the primary literature provide support for clinical signs used to distinguish psychogenic nonepileptic seizures from epileptic seizures?

Psychogenic non-epileptic seizures (PNES) represent a diagnostic challenge. When trying to distinguish between PNES and epileptic seizures (ES), clinicians rely on the presence or absence of several clinical signs. The purpose of this review is to establish the extent to which these signs are supported by primary data from the literature. A Medline search was used to identify primary studies that used video-EEG to define the presence or absence of different clinical signs in PNES and ES. The methodological quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool. 34 studies matched the inclusion criteria. A specific sign was considered well supported by the data from the primary literature if we were able to identify at least two controlled studies demonstrating its usefulness and if the data from other studies were supportive. There is good evidence from the literature that long duration, occurrence from apparent sleep with EEG-verified wakefulness, fluctuating course, asynchronous movements, pelvic thrusting, side-to-side head or body movement, closed eyes during the episode, ictal crying, memory recall and absence of postictal confusion are signs that distinguish PNES from ES. Postictal stertorous breathing proved to distinguish convulsive PNES from generalised tonic clonic seizures (GTCS) and should be added to the list of useful clinical signs. The final clinical diagnosis should encompass all available data and should not rely on any single sign alone.