ORCID Profile
0000-0003-0870-6094
Current Organisations
King Faisal Specialist Hospital & Research Centre
,
Royal Australasian College of Physicians
,
Princess Alexandra Hospital
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Publisher: Springer Science and Business Media LLC
Date: 24-04-2014
DOI: 10.1007/S00415-014-7329-4
Abstract: The idiomuscular response to direct percussion is rarely tested nowadays because of its uncertain mechanism and significance. While performing neurological examination, we observed a brisk ankle dorsiflexion response on direct muscle percussion of m. tibialis anterior in patients with acute inflammatory demyelinating polyradiculoneuropathy (AIDP). In contrast, in patients with upper motor neuron lesions, an ankle inversion response was seen. In this article we describe our findings in patients with bilateral lower limb weakness. We assessed 73 consecutive patients with bilateral lower limb weakness. A strong dorsiflexion response to percussion of m. tibialis anterior was seen in 11 out of 14 patients with AIDP (sensitivity 78.6%). None of the other patients showed a strong dorsiflexion response (specificity 100%). An inversion response was seen in 11 out of 13 patients with UMN involvement (sensitivity 92.3%). It was also noted in two of 46 patients without proven UMN involvement (specificity 96.7%). The idiomuscular response to percussion of m. tibialis anterior can be useful in the assessment of patients with lower limb weakness of unclear cause.
Publisher: Wiley
Date: 07-2018
DOI: 10.1111/IMJ.13765
Abstract: The present study aims to determine qualitative outcomes of presentations with acute recurrent seizures or status epilepticus to the emergency department of our institution after the introduction of a new seizure management protocol. We performed a retrospective analysis on two cohorts of patients for all presentations to the emergency department of our institution. Presentations were reviewed from January to July pre-protocol introduction and the same period post-protocol. Patients were included if they were treated for acute recurrent seizures or status epilepticus. The protocol applied a strict treatment regimen and used levetiracetam, valproate and phenobarbitone in place of phenytoin. A total of 77 patients was included from the pre-protocol cohort and 72 from the post-protocol group. There was a significant reduction in intensive care unit (ICU) admission (seven patients in cohort 1 and 0 patients in cohort 2) and adverse drug reactions (18 patients in cohort 1 and four patients in cohort 2). There was a trend towards fewer deaths. The introduction of the new seizure management protocol assessed in this study has resulted in fewer ICU admissions, adverse drug reactions and most importantly fewer patient deaths. This is likely attributable to a combination of improved efficacy of the newer antiepileptic agents and a clearly defined protocol directed therapy.
Publisher: Wiley
Date: 15-08-2021
DOI: 10.1111/EPI.17038
Abstract: We aimed to estimate the rate of psychogenic nonepileptic seizures (PNES) among patients presenting to an emergency department with presumed seizures. We also wanted to identify factors that can assist health care professionals in determining whether these events are likely to be epileptic or nonepileptic. We performed two retrospective audits on patients who were treated for seizures in the department of emergency medicine at the Princess Alexandra Hospital, Brisbane, Australia. Exploratory analyses and logistic regressions were conducted to investigate the characteristics of the presentations and the relationships between our variables of interest. In the group of all presentations with presumed seizures over a 3‐month period ( n = 157), a total of 151 presentations (96.2%) presentations were given a primary diagnosis of epileptic seizures. Of these 151 presentations, only 84 (55.6%) presented with epileptic seizures and 40 (26.5%) actually presented with PNES. In the group of patients who presented with prolonged and/or multiple events ( n = 213) over a 1‐year period, 196 (92.0%) were treated as epileptic seizures. Of these 196 presentations, only 85 (43.4%) presented with epileptic seizures and 97 (49.5%) actually presented with PNES. Several factors were identified to help risk stratify between epileptic seizures and PNES: Duration of events and of the postictal phase, number of events, presence of a structural brain pathology, mental health history, lactate levels and presence of tongue bite, incontinence, and/or vomiting. A large proportion of people who present to emergency departments with events resembling epileptic seizures actually have PNES rather than epilepsy—particularly those patients who present with prolonged and/or multiple events. The rate of misdiagnosis was high. Efforts need to be made to recognize patients with psychogenic nonepileptic seizures earlier and diagnose them correctly to avoid unnecessary iatrogenic harm and to provide adequate treatment.
Publisher: MIT Press
Date: 2023
DOI: 10.1162/NETN_A_00295
Abstract: The dynamic integration of sensory and bodily signals is central to adaptive behaviour. Although the anterior cingulate cortex (ACC) and the anterior insular cortex (AIC) play key roles in this process, their context-dependent dynamic interactions remain unclear. Here, we studied the spectral features and interplay of these two brain regions using high-fidelity intracranial-EEG recordings from five patients (ACC: 13 contacts, AIC: 14 contacts) acquired during movie viewing with validation analyses performed on an independent resting intracranial-EEG dataset. ACC and AIC both showed a power peak and positive functional connectivity in the gamma (30–35 Hz) frequency while this power peak was absent in the resting data. We then used a neurobiologically informed computational model investigating dynamic effective connectivity asking how it linked to the movie’s perceptual (visual, audio) features and the viewer’s heart rate variability (HRV). Exteroceptive features related to effective connectivity of ACC highlighting its crucial role in processing ongoing sensory information. AIC connectivity was related to HRV and audio emphasising its core role in dynamically linking sensory and bodily signals. Our findings provide new evidence for complementary, yet dissociable, roles of neural dynamics between the ACC and the AIC in supporting brain-body interactions during an emotional experience.
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 05-2018
DOI: 10.1016/J.YEBEH.2018.02.010
Abstract: Semiology observation and characterization play a major role in the presurgical evaluation of epilepsy. However, the interpretation of patient movements has subjective and intrinsic challenges. In this paper, we develop approaches to attempt to automatically extract and classify semiological patterns from facial expressions. We address limitations of existing computer-based analytical approaches of epilepsy monitoring, where facial movements have largely been ignored. This is an area that has seen limited advances in the literature. Inspired by recent advances in deep learning, we propose two deep learning models, landmark-based and region-based, to quantitatively identify changes in facial semiology in patients with mesial temporal lobe epilepsy (MTLE) from spontaneous expressions during phase I monitoring. A dataset has been collected from the Mater Advanced Epilepsy Unit (Brisbane, Australia) and is used to evaluate our proposed approach. Our experiments show that a landmark-based approach achieves promising results in analyzing facial semiology, where movements can be effectively marked and tracked when there is a frontal face on visualization. However, the region-based counterpart with spatiotemporal features achieves more accurate results when confronted with extreme head positions. A multifold cross-validation of the region-based approach exhibited an average test accuracy of 95.19% and an average AUC of 0.98 of the ROC curve. Conversely, a leave-one-subject-out cross-validation scheme for the same approach reveals a reduction in accuracy for the model as it is affected by data limitations and achieves an average test accuracy of 50.85%. Overall, the proposed deep learning models have shown promise in quantifying ictal facial movements in patients with MTLE. In turn, this may serve to enhance the automated presurgical epilepsy evaluation by allowing for standardization, mitigating bias, and assessing key features. The computer-aided diagnosis may help to support clinical decision-making and prevent erroneous localization and surgery.
Publisher: Elsevier BV
Date: 06-2013
Publisher: BMJ
Date: 17-06-2011
Publisher: Wiley
Date: 10-2018
Abstract: We report a case of medically refractory anti‐GAD encephalitis which was treated with deep brain stimulation (DBS) after seizure termination was achieved using cortical stimulation during stereo‐electroencephalography (SEEG) evaluation. The patient underwent bilateral SEEG implantation and cortical stimulation. Upon stimulation, mimicking the intrinsic seizures (at 1 Hz), it was possible to induce seizures with typical semiology, on multiple attempts. Stimulation during these seizures with high frequency (50 Hz) resulted in complete termination of the seizure. DBS was inserted after the SEEG evaluation, targeting the bilateral anterior nucleus of the thalamus. There was a sustained reduction in seizure frequency and severity 12 months post insertion. There were also improvements in quality of life. To the best of our knowledge, this is the only case reported in which DBS was successfully used to treat refractory epilepsy in a patient with seizures that were proven to be responsive to electrical stimulation during SEEG recording.
Publisher: Elsevier BV
Date: 09-2019
DOI: 10.1016/J.CLINPH.2019.05.033
Abstract: Paroxysmal nocturnal movements in epilepsy are a recognised phenomenon, however, the mechanisms that produce them and the effect of the underlying epilepsy still remains elusive. In this study, 10 patients were studied to define the cerebral networks corresponding to these movements and explore how epileptiform activity modulated them. We compared the change in power of the 25-250 Hz frequency band using event-related synchronization of all stereo-EEG electrodes implanted, during a baseline segment, during nocturnal movements and seizures. The underlying network activated during these paroxysmal movements comprised the insula, anterior cingulate, premotor areas and orbitofrontal regions. Three groups emerged, (1) complete overlap, (2) no overlap and (3) partial overlap of ERS changes of the epileptogenic zone within the proposed network and correlation of semiology between nocturnal movements and seizures. We conclude that nocturnal movements are due to a complex interplay within this physiological network of defined anatomical regions. Epileptic activity had significant impact on nocturnal movements but was not required for generation. Where the semiology of the first clinical sign of a seizure consistently matches a patient's nocturnal movements, we suggest that the underlying epileptogenic zone is potentially located within this defined network.
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 03-2020
DOI: 10.1016/J.JNEUMETH.2019.108559
Abstract: Cortico-Cortical Evoked Potentials (CCEPs) are a novel low frequency stimulation method used for brain mapping during intracranial epilepsy investigations. Only a handful of metrics have been applied to CCEP data to infer connectivity, and no comparison as to which is best has been performed. We implement a novel method which involved superimposing synthetic cortical responses onto stereoelectroencephalographic (SEEG) data, and use this to compare several metric's ability to detect the simulated patterns. In this we compare two commonly employed metrics currently used in CCEP analysis against eight time series similarity metrics (TSSMs), which have been widely used in machine learning and pattern matching applications. Root Mean Square (RMS), a metric commonly employed in CCEP analysis, was sensitive to a wide variety of response patterns, but insensitive to simulated epileptiform patterns. Autoregressive (AR) coefficients calculated by Burg's method were also sensitive to a wide range of patterns, but were extremely sensitive to epileptiform patterns. Other metrics which employed elastic warping techniques were less sensitive to the simulated response patterns. Our study is the first to compare CCEP connectivity metrics against one-another. Our results found that RMS, which has been used in many CCEP studies previously, was the most sensitive metric across a wide range of patterns. Our novel method showed that RMS is a robust and sensitive measure, validating much of the findings of the SEEG-CCEP literature to date. Autoregressive coefficients may also be a useful metric to investigate epileptic networks.
Publisher: Wiley
Date: 09-10-2017
DOI: 10.1111/EPI.13907
Abstract: Epilepsy being one of the most prevalent neurological disorders, affecting approximately 50 million people worldwide, and with almost 30-40% of patients experiencing partial epilepsy being nonresponsive to medication, epilepsy surgery is widely accepted as an effective therapeutic option. Presurgical evaluation has advanced significantly using noninvasive techniques based on video monitoring, neuroimaging, and electrophysiological and neuropsychological tests however, certain clinical settings call for invasive intracranial recordings such as stereoelectroencephalography (SEEG), aiming to accurately map the eloquent brain networks involved during a seizure. Most of the current presurgical evaluation procedures focus on semiautomatic techniques, where surgery diagnosis relies immensely on neurologists' experience and their time-consuming subjective interpretation of semiology or the manifestations of epilepsy and their correlation with the brain's electrical activity. Because surgery misdiagnosis reaches a rate of 30%, and more than one-third of all epilepsies are poorly understood, there is an evident keen interest in improving diagnostic precision using computer-based methodologies that in the past few years have shown near-human performance. Among them, deep learning has excelled in many biological and medical applications, but has advanced insufficiently in epilepsy evaluation and automated understanding of neural bases of semiology. In this paper, we systematically review the automatic applications in epilepsy for human motion analysis, brain electrical activity, and the anatomoelectroclinical correlation to attribute anatomical localization of the epileptogenic network to distinctive epilepsy patterns. Notably, recent advances in deep learning techniques will be investigated in the contexts of epilepsy to address the challenges exhibited by traditional machine learning techniques. Finally, we discuss and propose future research on epilepsy surgery assessment that can jointly learn across visually observed semiologic patterns and recorded brain electrical activity.
Publisher: Elsevier BV
Date: 05-2019
DOI: 10.1016/J.JNEUROIM.2019.02.005
Abstract: Chronic autoimmune epilepsy is an increasingly recognised entity however its clinical and electrographic features remain poorly understood. We present a case undergoing diagnostic Stereo-electroencephalography implantation that was found to have a multifocal perisylvian epilepsy with unique electrographic features and is now seizure free with immunotherapy. The patient had antibody negative refractory perisylvian epilepsy and underwent implantation of the perisylvian-temporal networks. Immunomodulatory treatment was administered during SEEG. SEEG demonstrated a multifocal perisylvian epilepsy with strong involvement of the posterior insula. There was almost continuous spiking seen interictally from multiple foci within the right hemisphere and independent seizures were generated from 5 locations. After treatment with intravenous methylprednisone and immunoglobulin during SEEG, spiking and seizures terminated while still off anti-seizure medications. The patient remains seizure free on immunotherapy. This case highlights the importance of considering autoimmunity in the differential diagnosis of refractory epilepsy, especially perisylvian epilepsy. It also highlights the need to define a clinical phenotype associated with autoantibodies in epilepsy, as there are likely many cases who are not positive for one of the commercially available tests. This case also provides insights into the possible features of an electroclinical syndrome associated with autoimmunity.
Publisher: Elsevier BV
Date: 04-2019
DOI: 10.1016/J.SEIZURE.2019.03.008
Abstract: Recurrent seizures and status epilepticus after medication reduction for inpatient Video Electroencephalograph (VEEG) monitoring is a well-known complication of this investigation. In the literature this is reported to occur at a rate of approximately 3-7%. We review the use of short burst Clobazam dosing on discharge from the Epilepsy monitoring unit (EMU) to determine if this might reduce rates of representation with seizures. We performed a retrospective review of all cases admitted to the EMU. Their medication reduction, number of seizures, seizure severity and demographics were collected. Representations to hospital were considered if they occurred within 14 days of discharge from the unit. 264 cases were included, and 146 patients received 5 days of Clobazam 10 mg PO BD upon discharge after VEEG and 118 did not. There were significantly fewer patients re-presenting to hospital for seizures in the 14 days following discharge in those who were administered short-burst Clobazam compared to those who were not (0% and 4.23% respectively). There was also a trend towards fewer re-admissions for non-seizure indications including mental health issues or non-epileptic seizures and AED side effects. There were no definite adverse reactions to Clobazam recorded. Short burst Clobazam appears to be a safe and effective means to reduce representation with seizures after medication reduction during VEEG recording. This obviously benefits patients but it may also be a cost-effective means to reduce unnecessary health expenditure.
Publisher: Elsevier BV
Date: 05-2020
Publisher: Wiley
Date: 07-2013
DOI: 10.1111/IMJ.12168
Abstract: Seizures are a commonly encountered medical problem. Seizure protocols have been shown to be effective by avoiding inappropriate over- and undertreatment, but are not presently utilised in many centres in Australia. We outline a stepwise approach to effective seizure management based on timely investigation and escalating treatment with an appropriate choice of medications. Because large-scale clinical trials are lacking, we base our approach on the underlying seizure pathophysiology and the pharmacological properties of the available drugs. Early management consists of finding and correcting possible reversible causes and ensuring patient safety. With ongoing seizure length, spontaneous resolution becomes unlikely, necessitating administration of anti-epileptic drugs. Benzodiazepines are the agents of first choice, with a preference of short-acting drugs. With ongoing seizures, other agents (i.e. valproate, levetiracetam, phenobarbitone, phenytoin) are utilised. Refractory status epilepticus requires aggressive treatment in an intensive care setting. Novel approaches and agents, including ketamine, topiramate, lacosamide, pregabalin and intravenous immunoglobulins, are discussed. We provide our own recently developed hospital protocol as a guide. This protocol relies on a time-based four-step escalating approach to seizure management, ranging from supportive management of the initial simple seizure to the use of multiple agents for established status epilepticus.
Publisher: Elsevier BV
Date: 10-2018
Publisher: BMJ
Date: 12-2021
DOI: 10.1136/BMJOPEN-2021-050070
Abstract: Epilepsy places a large burden on health systems, with hospitalisations for seizures alone occurring more frequently than those related to diabetes. However, the cost of epilepsy to the Australian health system is not well understood. The primary aim of this study is to quantify the health service use and cost of epilepsy in Queensland, Australia. Secondary aims are to identify differences in health service use and cost across population and disease subgroups, and to explore the associations between health service use and common comorbidities. This project will use data linkage to identify the health service utilisation and costs associated with epilepsy. A base cohort of patients will be identified from the Queensland Hospital Admitted Patient Data Collection. We will select all patients admitted between 2014 and 2018 with a diagnosis classification related to epilepsy. Two comparison cohorts will also be identified. Retrospective hospital admissions data will be linked with emergency department presentations, clinical costing data, specialist outpatient and allied health occasions of service data and mortality data. The level of health service use in Queensland, and costs associated with this, will be quantified using descriptive statistics. Difference in health service costs between groups will be explored using logistic regression. Linear regression will be used to model the associations of interest. The analysis will adjust for confounders including age, sex, comorbidities, indigenous status, and remoteness. Ethical approval has been obtained through the QUT University Human Research Ethics Committee (1900000333). Permission to waive consent has been granted under the Public Health Act 2005, with approval provided by all relevant data custodians. Findings of the proposed research will be communicated through presentations at national and international conferences, presentations to key stakeholders and decision-makers, and publications in international peer-reviewed journals.
Publisher: Wiley
Date: 04-2020
DOI: 10.1111/IMJ.14801
Publisher: IEEE
Date: 07-2018
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.SEIZURE.2018.12.015
Abstract: The clinical utility of EEG in cases of NMDA encephalitis is broad with many findings indicating not just epileptiform activity but also encephalopathy and potentially providing insights into pathophysiologic mechanisms of disease. We aimed to determine the frequency of different abnormalities described on EEG and their association with outcome in patients affected by NMDARE through a systematic review of all cases published. A systematic literature review of PubMed and Embase of all published cases of anti-NMDA receptor encephalitis with EEG results, was performed from inception to January 2018. A total of 446 cases of anti-NMDA receptor encephalitis with reported EEG findings were identified. 373 EEGs were abnormal, and this strongly correlated with ICU admission and time to recovery (p = 0.014 and 0.04 respectively). ICU admission and recovery were also correlated with delta range abnormalities including extreme delta brush (p = 0.007 and 0.03). Electrographic seizures correlated strongly with clinical seizures (p < 0.0001), however only 39 cases had EEG seizures captured, while there were 294 cases with clinical seizures. EEG is useful in the clinical management and prognostication of cases on NMDA encephalitis. This is particularly true of certain findings which portend a higher likelihood of ICU admission or poorer outcome and this may assist in the decision to pursue more aggressive treatment options.
Publisher: Wiley
Date: 12-2017
Abstract: Aims . We report a case series of 10 patients with chronic medically refractory antibody‐positive autoimmune epilepsy and assess their common clinical features. Immune‐mediated seizures are most commonly reported in the context of encephalitis or encephalopathy, with few reports focusing on lone, chronic epilepsy in the outpatient setting. Our aim was to define the potential diagnostic clues that might be present in these cases, leading to consideration of an autoimmune cause of the epilepsy. Methods . We performed a retrospective review of all patients presenting to the outpatient department of our unit who underwent autoimmune screening. All patients with chronic epilepsy and a positive result for an antibody known to be associated with epilepsy were included. Results . Sixty‐three patients underwent testing. Thirteen returned a positive result, however, only 10 of these were patients which chronic epilepsy who did not present with an acute illness. Common features in these cases included: perisylvian semiology, EEG abnormalities in the mid temporal region, normal or non‐specific MRI findings, depression, and head injury. Conclusion . In cases of medically refractory, lesion‐negative epilepsy, with predominantly perisylvian semiology, clinicians should have a high level of suspicion for the diagnosis of autoimmune aetiologies and a low threshold to perform autoantibody screening. This is especially true if there are atypical electrographic findings, a previous history of head injury, or co‐morbid depression.
Publisher: Elsevier BV
Date: 08-2019
Publisher: Elsevier BV
Date: 05-2015
DOI: 10.1016/J.CLINPH.2014.07.035
Abstract: The analysis of hippoc al local field potentials in humans during the encoding of episodic memories has revealed that a robust increase in gamma band oscillatory power predicts successful item encoding, termed the gamma band subsequent memory effect (SME). No previous investigation has looked for differences in this pattern between epileptogenic and non-epileptogenic sources we sought to examine the gamma band effect in seizure patients to address this question. We recorded hippoc al activity in nine patients who underwent stereoelectroencephalography for seizure localization and also performed the Free Recall task, a standard test of episodic memory. We compared gamma band oscillatory activity between 15 electrodes localized to epileptogenic hippoc i and 24 electrodes in non-epileptogenic hippoc i. The epileptogenic hippoc i exhibited a significant decrease in gamma band power during successful item encoding, whereas the non-epileptogenic group exhibited the expected positive gamma band effect (t(37)=4.69, p<0.0001). The typical gamma band effect is reversed for epileptogenic hippoc i. This is the first study to demonstrate a difference for epileptogenic hippoc i for an important oscillatory pattern that normally predicts successful item encoding. Patients with epilepsy suffer selective impairment of episodic memory ability, so our findings are especially relevant for clinicians and memory researchers alike.
Publisher: Wiley
Date: 16-11-2017
DOI: 10.1111/EPI.13939
Abstract: This review aims to highlight key considerations when performing cortico-cortical evoked potentials (CCEPs) using stereo-electroencephalography (SEEG) for network mapping and show its clinical applicability to presurgical evaluations. The parameters for performing stimulation and safety aspects have been investigated in electrocorticography (ECoG) and deep brain stimulation (DBS), but not as extensively in SEEG. A review of current literature was performed, with an attempt made to emphasize practical insights from all modalities of intracranial stimulation. This paper reviews physical stimulation parameters, highlights safety limits, and considers the influence of changing common stimulation parameters. These factors are put into the context of CCEPs in SEEG. Given the paucity of direct research in this area, studies utilizing low frequency stimulation, DBS, and ECoG are incorporated along with the fundamental principles of electrical engineering. In addition, postprocessing considerations are reviewed, including electrode localization, application of digital filters, baseline selection, application of connectivity metrics, and higher order network analysis. The aim is to guide CCEP stimulation as well as to provide an understanding of the underlying principles of this technique. At present, there are few articles detailing the design of low-frequency stimulation paradigms, especially in the setting of SEEG. Providing a review of the fundamentals and postprocessing considerations when performing CCEPs in SEEG will increase the accessibility of this technique.
Publisher: Elsevier BV
Date: 09-2019
DOI: 10.1016/J.JNEUMETH.2019.108347
Abstract: The successful delineation of the epileptogenic zone in epilepsy monitoring is crucial for achieving seizure freedom after epilepsy surgery. We aim to improve epileptogenic zone localization by utilizing a computer-assisted tool for the automated grading of the seizure activity recorded in various locations for 20 patients undergoing stereo electroencephalography. Their epileptic seizures were processed to extract two potential biomarkers. The concentration of these biomarkers from within each patient's implantation were then graded to identify their epileptogenic zone and were compared to the clinical assessment. Our technique was capable of ranking the clinically defined epileptogenic zone with high accuracy, above 95%, with a true to false positive ratio of 1:1.52, and was effective with both temporal and extra-temporal onset epilepsies. We compared our method to two other groups performing localization using similar biomarkers. Our classification metrics, sensitivity and precision together were comparable to both groups and our overall accuracy from a larger population was also higher then both. Our method is highly accurate, automated and non-parametric providing clinicians another tool that can be used to help identify the epileptogenic zone in patients undergoing the stereo electroencephalography procedure for epilepsy monitoring.
Publisher: Wiley
Date: 21-07-2018
DOI: 10.1111/ENE.13721
Abstract: Antibodies to glycine receptors (GlyR‐Abs) were first defined in progressive encephalopathy with rigidity and myoclonus ( PERM ) but were subsequently identified in other clinical presentations. Our aim was to assess the clinical associations of all patients identified with GlyR‐Abs in Queensland, Australia, between April 2014 and May 2017 and to compare these to cases reported in the literature. A literature review identified the clinical features of all published GlyR‐Ab‐positive cases through online databases. A case series was undertaken via collection of clinical information from all patients diagnosed or known to immunology, pathology or neurological services in Queensland during the study period of 3 years. In all, 187 GlyR‐Ab‐positive cases were identified in the literature. The majority (47.6%) had PERM , 22.4% had epilepsy, but the remaining 30% included mixed phenotypes consisting of cerebellar ataxia, movement disorders, demyelination and encephalitis/cognitive dysfunction. By contrast, in our series of 14 cases, eight had clinical presentations consistent with seizures and epilepsy and only three cases had classical features of PERM . There was one case each of global fatiguable weakness with sustained clonus, laryngeal dystonia and movement disorder with hemiballismus and tics. The rate of response to immune therapy was similar in all groups. Antibodies to glycine receptors are linked to a spectrum of neurological disease. The results of the literature review and our case series suggest a greater relationship between GlyR‐Abs and epilepsy than previously reported.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2019
Publisher: American Chemical Society (ACS)
Date: 20-11-2013
DOI: 10.1021/EF401541B
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.SEIZURE.2018.12.017
Abstract: The recent explosion of artificial intelligence techniques in video analytics has highlighted the clinical relevance in capturing and quantifying semiology during epileptic seizures however, we lack an automated anomaly identification system for aberrant behaviors. In this paper, we describe a novel system that is trained with known clinical manifestations from patients with mesial temporal and extra-temporal lobe epilepsy and presents aberrant semiology to physicians. We propose a simple end-to-end-architecture based on convolutional and recurrent neural networks to extract spatiotemporal representations and to create motion capture libraries from 119 seizures of 28 patients. The cosine similarity distance between a test representation and the libraries from five aberrant seizures separate to the main dataset is subsequently used to identify test seizures with unusual patterns that do not conform to known behavior. Cross-validation evaluations are performed to validate the quantification of motion features and to demonstrate the robustness of the motion capture libraries for identifying epilepsy types. The system to identify unusual epileptic seizures successfully detects out of the five seizures categorized as aberrant cases. The proposed approach is capable of modeling clinical manifestations of known behaviors in natural clinical settings, and effectively identify aberrant seizures using a simple strategy based on motion capture libraries of spatiotemporal representations and similarities between hidden states. Detecting anomalies is essential to alert clinicians to the occurrence of unusual events, and we show how this can be achieved using pre-learned database of semiology stored in health records.
Location: Saudi Arabia
No related grants have been discovered for Sasha Dionisio.