Call for quality epilepsy neuroimaging—An illustrative case of missed epileptic substrate

No. 779

The default mode network is disrupted in Parkinson's disease with visual hallucinations.

BACKGROUND: Visual hallucinations (VH) are one of the most striking nonmotor symptoms in Parkinson's disease (PD), and predict dementia and mortality. Aberrant default mode network (DMN) is associated with other psychoses. Here, we tested the hypothesis that DMN dysfunction contributes to VH in PD. METHODS: Resting state functional data was acquired from individuals with PD with VH (PDVH) and without VH (PDnonVH), matched for levodopa drug equivalent dose, and a healthy control group (HC). Independent component analysis was used to investigate group differences in functional connectivity within the DMN. In addition, we investigated whether the functional changes associated with hallucinations were accompanied by differences in cortical thickness. RESULTS: There were no group differences in cortical thickness but functional coactivation within components of the DMN was significantly lower in both PDVH and PDnonVH groups compared to HC. Functional coactivation within the DMN was found to be greater in PDVH group relative to PDnonVH group. CONCLUSION: Our study demonstrates, for the first time that, within a functionally abnormal DMN in PD, relatively higher "connectivity" is associated with VH. We postulate that aberrant connectivity in a large scale network affects sensory information processing and perception, and contributes to "positive" symptom generation in PD.Contract grant sponsor: Research Grant Council of Hong Kong (General Research Fund awarded to Chua and McAlonan); Infrastructural support: National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust and [Institute of Psychiatry] King's College London (McAlonan); Wellcome Trust; Contract grant number: 088324 (Rowe); National Institute for Health Research Cambridge Biomedical Research Centre (Suckling).This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/hbm.2257

Association between the risk of seizure and COVID-19 vaccinations: A self-controlled case-series study

OBJECTIVE: The risk of seizure following BNT162b2 and CoronaVac vaccinations has been sparsely investigated. This study aimed to evaluate this association. METHOD: Patients who had their first seizure-related hospitalization between February 23, 2021 and January 31, 2022 were identified in Hong Kong. All seizure episodes happening on the day of vaccination (day 0) were excluded since clinicians validated that most of the cases on day 0 were syncopal episodes. Within-individual comparison using a modified self-controlled case series analysis was applied to estimate the incidence rate ratio (IRR) with 95% confidence intervals (CI) of seizure using conditional Poisson regression. RESULTS: We identified 1656 individuals who had their first seizure-related hospitalization (BNT162b2: 426; CoronaVac: 263; unvaccinated: 967) within the observation period. The incidence of seizure was 1.04 (95% CI: 0.80-1.33) and 1.11 (95% CI: 0.80-1.50) per 100,000 doses of BNT162b2 and CoronaVac administered respectively. 16 and 17 individuals received second dose after having first seizure within 28 days after first dose of BNT162b2 and CoronaVac vaccinations, respectively. None had recurrent seizures after the second dose. There was no increased risk during day 1-6 after the first (BNT162b2: IRR=1.39, 95% CI=0.75-2.58; CoronaVac: IRR=1.19, 95% CI=0.50-2.83) and second doses (BNT162b2: IRR=1.36, 95% CI 0.72-2.57; CoronaVac: IRR=0.71, 95% CI=0.22-2.30) of vaccinations. During 7-13, 14-20- and 21-27-days post-vaccination, no association was observed for both vaccines. SIGNIFICANCE: The findings demonstrated no increased risk of seizure following BNT162b2 and CoronaVac vaccinations. Future studies will be warranted to evaluate the risk of seizure following COVID-19 vaccinations in different populations with subsequent doses to ensure the generalizability

Role of machine learning in the management of epilepsy: a systematic review protocol

Introduction Machine learning is a rapidly expanding field and is already incorporated into many aspects of medicine including diagnostics, prognostication and clinical decision-support tools. Epilepsy is a common and disabling neurological disorder, however, management remains challenging in many cases, despite expanding therapeutic options. We present a systematic review protocol to explore the role of machine learning in the management of epilepsy.Methods and analysis This protocol has been drafted with reference to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for Protocols. A literature search will be conducted in databases including MEDLINE, Embase, Scopus and Web of Science. A PRISMA flow chart will be constructed to summarise the study workflow. As the scope of this review is the clinical application of machine learning, the selection of papers will be focused on studies directly related to clinical decision-making in management of epilepsy, specifically the prediction of response to antiseizure medications, development of drug-resistant epilepsy, and epilepsy surgery and neuromodulation outcomes. Data will be extracted following the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. Prediction model Risk Of Bias ASsessment Tool will be used for the quality assessment of the included studies. Syntheses of quantitative data will be presented in narrative format.Ethics and dissemination As this study is a systematic review which does not involve patients or animals, ethics approval is not required. The results of the systematic review will be submitted to peer-review journals for publication and presented in academic conferences.PROSPERO registration number CRD42023442156

Classifications of seizures and epilepsies, where are we? – A brief historical review and update

In March 2017, the International League Against Epilepsy (ILAE) announced their new classifications of seizures and epilepsies. Development of these classification systems led by the ILAE is a long and complicated process. Outsiders may find it difficult to understand the arguments behind. We summarize the major developmental milestones of the ILAE classification schemata. An update of the latest classification is also included. It is hope that this review can serve as an outline in learning the taxonomy in epileptology

Effect of plasmapheresis on serum levels of clobazam, levetiracetam and topiramate

A 27-year-old man with a diagnosis of new onset refractory status epilepticus (NORSE) was treated with five anti-seizure drugs (ASDs) including clobazam, levetiracetam and topiramate. He received plasma exchange (PE) for presumed autoimmune etiology. Serum ASD levels were serially monitored in two sessions. Levels of clobazam, levetiracetam and topiramate were significant reduced by PE. Serum clobazam level dropped down to at least 85% and 75% of the baseline during and after the procedure respectively; levetiracetam dropped down to 83% and 83%; and topiramate dropped to 86% and 79%. The results may imply a theoretical risk of breakthrough seizure during PE due to low ASD levels

Reduction of psycho-spiritual distress of an elderly with advanced congestive heart failure by life review interview in a palliative care day center

Objectives: Major depression is common in patients hospitalized with congestive heart failure and is independently associated with increased re-hospitalization and mortality. Methods: Hereby, we report the treatment for an elderly congestive heart failure patient with frequent emergency department visits having major depression and hopelessness. Results: Treatment outcomes measured showed that depressed scores of psychosocial needs were reduced with life review interview therapy in a palliative care day center. Conclusion: We hypothesize that multidisciplinary team’s approach to treatment was important for this case