Seizure Assessment and Forecasting With Efficient Rapid-EEG: A Retrospective Multicenter Comparative Effectiveness Study.

BACKGROUND AND OBJECTIVES: Approximately 30% of critically ill patients have seizures, and more than half of these seizures do not have an overt clinical correlate. EEG is needed to avoid missing seizures and prevent overtreatment with antiseizure medications. Conventional-EEG (cEEG) resources are logistically constrained and unable to meet their growing demand for seizure detection even in highly developed centers. Brief EEG screening with the validated 2HELPS2B algorithm was proposed as a method to triage cEEG resources, but it is hampered by cEEG requirements, primarily EEG technologists. Seizure risk-stratification using reduced time-to-application rapid response-EEG (rrEEG) systems (∼5 minutes) could be a solution. We assessed the noninferiority of the 2HELPS2B score on a 1-hour rrEEG compared to cEEG. METHODS: A multicenter retrospective EEG diagnostic accuracy study was conducted from October 1, 2021, to July 31, 2022. Chart and EEG review performed with consecutive sampling at 4 tertiary care centers, included records of patients ≥18 years old, from January 1, 2018, to June 20, 2022. Monte Carlo simulation power analysis yielded n = 500 rrEEG; for secondary outcomes n = 500 cEEG and propensity-score covariate matching was planned. Primary outcome, noninferiority of rrEEG for seizure risk prediction, was assessed per area under the receiver operator characteristic curve (AUC). Noninferiority margin (0.05) was based on the 2HELPS2B validation study. RESULTS: A total of 240 rrEEG with follow-on cEEG were obtained. Median age was 64 (interquartile range 22); 42% were female. 2HELPS2B on a 1-hour rrEEG met noninferiority to cEEG (AUC 0.85, 95% CI 0.78-0.90, p = 0.001). Secondary endpoints of comparison with a matched contemporaneous cEEG showed no significant difference in AUC (0.89, 95% CI 0.83-0.94, p = 0.31); in false negative rate for the 2HELPS2B = 0 group (p = 1.0) rrEEG (0.021, 95% CI 0-0.062), cEEG (0.016, 95% CI 0-0.048); nor in survival analyses. DISCUSSION: 2HELPS2B on 1-hour rrEEG is noninferior to cEEG for seizure prediction. Patients with low-risk (2HELPS2B = 0) may be able to forgo prolonged cEEG, allowing for increased monitoring of at-risk patients. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that rrEEG is noninferior to cEEG in calculating the 2HELPS2B score to predict seizure risk.

Implications of Large Language Models for Quality and Efficiency of Neurologic Care: Emerging Issues in Neurology.

Large language models (LLMs) are advanced artificial intelligence (AI) systems that excel in recognizing and generating human-like language, possibly serving as valuable tools for neurology-related information tasks. Although LLMs have shown remarkable potential in various areas, their performance in the dynamic environment of daily clinical practice remains uncertain. This article outlines multiple limitations and challenges of using LLMs in clinical settings that need to be addressed, including limited clinical reasoning, variable reliability and accuracy, reproducibility bias, self-serving bias, sponsorship bias, and potential for exacerbating health care disparities. These challenges are further compounded by practical business considerations and infrastructure requirements, including associated costs. To overcome these hurdles and harness the potential of LLMs effectively, this article includes considerations for health care organizations, researchers, and neurologists contemplating the use of LLMs in clinical practice. It is essential for health care organizations to cultivate a culture that welcomes AI solutions and aligns them seamlessly with health care operations. Clear objectives and business plans should guide the selection of AI solutions, ensuring they meet organizational needs and budget considerations. Engaging both clinical and nonclinical stakeholders can help secure necessary resources, foster trust, and ensure the long-term sustainability of AI implementations. Testing, validation, training, and ongoing monitoring are pivotal for successful integration. For neurologists, safeguarding patient data privacy is paramount. Seeking guidance from institutional information technology resources for informed, compliant decisions, and remaining vigilant against biases in LLM outputs are essential practices in responsible and unbiased utilization of AI tools. In research, obtaining institutional review board approval is crucial when dealing with patient data, even if deidentified, to ensure ethical use. Compliance with established guidelines like SPIRIT-AI, MI-CLAIM, and CONSORT-AI is necessary to maintain consistency and mitigate biases in AI research. In summary, the integration of LLMs into clinical neurology offers immense promise while presenting formidable challenges. Awareness of these considerations is vital for harnessing the potential of AI in neurologic care effectively and enhancing patient care quality and safety. The article serves as a guide for health care organizations, researchers, and neurologists navigating this transformative landscape.

The online educational tool "Roadmap to EEGs" significantly improved trainee performance in recognizing EEG patterns.

OBJECTIVE: We created a framework to assess the competency-based EEG curriculum, outlined by the International League Against Epilepsy (ILAE) through a video-based online educational resource ("Roadmap to EEGs") and assessed its effectiveness and feasibility in improving trainees' knowledge. METHODS: Ten video-based e-learning modules addressed seven key topics in EEG and epileptology (normal EEG, normal variants, EEG artifacts, interictal epileptiform discharges (IED), focal seizures, idiopathic generalized epilepsy (IGE), and developmental and epileptic encephalopathies (DEE)). We posted the educational videos on YouTube for free access. Pre- and post-tests, each comprising 20 multiple-choice questions, were distributed to institution leadership and advertised on social media platforms to reach a global audience. The tests were administered online to assess the participants' knowledge. Pre- and post-test questions showed different EEG samples to avoid memorization and immediate recall. After completing the post-test, participants were asked to respond to 7 additional questions assessing their confidence levels and recommendations for improvement. RESULTS: A total of 52 complete and matched pre- and post-test responses were collected. The probability of a correct response was 73% before teaching (95% CI: 70%-77%) and 81% after teaching (95% CI: 78%-84%). The odds of a correct response increased significantly by 59% (95% CI: 28%-98%, p < .001). For participants having >4 weeks of EEG training, the probability of a correct response was 76% (95% CI: .72-.79) and 81% after teaching (95% CI: .78-.84). The odds of answering correctly increased by 44% (95% CI: 15%-80%, p = .001). Participants felt completely confident in independently interpreting and identifying EEG findings after completing the teaching modules (17.1% before vs. 37.8% after, p-value < .0001). 86.5% of participants expressed a high likelihood of recommending the module to other trainees. SIGNIFICANCE: The video-based online educational resource allows participants to acquire foundational knowledge in EEG/epilepsy, and participants to review previously learned EEG/epilepsy information.

Improving Neurology Clinical Care With Natural Language Processing Tools.

The integration of natural language processing (NLP) tools into neurology workflows has the potential to significantly enhance clinical care. However, it is important to address the limitations and risks associated with integrating this new technology. Recent advances in transformer-based NLP algorithms (e.g., GPT, BERT) could augment neurology clinical care by summarizing patient health information, suggesting care options, and assisting research involving large datasets. However, these NLP platforms have potential risks including fabricated facts and data security and substantial barriers for implementation. Although these risks and barriers need to be considered, the benefits for providers, patients, and communities are substantial. With these systems achieving greater functionality and the pace of medical need increasing, integrating these tools into clinical care may prove not only beneficial but necessary. Further investigation is needed to design implementation strategies, mitigate risks, and overcome barriers.

Evaluating adult care in Dravet syndrome upon transferring from pediatrics in the U.S.: A caregiver-based survey study.

Patients with Dravet syndrome (DS) and their caregivers must navigate a complex process upon transitioning from pediatric to adult healthcare settings. Our study examines the state of care transfer of patients with DS in the U.S. A 34-question e-survey evaluating patient demographics, clinical features, and details of the transfer process was sent to caregivers of adults with DS (≥18 years old) residing in the U.S. through the Dravet Syndrome Foundation. Forty-six responses were included in the analysis. Twenty-nine patients (n = 29/46) did not undergo transfer of care - mostly because they were still followed by pediatric neurologists/epileptologists (71%), whereas 17 (n = 17/46) underwent transfer of care. Adult neurology/epilepsy teams providing care never/rarely included a multidisciplinary team (71%), addressed patients' self-advocacy capabilities (53%), or legal guardianship/end-of-life decision-making (59%). Adult neurology/epilepsy teams were considered very much attentive/available (63%), attentive and accommodating to patients with behavioral/cognitive issues (50%), and knowledgeable about caring for patients with intellectual disability/behavioral issues (63%), collaborating with caregivers (75%), and DS - especially in adults (50%). Most caregivers (62.5%) rated the transfer process as good, very good, or excellent. Patients with DS and their caregivers would benefit from more accessible transition programs, which would be ideally equipped to deliver care tailored to these patients' needs.

EEG-based grading of immune effector cell-associated neurotoxicity syndrome.

CAR-T cell therapy is an effective cancer therapy for multiple refractory/relapsed hematologic malignancies but is associated with substantial toxicity, including Immune Effector Cell Associated Neurotoxicity Syndrome (ICANS). Improved detection and assessment of ICANS could improve management and allow greater utilization of CAR-T cell therapy, however, an objective, specific biomarker has not been identified. We hypothesized that the severity of ICANS can be quantified based on patterns of abnormal brain activity seen in electroencephalography (EEG) signals. We conducted a retrospective observational study of 120 CAR-T cell therapy patients who had received EEG monitoring. We determined a daily ICANS grade for each patient through chart review. We used visually assessed EEG features and machine learning techniques to develop the Visual EEG-Immune Effector Cell Associated Neurotoxicity Syndrome (VE-ICANS) score and assessed the association between VE-ICANS and ICANS. We also used it to determine the significance and relative importance of the EEG features. We developed the Visual EEG-ICANS (VE-ICANS) grading scale, a grading scale with a physiological basis that has a strong correlation to ICANS severity (R = 0.58 [0.47-0.66]) and excellent discrimination measured via area under the receiver operator curve (AUC = 0.91 for ICANS ≥ 2). This scale shows promise as a biomarker for ICANS which could help to improve clinical care through greater accuracy in assessing ICANS severity.

Using CT Perfusion in the Interictal State.

SUMMARY: Periodic discharges seen in patients undergoing continuous EEG pose a challenge to physicians in falling into the interictal-ictal continuum and need for appropriate diagnostic and management approach. The authors herein present an 83-year-old male patient with an acute subdural hematoma who developed intermittent right upper and lower extremity weakness with change in mental status post craniotomy and hematoma evacuation. The patient was intubated and sedated with midazolam and propofol and placed on anti-seizure medications to control seizures. He was placed on continuous EEG monitoring and later developed lateralized periodic discharges. To guide treatment, a computed tomography perfusion study of the brain was performed. The results were consistent with an ictal phenomenon because of the presence of left hemispheric hyperemia. This increased cerebral blood volume and blood flow was used as a diagnostic tool to warrant more aggressive antiepileptic regimen. The patient was then started on an additional anti-seizure medication and dosages were further optimized. This led to an improvement in the patient's EEG and clinical state. There are numerous studies that show lateralized periodic discharges are seen as examples of subclinical status epilepticus and demonstrate hypermetabolism and hyperemia on positron emission tomography and single-photon emission computed tomography scans. When such imaging modalities are unavailable, cortical hyperperfusion on a computed tomography perfusion study might be a valid predictor of ongoing, subclinical, ictal activity and may be used as a complementary diagnostic tool to EEG to guide treatment.

Unusual Movement Disorders and Atypical Magnetic Resonance Imaging (MRI) Findings in Patients with West Nile Encephalitis: Case Reports of 2 Patients with Evidence of Clinical and Imaging Resolution with IVIG.

BACKGROUND West Nile virus (WNv) is the leading cause of epidemic arbovirus encephalitis in the continental United States. Movement disorders (MDs) have been reported in 20% to 40% of patients with WNv and about 37% of patients with WNv encephalitis have changes on magnetic resonance imaging (MRI). We report 2 unusual cases of neuroinvasive WNv in patients with unusual MDs and unreported MRI findings. CASE REPORT In the first case, a 34-year-old man presented with a 1-week history of disinhibition, agitation, opsoclonus-myoclonus and ataxia syndrome (OMAS), tremor, and facial agnosia. Evaluation of his cerebrospinal fluid (CSF) revealed elevated immunoglobulin (Ig)M against WNv, a high level of protein (98 mg/dL), and an elevated white blood cell (WBC) count (134, 37% lymphocytes). An MRI of the brain showed an area of diffusion restriction in the splenium of the corpus callosum. The patient's MRI findings and OMA improved significantly after 2 treatments with i.v. IG (IVIG). In the second case, a 57-year-old woman presented with fever, headaches, psychosis, and ataxia; she was subsequently intubated for airway protection. Analysis of her CSF showed elevated IgM against WNv, a high level of protein (79 mg/dL), and elevated WBC count (106, 90% lymphocytes). One week after the onset of symptoms, the patient experienced facial dyskinesia. Later, she developed proximal bilateral lower extremity weakness. An MRI of her lumbar spine showed evidence of myeloradiculitis with contrast enhancement of the conus medullaris and ventral nerve roots. After a single treatment with IVIG, she had partial improvement in weakness. CONCLUSIONS MDs and changes on MRI have been reported in patients with neuroinvasive WNv disease. Our patient with OMAS also had transient splenial diffusion restriction on imaging, which, to the best of our knowledge, has not been previously reported with WNv infection. In both patients, treatment with IVIG resulted in improvement in symptoms.

Neurological Predictors of Clinical Outcomes in Hospitalized Patients With COVID-19.

Introduction: Multiple risk factors of mortality have been identified in patients with COVID-19. Here, we sought to determine the effect of a history of neurological disorder and development of neurological manifestations on mortality in hospitalized patients with COVID-19. Methods: From March 20 to May 20, 2020, hospitalized patients with laboratory confirmed or highly suspected COVID-19 were identified at four hospitals in Ohio. Previous history of neurological disease was classified by severity (major or minor). Neurological manifestations during disease course were also grouped into major and minor manifestations. Encephalopathy, ischemic or hemorrhagic stroke, and seizures were defined as major manifestations, whereas minor neurological manifestations included headache, anosmia, dysgeusia, dizziness or vertigo, and myalgias. Multivariate logistic regression models were used to determine significant predictors of mortality in patients with COVID-19 infection. Results: 574/626 hospitalized patients were eligible for inclusion. Mean age of the 574 patients included in the analysis was 62.8 (SD 17.6), with 298 (51.9%) women. Of the cohort, 240(41.8%) patients had a prior history of neurological disease (HND), of which 204 (35.5%) had a major history of neurological disease (HND). Mortality rates were higher in patients with a major HND (30.9 vs. 15.4%; p = 0.00002), although this was not a significant predictor of death. Major neurological manifestations were recorded in 203/574 (35.4%) patients during disease course. The mortality rate in patients who had major neurological manifestations was 37.4% compared to 11.9% (p = 2 × 10-12) in those who did not. In multivariate analysis, major neurological manifestation (OR 2.1, CI 1.3-3.4; p = 0.002) was a predictor of death. Conclusions: In this retrospective study, history of pre-existing neurological disease in hospitalized COVID-19 patients did not impact mortality; however, development of major neurological manifestations during disease course was found to be an independent predictor of death. Larger studies are needed to validate our findings.

Malignant glomus tumor of the lung with multiorgan metastases: case report and literature review.

Glomus tumor is an exceedingly rare neoplasm that is derived from cells of the neuromyoarterial glomus or glomus body. It rarely occurs in the visceral organs where glomus body may be sparse or even absent, such as the stomach, intestines, mediastinum, and respiratory tract. It is unusual for a glomus tumor to demonstrate atypical or malignant histopathological characteristics. It is also rare for such a tumor to express clinically aggressive behavior. However, when metastasis does occur, this disease is often fatal. We herein report an interesting case of a middle-age woman admitted due to progressive cough and hemoptysis. A polypoid mass was found to occlude the left lingular lobar bronchus. Final histopathologic examination showed the presence of malignant glomus tumor, confirmed by immunoreactivity for smooth muscle actin and vimentin. Two months later, the patient developed abdominal distension and gastrointestinal bleeding. Further evaluation lead to the discovery of widespread metastatic disease to the gastrointestinal tract, spleen, and the left adrenal gland. We further entail a review of the literature on the clinicopathologic features and diagnosis of this uncommon tumor.