Neurological Expertise Research Articles

The prevalence of multiple sclerosis in Israel based on validation of a health care organization database

In Israel there is no registry of multiple sclerosis (MS), thus the prevalence of MS is unknown. Clalit Health Services (CHS) is Israel’s largest health care organization. We have developed an algorithm to identify people with MS (PwMS) using CHS database and validated it against a gold-standard diagnosis by expert neurologists. People with a possible diagnosis of MS were identified in CHS database according to ICD-9 code or dispense of MS specific disease modifying treatment (DMT). The electronic medical records (EMRs) of a random sample of 25% of this population, stratified by age and sex were examined to determine positive predictive value (PPV). Another age- and sex- stratified random sample of 15% of pwMS under our care were searched in CHS database to determine database sensitivity (Sn). Finally, a random sample of 40% of people without MS were searched in CHS database to evaluate database specificity (Sp). The best case definition to retrieve pwMS was ICD-9 code 340 as an established diagnosis or at least one dispense of a DMT (PPV = 87%, Sn = 92%, Sp = 90%). Using this definition the prevalence of MS in Israel was 68, 82 and 95 per 100,000 population by the end of 2011, 2016 and 2021, respectively. The prevalence of MS in Israel is rising, in line with the worldwide trend.

VISIT STROKE: non-inferiority of telemedicine-based neurological consultation for post-acute stroke patients – protocol of a prospective observational controlled multi-center study

BackgroundTelemedicine provides specialized medical expertise in underserved areas where neurological expertise is frequently not available on a daily basis for hospitalized stroke patients. While tele-consultations are well established in acute stroke assessment, the value of telemedicine-based ward-rounds in the subsequent in-patient stroke management is unknown.MethodsFour telemedicine stroke networks in Germany, implemented in eight out of 16 federal states, participate in this prospective observational multi-center study. We plan to enroll 523 patients hospitalized due to acute (suspected or confirmed) stroke or transient ischemic attack. Each recruited patient will receive both a tele-consultation and an on-site consultation at the same day within the first three days after hospital admission. We will test non-inferiority of telemedicine-based assessments in ward-rounds in terms of quality of medical assessment and recommendations for hospitalized stroke patients. The correctness of the medical assessment and recommendation is defined as positive evaluation (binary, correct vs. in-correct) of six out of six predefined quality indicators by at least two out of three blinded independent raters. The non-inferiority margin for the difference in proportions of correct assessments is set to 5%-points.DiscussionIf non-inferiority of telemedicine-based ward-rounds compared to on-site ward-rounds by a neurologist were demonstrated, telemedicine-based neurological consultation for post-acute stroke patients may contribute to deliver evidence-based high-quality stroke care more easily in underserved regions.Trial registrationDRKS - DRKS00028671 (https://drks.de/search/de/trial/DRKS00028671; registration date 09-27-2022).

ChatGPT M.D.: Is there any room for generative AI in neurology?

ChatGPT, a general artificial intelligence, has been recognized as a powerful tool in scientific writing and programming but its use as a medical tool is largely overlooked. The general accessibility, rapid response time and comprehensive training database might enable ChatGPT to serve as a diagnostic augmentation tool in certain clinical settings. The diagnostic process in neurology is often challenging and complex. In certain time-sensitive scenarios, rapid evaluation and diagnostic decisions are needed, while in other cases clinicians are faced with rare disorders and atypical disease manifestations. Due to these factors, the diagnostic accuracy in neurology is often suboptimal. Here we evaluated whether ChatGPT can be utilized as a valuable and innovative diagnostic augmentation tool in various neurological settings. We used synthetic data generated by neurological experts to represent descriptive anamneses of patients with known neurology-related diseases, then the probability for an appropriate diagnosis made by ChatGPT was measured. To give clarity to the accuracy of the AI-determined diagnosis, all cases have been cross-validated by other experts and general medical doctors as well. We found that ChatGPT-determined diagnostic accuracy (ranging from 68.5% ± 3.28% to 83.83% ± 2.73%) can reach the accuracy of other experts (81.66% ± 2.02%), furthermore, it surpasses the probability of an appropriate diagnosis if the examiner is a general medical doctor (57.15% ± 2.64%). Our results showcase the efficacy of general artificial intelligence like ChatGPT as a diagnostic augmentation tool in medicine. In the future, AI-based supporting tools might be useful amendments in medical practice and help to improve the diagnostic process in neurology.

Neurology of Aging : adapting neurology provision for an aging population.

Background Over the past few decades, advances in neurology of aging have been considerable and have led to a better understanding of the science of age-related neurological disorders. Likewise, it changed the perception of classical neurology practice, research and the way of looking at age-related conditions. Neurological disorders are the most frequent cause of major disability in the elderly and account for almost half of the incapacitation occurring beyond age 65 and more than 90% of serious dependency. However, a number of neurological changes occur also in the absence of a specific disease, making the assessment and management of neurological complaints and findings a specific expertise. Summary Maximizing success in clinical care of the elderly requires expertise in geriatric neurology, which includes an understanding of current research regarding aging and age-related neurological dysfunctions, and the ability to work with other geriatric health care providers. Although current therapies for neurodegenerative diseases mainly offer symptomatic relief without slowing progression, the landscape is evolving. Biomarkers of pathology and neuroimaging have continued to develop, with a significant impact on diagnosis and treatment. These advances have helped to improve our knowledge of disease pathophysiology but also disease stages, guiding symptomatic monitoring, and possible therapeutic options at a pre-symptomatic stage. Key Messages Neurological disorders are a leading cause of major disability and dependency in the elderly, underscoring the need for expertise in geriatric neurology for effective clinical care of this population. Although current therapies for neurodegenerative diseases primarily provide symptomatic relief without slowing disease progression, advancements in biomarkers and neuroimaging are significantly evolving. These advancements enhance our understanding of disease pathophysiology and stages, guiding symptomatic monitoring and potential therapeutic options at a pre-symptomatic stage. As knowledge about age-associated conditions is steadily rising and geriatric medicine gains further recognition, this article argues for a new focus on the role of neurologists in geriatric medicine, emphasizing the importance of integrating current research and collaborative care approaches in the management of elderly patients.

Graph neural networks for electroencephalogram analysis: Alzheimer’s disease and epilepsy use cases

Electroencephalography (EEG) is widely used as a non-invasive technique for the diagnosis of several brain disorders, including Alzheimer’s disease and epilepsy. Until recently, diseases have been identified over EEG readings by human experts, which may not only be specific and difficult to find, but are also subject to human error. Despite the recent emergence of machine learning methods for the interpretation of EEGs, most approaches are not capable of capturing the underlying arbitrary non-Euclidean relations between signals in the different regions of the human brain. In this context, Graph Neural Networks (GNNs) have gained attention for their ability to effectively analyze complex relationships within different types of graph-structured data. This includes EEGs, a use case still relatively unexplored. In this paper, we aim to bridge this gap by presenting a study that applies GNNs for the EEG-based detection of Alzheimer’s disease and discrimination of two different types of seizures. To this end, we demonstrate the value of GNNs by showing that a single GNN architecture can achieve state-of-the-art performance in both use cases. Through design space explorations and explainability analysis, we develop a graph-based transformer that achieves cross-validated accuracies over 89% and 96% in the ternary classification variants of Alzheimer’s disease and epilepsy use cases, respectively, matching the intuitions drawn by expert neurologists. We also argue about the computational efficiency, generalizability and potential for real-time operation of GNNs for EEGs, positioning them as a valuable tool for classifying various neurological pathologies and opening up new prospects for research and clinical practice.

Assessment of long-term psychosocial outcomes in N-methyl-D-aspartate receptor encephalitis – the SAPIENCE study protocol

BackgroundN-methyl-D-aspartate-receptor (NMDAR) encephalitis is a rare neurological autoimmune disease with severe neuropsychiatric symptoms during the acute phase. Despite good functional neurological recovery, most patients continue to experience cognitive, psychiatric, psychological, and social impairments years after the acute phase. However, the precise nature and evolving patterns over time of these long-term consequences remain unclear, and their implications for the well-being and quality of life of predominantly young patients have yet to be thoroughly examined.MethodsSAPIENCE is a European multi-center (n = 3) prospective observational cohort study studying the long-term cognitive, psychiatric, psychological, and social outcome in patients with NMDAR encephalitis. The study consists of three interconnected levels. Level 1 comprises a qualitative interview and focus groups with patients and their caregivers. Level 2 consists of a condensed form of the interview, standardized questionnaires, and a detailed neuropsychological examination of patients. Level 3 involves an online survey that will be open to patients world-wide and explores patient-reported outcomes (PROMs), and patient-reported experiences (PREMs) in association with clinical and cognitive outcomes. Levels 1 to 3 will progressively contribute developing of structured interviews, survey questions, and treatment guidelines by informing one another.DiscussionSAPIENCE is an in-depth study of the long-term effects of NMDAR encephalitis and bridges the gap between standardized assessments and individual patient experiences, intending to improve patient care and to increase awareness of the psychosocial long-term consequences of the disease. Through collaboration of experts in clinical neurology and social and health psychology across Europe, SAPIENCE aims to create online assessment tools and formulate guidelines for patient-centered post-acute care that will help enhance the quality of life for patients and caregivers.

Analysis of white matter hyperintensities in Alzheimer’s disease and vascular dementia with magnetic resonance imaging

Objectives: The study aimed to analyze the brain white matter hyperintensities (WMHs) of patients with vascular dementia (VaD) and Alzheimer’s disease (AD) using magnetic resonance imaging to determine whether white matter lesions in the brain could be detected by a computer using image processing methods. Patients and methods: In this retrospective observational study, a unimodal, unsupervised, and automatic method was developed, and magnetic resonance imaging of 35 patients were examined. Of the 35 patients, 19 (14 males, 5 females; mean age: 73.2±6.7 years; range, 56 to 83 years) were picked from patients with AD or VaD who were admitted to a neurology clinic between January 2016 and December 2022 (Group 1). The remaining 16 patients (10 females, 5 males; mean age: 80.4±5.4 years; range, 69 to 92 years) were included from the ABVIB (Aging Brain: Vasculature, Ischemia, and Behavior) study from the ADNI (Alzheimer’s Disease Neuroimaging Initiative) database (Group 2). To calculate the volume of WMHs, a detailed analysis was conducted. Initially, skull stripping was performed, and then the brain was segmented. Afterward, two types of masks (Mask1 and Mask-2) were obtained by applying painting, decreasing, and blurring processes to the segmented white matter. These masks limited the region that was searched for WMHs. With this limitation, false positives that could arise from gray matter intensities were tried to be prevented. To evaluate the accuracy of WMH detection, a user interface was developed, and manual marking was conducted by an expert neurologist. After WMH detection, WMH volumes were calculated. Results: For Group 1, the similarity index was found to be 0.76 for Mask-1 and 0.80 for Mask-2, while for Group 2, the similarity index was 0.71 for Mask-1 and 0.87 for Mask-2. In patients with AD, the mean WMH lesion load (LL) was 15.16±16.59 mL. In patients with VaD, who were expected to suffer more from WMHs, the mean WMH LL was 29.22±11.40 mL. In Group 2, the mean WMH LL was 17.77±12.26 mL. Conclusion: This study may contribute to the literature since it is an automatic, unimodal, and unsupervised method that was applied to both a completely unique data set with many different scanning parameters and an open database data set.

ENTIMOS: Decision Support Tool Highlights Potential Impact of Non-intravenous Therapies for Multiple Sclerosis on Patient Care via Clinical Scenario Simulation.

Administration of intravenous (IV), high-efficacy treatments (HETs) for the treatment of multiple sclerosis (MS) poses a high resourcing and planning burden on infusion centres, resulting in treatment delays that may increase the risk of breakthrough disease activity. Simulation tools can be used to systematically analyse capacity scenarios and identify and better understand constraints, therefore enabling decision-makers to optimise patient care. We have previously applied ENTIMOS, a discrete event simulation model, to assess scenarios of patient flow and care delivery using real-life data inputs from the neurology infusion suite at Charing Cross Hospital London. The model predicted that, given current capacity and projected demand, patients would experience high-risk treatment delays within 30 months. This study aimed to address key healthcare challenges for MS patient care management as seen from a neurologist's perspective. We used ENTIMOS to predict the impact of several distinct and clinically plausible scenarios on patient waiting times at the same MS infusion suite and to quantify mitigation strategies needed to assure continuity of care. We used real-world experience of an expert neurologist to identify five clinical scenarios: (1) switching patients to a subcutaneous (SC) MS treatment of the same therapeutic agent, in the same hospital setting; (2) extending opening times to the weekend; (3) reducing the number of infusion chairs (to simulate social distancing measures applied during the coronavirus disease 2019 [COVID-19] pandemic); (4) increasing demand for infusions; and (5) increasing the scheduling approval time. Patient waiting time for next due infusion and time to high-risk treatment delays (≥ 30 days) were the main analysed model outputs. Previously published base case results were used as reference. All hypothetical scenarios were run over a 3-year horizon (with the exception of scenario 1, which was run over a 3- and 5-year horizon). Strategies to mitigate treatment delays were analysed and discussed. Switching 50% of patients to SC treatment of the same therapeutic agent administered in hospital postponed the predicted high-risk treatment delays to shortly beyond the 3-year simulation timeframe (month 38). Weekend opening reduced waiting times from 20 days to 4 days and prevented treatment delays, however, at elevated labour costs. Reducing the infusion chairs increased waiting time to 53 days on average and 86 days at the end of the simulation, leading to high-risk treatment delays within 6 months. An increased demand for infusions increased waiting time to 26 days on average and 47 days at the end of the simulation, leading to high-risk treatment delays within 22 months. Prolonged scheduling approval time did not reduce the waiting time, nor postpone the high-risk treatment delays. Decision makers need transparency on capacity constraints to better plan resourcing at infusion suites and MS treatments. Our results showed that various mitigation measures, such as increasing capacity by additional infusion chairs per year and transferring patients to other infusion suites, may help prevent treatment delays. Switching patients from IV to an SC version of the same therapeutic agent reduced the waiting time moderately and postponed high-risk treatment delays. It was insufficient to prevent high-risk treatment delays in the long term.

Brain fog assessment in patients recovered from COVID-19 in China: a development and validation study

Background Post coronavirus disease 2019 (COVID-19) pandemic, the widespread emergence and persistence of brain fog has led to a decline in people’s productivity and quality of life. However, the clinical characteristics of COVID-19-associated brain fog are unclear, and standardized assessments are lacking. This study aims to develop a scale for brain fog assessment and support clinical practice and research. Methods The 17-item Brain Fog Assessment (BFA) scale was developed using a standardized methodology, including literature review, focus group discussions (FGDs), expert evaluation, and psychometric validation. Eighteen potential items were generated following the literature review. These items were subsequently refined during FGDs, which included input from patients, caregivers, and multidisciplinary experts in neurology, cognitive neuroscience, and psychology. After thorough deliberation and expert evaluation, the item pool was finalized into a 17-item scale. We recruited 1,325 patients recovered from COVID-19 from Chinese communities. Psychometric properties were assessed by reliability and validity analysis. Results Exploratory factor analysis of the BFA scale revealed a three-factor mode comprising ‘cognitive decline’ (nine items), ‘confusion − disorientation’ (five items), and ‘fatigue’ (three items). The internal consistency of each factor was strong (Cronbach’s α: 0.82–0.92). Confirmatory factor analysis showed that the model fit, convergent validity, and discriminant validity of the scale were satisfactory. The test-retest reliability was strong (intraclass correlation coefficient = 0.84). Criterion-related validity analysis showed a strong correlation to the Wood Mental Fatigue Inventory (r = 0.70, p < 0.001). Individuals with a higher BFA score tended to score lower on the Montreal Cognitive Assessment (r = −0.23, p = 0.015). Conclusions We established a novel BFA scale to quantify multiple clinical aspects of COVID-19-associated brain fog. Using the BFA scale, fatigue and declining performance in memory, attention, and thought were identified as the main symptoms of COVID-19-associated brain fog. This scale has potential implications for disease monitoring and therapy development for individuals with COVID-19-associated brain fog.

Evaluation of the impact of neurology electronic consults (e-consults): Experiences of a neurology resident clinic in a safety-net hospital.

Electronic consults (e-consults) are asynchronous, formalized requests by a provider to involve a specialist to assist with decision making. E-consults are an alternative to face-to-face consultation and are a promising strategy to efficiently address certain requests for advice. The objective of this project was to examine the utility and characteristics of electronic consults utilized in a safety-net hospital outpatient neurology clinic. We retrospectively reviewed e-consults to the neurology clinic from1 January 2021 to 31 September 2021. The reasons for requests and any diagnostic or treatment recommendations were collected. The time to completion of the e-consults and the percentage of e-consult referred for an in-person clinic evaluation were determined as outcome measures. Following each e-consult, the consulting provider completed a survey to gather their assessment on the appropriateness of the consult, time spent answering the consult, and if unnecessary testing or clinic visits were avoided. A total of 528 e-consults were completed during the study period. The most frequent e-consult referrals were for headache (22%), stroke/neurovascular (21%), neuropathy/neuritis/disturbance of skin sensation (11%), and seizures/spells (11%). The majority of e-consults (94%) were answered in one business day (defined as occurring within 24 h) with 67% of consults answered the same day (defined as occurring within the same calendar day). The consulting providers reported that more than 90% of e-consults took <15 min to answer, and 84% of e-consult requests were felt to be appropriate. A total 156 (41.4%) patients initially seen as an e-consult were referred for a face-to-face visit within 90 days of the e-consult. E-consults provided expedited input from neurologists, which is vital in health systems that provide care to vulnerable populations. The majority of e-consults were answered within 1 day of referral, offering rapid access to neurological expertise in comparison to wait times currently encountered for face-to-face visits. Accordingly, e-consults have the potential to expedite treatment for patients, empower primary care providers, and reduce demand for in-person consultations, particularly in large health systems caring for vulnerable populations.

ICU-Electroencephalogram Unit Improves Outcome in Status Epilepticus Patients: A Retrospective Before-After Study.

Continuous electroencephalogram (cEEG) monitoring is recommended for status epilepticus (SE) management in ICU but is still underused due to resource limitations and inconclusive evidence regarding its impact on outcome. Furthermore, the term "continuous monitoring" often implies continuous recording with variable intermittent review. The establishment of a dedicated ICU-electroencephalogram unit may fill this gap, allowing cEEG with nearly real-time review and multidisciplinary management collaboration. This study aimed to evaluate the effect of ICU-electroencephalogram unit establishing on SE outcome and management. Single-center retrospective before-after study. Neuro-ICU of a Swiss academic tertiary medical care center. Adult patients treated for nonhypoxic SE between November 1, 2015, and December 31, 2023. None. Data from all SE patients were assessed, comparing those treated before and after ICU-electroencephalogram unit introduction. Primary outcomes were return to premorbid neurologic function, ICU mortality, SE duration, and ICU SE management. Secondary outcomes were SE type and etiology. Two hundred seven SE patients were included, 149 (72%) before and 58 (38%) after ICU-electroencephalogram unit establishment. ICU-electroencephalogram unit introduction was associated with increased detection of nonconvulsive SE ( p = 0.003) and SE due to acute symptomatic etiology ( p = 0.019). Regression analysis considering age, comorbidities, SE etiology, and SE semeiology revealed a higher chance of returning to premorbid neurologic function ( p = 0.002), reduced SE duration ( p = 0.024), and a shift in SE management with increased use of antiseizure medications ( p = 0.007) after ICU-electroencephalogram unit introduction. Integrating neurology expertise in the ICU setting through the establishment of an ICU-electroencephalogram unit with nearly real-time cEEG review, shortened SE duration, and increased likelihood of returning to premorbid neurologic function, with an increased number of antiseizure medications used. Further studies are warranted to validate these findings and assess long-term prognosis.

Updated Clinical Recommendations for Multiple Sclerosis by Saudi Neurology Experts

Abstract This study presents an update on clinical recommendations in the diagnosis and management of people with multiple sclerosis (pwMS). This has been accomplished through a systematic effort by a committee of leading neurology experts appointed by the Ministry of Health in Saudi Arabia to review the latest scientific literature on MS to enhance the care of MS patients. These recommendations encompass multifaceted aspects of MS care, facilitate an optimized approach for healthcare providers, and include diagnosis, management, and special considerations unique to pwMS.

Families as partners in neonatal neuro-critical care programs.

Parents of neonates with neurologic conditions face a specific breadth of emotional, logistical, and social challenges, including difficulties coping with prognostic uncertainty, the need to make complex medical decisions, and navigating new hopes and fears. These challenges place parents in a vulnerable position and at risk of developing mental health issues, which can interfere with bonding and caring for their neonate, as well as compromise their neonate's long-term neurodevelopment. To optimize neurologic and developmental outcomes, emerging neonatal neuro-critical care (NNCC) programs must concurrently attend to the unique needs of the developing newborn brain and of his/her parents. This can only be accomplished by embracing a family-centered care environment-one which prioritizes effective parent-clinician communication, longitudinal parent support, and parents as equitable partners in clinical care. NNCC programs offer a multifaceted approach to critical care for neonates at-risk for neurodevelopmental impairments, integrating expertise in neonatology and neurology. This review highlights evidence-based strategies to guide NNCC programs in developing a family-partnered approach to care, including primary staffing models; staff communication, implicit bias, and cultural competency trainings; comprehensive and tailored caregiver training; single-family rooms; flexible visitation policies; colocalized neonatal and maternal care; uniform mental health screenings; follow-up care referrals; and connections to peer support. IMPACT: Parents of neonates with neurologic conditions are at high-risk for experiencing mental health issues, which can adversely impact the parent-neonate relationship and long-term neurodevelopmental outcomes of their neonates. While guidelines to promote families as partners in the neonatal intensive care unit (NICU) have been developed, no protocols integrate the unique needs of parents in neonatal neurologic populations. A holistic approach that makes families true partners in the care of their neonate with a neurologic condition in the NICU has the potential to improve mental and physical well-being for both parents and neonates.

Scottish Intercollegiate Guidelines Network Guidance on Dementia: The Investigation of Suspected Dementia (SIGN 168) with Focus on Biomarkers-Executive Summary.

This is an executive summary of the recent guidance produced by the Scottish Intercollegiate Guidelines Network (SIGN) dementia guideline group with regards to the investigation of suspected dementia. This is a sub-section of the broader SIGN 168 guideline released in November 2023. The guideline group included clinicians with expertise in Old Age Psychiatry, Neurology, Radiology, and Nuclear Medicine supported by colleagues from the SIGN and Healthcare Improvement Scotland teams. There was representation from carers and support organizations with experience of dementia, to ensure the recommendations were appropriate from the perspective of the people being assessed for possible dementia and their carers. As the 2018 National Institute for Health and Clinical Excellence (NICE) dementia review included a review of the evidenced investigation of dementia, the SIGN guideline development group decided to focus on a review on the up-to-date evidence regarding the role of imaging and fluid biomarkers in the diagnosis of dementia. To give context to the consideration of more advanced diagnostic biomarker investigations, the guideline and this summary include the NICE guidance on the use of standard investigations as well as more specialist investigations. The evidence review supports consideration of the use of structural imaging, nuclear medicine imaging, and established Alzheimer's cerebrospinal fluid biomarkers (amyloid and tau) in the diagnosis of dementia. Although routine use of amyloid positron emission tomography imaging was not recommended, its potential use, under specialist direction, in patients with atypical or young-onset presentations of suspected Alzheimer's dementia was included as a clinical good practice point.

Perioperative care of patients with recent stroke undergoing nonemergent, nonneurological, noncardiac, nonvascular surgery: a systematic review and meta-analysis.

To systematically review and perform a meta-analysis of published literature regarding postoperative stroke and mortality in patients with a history of stroke and to provide a framework for preoperative, intraoperative, and postoperative care in an elective setting. Patients with nonneurological, noncardiac, and nonvascular surgery within three months after stroke have a 153-fold risk, those within 6 months have a 50-fold risk, and those within 12 months have a 20-fold risk of postoperative stroke. There is a 12-fold risk of in-hospital mortality within three months and a three-to-four-fold risk of mortality for more than 12 months after stroke. The risk of stroke and mortality continues to persist years after stroke. Recurrent stroke is common in patients in whom anticoagulation/antiplatelet therapy is discontinued. Stroke and time elapsed after stroke should be included in the preoperative assessment questionnaire, and a stroke-specific risk assessment should be performed before surgical planning is pursued. In patients with a history of a recent stroke, anesthesiology, surgery, and neurology experts should create a shared mental model in which the patient/surrogate decision-maker is informed about the risks and benefits of the proposed surgical procedure; secondary-stroke-prevention medications are reviewed; plans are made for interruptions and resumption; and intraoperative care is individualized to reduce the likelihood of postoperative stroke or death.

Forensic Neurology and the Role of Neurologists in Forensic Evaluations.

Forensic psychiatrists may be asked to opine on neurological evidence or neurological diseases outside the scope of their expertise. This article discusses the value of involving experts trained in behavioral neurology in such cases. First, we describe the field of behavioral neurology and neuropsychiatry, the subspecialty available to both neurologists and psychiatrists focused on the behavioral, cognitive, and neuropsychiatric manifestations of neurological diseases. Next, we discuss the added value of behavioral neurologists in forensic cases, including assisting in the diagnostic evaluation for complex neuropsychiatric diseases, using expertise in localization to provide a strong scientific basis for linking neurodiagnostic testing to relevant neuropsychiatric symptoms, and assisting in relating these symptoms to the relevant legal question in cases where such symptoms may be less familiar to forensic psychiatrists, such as frontal lobe syndromes. We discuss approaches to integrating behavioral neurology with forensic psychiatry, highlighting the need for collaboration and mentorship between disciplines. Finally, we discuss several forensic cases highlighting the additional value of experts trained in behavioral neurology. We conclude that forensic psychiatrists should involve behavioral neurology experts when encountering neurological evidence that falls outside their scope of expertise, and the need for further cross-disciplinary collaboration and training.

A comparison of quantitative parameters of axial posture and spinal mobility between motor subtypes of Parkinson's disease.

<p>Parkinson&rsquo;s disease (PD) is a heterogeneous neurodegenerative disorder characterized by contradictory clinical outcomes among its several subtypes. The disease can manifest with a tremor-dominant (TD) or a non-tremor-dominant (NTD) phenotype. Although the TD subtype may show a better prognosis, there is limited information on the phenotypic differences regarding the level of axial symptoms. For this reason, in this study it was aimed to make a quantitative comparison of axial posture and spinal mobility between PD with TD and NTD.&nbsp;</p>. <p>This case-control study was conducted on 94 patients with diagnosed PD. A group diagnosis approach was used in the study, such that the diagnosis of each patient was confirmed, and they were assig-ned to TD and NTD groups by a neurologist expert on movement disorders. Of the patients with PD, 61 were in the TD group, and 33 were in the NTD group. Spinal mouse was used to measure spinal posture and spinal mobility in both sagittal and frontal planes.&nbsp;</p>. <p>Two groups of 61 patients (25 male + 36 female) with TD-PD (mean age: 64.49&plusmn;10.37 years) and 33 patients (20 male +13 female) with NTD-PD (mean age: 63.45&plusmn;9.11 years) were enrolled in the study. There were no significant differences bet&shy;ween the patients with TD and NTD in terms of sagittal and frontal postures (p&gt;0.05). In addition to this, anterior trunk tilt was found to significantly increase as the disease stage advanced in both groups. While the greatest anterior trunk tilt change in the TD-PD group was observed in the 3rd stage, NTD-PD group was in the 2.5th stage. Aside from this, the out&shy;comes of the spinal mobility measurements in the frontal and sagittal planes were similar between the groups (p&gt;0.05).</p>. <p>It is widely acknowledged that many clinical aspects of the TD and NTD forms of PD differ; however, in our study, it was observed that there may be no difference in the axial symptoms of the patients with PD in terms of classification according to tremor dominance.</p>.

Direct Clinical Applications of Natural Language Processing in Common Neurological Disorders: Scoping Review

Background Natural language processing (NLP), a branch of artificial intelligence that analyzes unstructured language, is being increasingly used in health care. However, the extent to which NLP has been formally studied in neurological disorders remains unclear. Objective We sought to characterize studies that applied NLP to the diagnosis, prediction, or treatment of common neurological disorders. Methods This review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) standards. The search was conducted using MEDLINE and Embase on May 11, 2022. Studies of NLP use in migraine, Parkinson disease, Alzheimer disease, stroke and transient ischemic attack, epilepsy, or multiple sclerosis were included. We excluded conference abstracts, review papers, as well as studies involving heterogeneous clinical populations or indirect clinical uses of NLP. Study characteristics were extracted and analyzed using descriptive statistics. We did not aggregate measurements of performance in our review due to the high variability in study outcomes, which is the main limitation of the study. Results In total, 916 studies were identified, of which 41 (4.5%) met all eligibility criteria and were included in the final review. Of the 41 included studies, the most frequently represented disorders were stroke and transient ischemic attack (n=20, 49%), followed by epilepsy (n=10, 24%), Alzheimer disease (n=6, 15%), and multiple sclerosis (n=5, 12%). We found no studies of NLP use in migraine or Parkinson disease that met our eligibility criteria. The main objective of NLP was diagnosis (n=20, 49%), followed by disease phenotyping (n=17, 41%), prognostication (n=9, 22%), and treatment (n=4, 10%). In total, 18 (44%) studies used only machine learning approaches, 6 (15%) used only rule-based methods, and 17 (41%) used both. Conclusions We found that NLP was most commonly applied for diagnosis, implying a potential role for NLP in augmenting diagnostic accuracy in settings with limited access to neurological expertise. We also found several gaps in neurological NLP research, with few to no studies addressing certain disorders, which may suggest additional areas of inquiry. Trial Registration Prospective Register of Systematic Reviews (PROSPERO) CRD42021228703; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=228703

Supplementing Best Care with Specialized Rehabilitation Treatment in Parkinson's Disease: A Retrospective Study by Different Expert Centers.

Background: This is a retrospective longitudinal study comparing 374 patients with Parkinson's disease (PD) who were treated in centers offering a specialized program of enhanced rehabilitation therapy in addition to expert outpatient care to 387 patients with PD, who only received expert outpatient care at movement disorders centers in Italy. Methods: The data are from subjects recruited in the Parkinson's Outcome Project (POP) at six Italian centers that are part of a multicenter collaboration for care quality improvement (the Fresco Network). The effects were measured with a baseline and a follow-up clinical evaluation of the Timed-Up-and-Go test (TUG), Parkinson's Disease Questionnaire (PDQ-39), and Multidimensional Caregiver Strain Index (MCSI), the number of falls and hospitalizations for any cause. We used a generalized linear mixed model with the dependent variables being the response variable, which included the covariates demographics, evaluation, and treatment variables. Results: We found that the subjects who underwent specialized enhanced rehabilitation had a better motor outcome over time than those who were managed by expert neurologists but had participated in community programs for exercise and other allied health interventions. The greatest effects were seen in patients in the early stages of the disease with a high amount of vigorous exercise per week in the last six months. Similar effects were seen for PDQ39, MCSI, the number of falls, and hospitalization. Conclusions: Long-term benefits to motor function and the quality of life in patients with PD and burden reduction in their caregivers can be achieved through a systematic program of specialized enhanced rehabilitation interventions.

Ischemic Stroke and Reduced Left Ventricular Ejection Fraction: A Multidisciplinary Approach to Optimize Brain and Cardiac Health.

Reduced left ventricular ejection fraction ≤40%, a known risk factor for adverse cardiac outcomes and recurrent acute ischemic stroke, may be detected during an acute ischemic stroke hospitalization. A multidisciplinary care paradigm informed by neurology and cardiology expertise may facilitate the timely implementation of an array of proven heart failure-specific therapies and procedures in a nuanced manner to optimize brain and cardiac health.