Faculty Bibliography

Orthostatic hypotension is an unusually large decrease in blood pressure on standing that increases the risk of adverse outcomes even when asymptomatic. Improvements in haemodynamic profiling with continuous blood pressure measurements have uncovered four major subtypes: initial orthostatic hypotension, delayed blood pressure recovery, classic orthostatic hypotension, and delayed orthostatic hypotension. Clinical presentations are varied and range from cognitive slowing with hypotensive unawareness or unexplained falls to classic presyncope and syncope. Establishing whether symptoms are due to orthostatic hypotension requires careful history taking, a thorough physical examination, and supine and upright blood pressure measurements. Management and prognosis vary according to the underlying cause, with the main distinction being whether orthostatic hypotension is neurogenic or non-neurogenic. Neurogenic orthostatic hypotension might be the earliest clinical manifestation of Parkinson's disease or related synucleinopathies, and often coincides with supine hypertension. The emerging variety of clinical presentations advocates a stepwise, individualised, and primarily non-pharmacological approach to the management of orthostatic hypotension. Such an approach could include the cessation of blood pressure lowering drugs, adoption of lifestyle measures (eg, counterpressure manoeuvres), and treatment with pharmacological agents in selected cases.

In large clinical centers a small subset of patients present with hydrocephalus that requires surgical treatment. We aimed to develop a screening tool to detect such cases from the head MRI with performance comparable to neuroradiologists. We leveraged 496 clinical MRI exams collected retrospectively at a single clinical site from patients referred for any reason. This diagnostic dataset was enriched to have 259 hydrocephalus cases. A 3D convolutional neural network was trained on 16 manually segmented exams (ten hydrocephalus) and subsequently used to automatically segment the remaining 480 exams and extract volumetric anatomical features. A linear classifier of these features was trained on 240 exams to detect cases of hydrocephalus that required treatment with surgical intervention. Performance was compared to four neuroradiologists on the remaining 240 exams. Performance was also evaluated on a separate screening dataset of 451 exams collected from a routine clinical population to predict the consensus reading from four neuroradiologists using images alone. The pipeline was also tested on an external dataset of 31 exams from a 2nd clinical site. The most discriminant features were the Magnetic Resonance Hydrocephalic Index (MRHI), ventricle volume, and the ratio between ventricle and brain volume. At matching sensitivity, the specificity of the machine and the neuroradiologists did not show significant differences for detection of hydrocephalus on either dataset (proportions test, p > 0.05). ROC performance compared favorably with the state-of-the-art (AUC 0.90-0.96), and replicated in the external validation. Hydrocephalus cases requiring treatment can be detected automatically from MRI in a heterogeneous patient population based on quantitative characterization of brain anatomy with performance comparable to that of neuroradiologists.

Encephalopathy, a common condition among patients hospitalized with COVID-19, can be a challenge to manage and negatively affect prognosis. While encephalopathy may present clinically as delirium, subsyndromal delirium, or coma and may be a result of systemic causes such as hypoxia, COVID-19 has also been associated with more prolonged encephalopathy due to less common but nevertheless severe complications, such as inflammation of the brain parenchyma (with or without cerebrovascular involvement), demyelination, or seizures, which may be disproportionate to COVID-19 severity and require specific management. Given the large number of patients hospitalized with severe acute respiratory syndrome coronavirus-2 infection, even these relatively unlikely complications are increasingly recognized and are particularly important because they require specific management. Therefore, the aim of this review is to provide pragmatic guidance on the management of COVID-19 encephalopathy through consensus agreement of the Global COVID-19 Neuro Research Coalition. A systematic literature search of MEDLINE, medRxiv, and bioRxiv was conducted between January 1, 2020, and June 21, 2021, with additional review of references cited within the identified bibliographies. A modified Delphi approach was then undertaken to develop recommendations, along with a parallel approach to score the strength of both the recommendations and the supporting evidence. This review presents analysis of contemporaneous evidence for the definition, epidemiology, and pathophysiology of COVID-19 encephalopathy and practical guidance for clinical assessment, investigation, and both acute and long-term management.

Transcranial direct current stimulation (tDCS) is a safe and well-tolerated noninvasive method for stimulating the brain that is rapidly developing into a treatment method for various neurological and psychiatric conditions. In particular, there is growing evidence of a therapeutic role for tDCS in ameliorating or delaying the cognitive decline in Alzheimer's disease (AD). We provide a brief overview of the current development and application status of tDCS as a nonpharmacological therapeutic method for AD and mild cognitive impairment (MCI), summarize the levels of evidence, and identify the improvements needed for clinical applications. We also suggest future directions for large-scale controlled clinical trials of tDCS in AD and MCI, and emphasize the necessity of identifying the mechanistic targets to facilitate clinical applications.

Epilepsy surgery should be considered in all patients with drug-resistant focal epilepsy. The diagnostic presurgical evaluation aims to delineate the epileptogenic zone and its relationship to eloquent brain regions. Genetic testing is not yet routine in presurgical evaluations, despite many monogenic causes of severe epilepsies, including some focal epilepsies. This review highlights genomic data that may inform decisions regarding epilepsy surgery candidacy and strategy. Focal epilepsies due to pathogenic variants in mechanistic target of rapamycin pathway genes are amenable to surgery if clinical, electroencephalography and imaging data are concordant. Epilepsy surgery outcomes are less favourable in patients with pathogenic variants in ion channel genes such as SCN1A. However, genomic data should not be used in isolation to contraindicate epilepsy surgery and should be considered alongside other diagnostic modalities. The additional role of somatic mosaicism in the pathogenesis of focal epilepsies may have implications for surgical planning and prognostication. Here, we advocate for including genomic data in the presurgical evaluation and multidisciplinary discussion for many epilepsy surgery candidates. We encourage neurologists to perform genetic testing in patients with focal non-lesional epilepsy, epilepsy in the setting of intellectual disability and epilepsy due to specific malformations of cortical development. The integration of genomics into the presurgical evaluation assists selection of patients for resective surgery and fosters a personalised medicine approach, where precision or targeted therapies are considered alongside surgical procedures.

Clinical practice guidelines (CPGs) are statements that provide evidence-based recommendations aimed at optimizing patient care. However, many other documents are often published as "guidelines" when they are not; these documents, although also important in clinical practice, are usually not systematically produced following rigorous processes linking the evidence to the recommendations. Specifically, the International League Against Epilepsy (ILAE) guideline development toolkit aims to ensure that high-quality CPGs are developed to fill knowledge gaps and optimize the management of epilepsy. In addition to adhering to key methodological processes, guideline developers need to consider that effective CPGs should lead to improvements in clinical processes of care and health care outcomes. This requires monitoring the effectiveness of epilepsy-related CPGs and interventions to remove the barriers to epilepsy CPG implementation. This article provides an overview of what distinguishes quality CPGs from other documents and discusses their benefits and limitations. We summarize the recently revised ILAE CPG development process and elaborate on the barriers and facilitators to guideline dissemination, implementation, and adaptation.

Background/UNASSIGNED:Prior to the COVID-19 pandemic, about half of patients from populations that sought care in neurology tried complementary and integrative therapies (CITs). With the increased utilization of telehealth services, we sought to determine whether patients also increased their use of virtual CITs. Methods/UNASSIGNED:We examined datasets from two separate cross-sectional surveys that included cohorts of patients with neurological disorders. One was a dataset from a study that examined patient and provider experiences with teleneurology visits; the other was a study that assessed patients with a history of COVID-19 infection who presented for neurologic evaluation. We assessed and reported the use of virtual (and non-virtual) CITs using descriptive statistics, and determined whether there were clinical characteristics that predicted the use of CITs using logistic regression analyses. Findings/UNASSIGNED:Patients who postponed medical treatment for non-COVID-19-related problems during the pandemic were more likely to seek CITs. Virtual exercise, virtual psychotherapy, and relaxation/meditation smartphone applications were the most frequent types of virtual CITs chosen by patients. In both studies, age was a key demographic factor associated with mobile/virtual CIT usage. Interpretations/UNASSIGNED:Our investigation demonstrates that virtual CIT-related technologies were utilized in the treatment of neurologic conditions during the pandemic, particularly by those patients who deferred non-COVID-related care.

In-scanner head motion systematically reduces estimated regional gray matter volumes obtained from structural brain MRI. Here, we investigate how head motion affects structural covariance networks that are derived from regional gray matter volumetric estimates. We acquired motion-affected and low-motion whole brain T1-weighted MRI in 29 healthy adult subjects and estimated relative regional gray matter volumes using a voxel-based morphometry approach. Structural covariance network analyses were undertaken while systematically increasing the number of included motion-affected scans. We demonstrate that the standard deviation in regional gray matter estimates increases as the number of motion-affected scans increases. This increases pairwise correlations between regions, a key determinant for construction of structural covariance networks. We further demonstrate that head motion systematically alters graph theoretic metrics derived from these networks. Finally, we present evidence that weighting correlations using image quality metrics can mitigate the effects of head motion. Our findings suggest that in-scanner head motion is a source of error that violates the assumption that structural covariance networks reflect neuroanatomical connectivity between brain regions. Results of structural covariance studies should be interpreted with caution, particularly when subject groups are likely to move their heads in the scanner.

BACKGROUND:There are thousands of apps for individuals struggling with headache, insomnia, and pain, but it is difficult to establish which of these apps are best suited for patients' specific needs. If clinicians were to have access to a platform that would allow them to make an informed decision on the efficacy and feasibility of smartphone apps for patient care, they would feel confident in prescribing specific apps. OBJECTIVE:We sought to evaluate the quality of apps for some of the top common, disabling neurologic conditions (headache, insomnia, and pain) based on principles derived from the American Psychiatric Association's (APA) app evaluation model. METHODS:We used the Mobile Health Index and Navigation database and expanded upon the database's current supported conditions by adding 177 new app entries. Each app was rated for consistency with the APA's app evaluation model, which includes 105 objective questions based on the following 5 major classes of consideration: (1) accessibility, (2) privacy and security, (3) clinical foundation, (4) engagement style, and (5) interoperability. These characteristics were evaluated to gain a broader understanding of the significant features of each app category in comparison against a control group. RESULTS:Approximately 90% (187/201) of all apps evaluated were free to download, but only 50% (63/201) of headache- and pain-related apps were truly free. Most (87/106, 81%) sleep apps were not truly free to use. The apps had similar limitations with limited privacy, accessibility, and crisis management resources. For example, only 17% (35/201) of the apps were available in Spanish. The apps offered mostly self-help tools with little tailoring; symptom tracking was the most common feature in headache- (32/48, 67%) and pain-related apps (21/47, 45%), whereas mindfulness was the most common feature in sleep-related apps (73/106, 69%). CONCLUSIONS:Although there are many apps for headache, pain, and insomnia, all 3 types of apps have room for improvement around accessibility and privacy. Pain and headache apps share many common features, whereas insomnia apps offer mostly mindfulness-based resources. Given the many available apps to pick from, clinicians and patients should seek apps that offer the highest-quality features, such as complete privacy, remedial features, and the ability to download the app at no cost. These results suggest that there are many opportunities for the improvement of apps centered on headache, insomnia, and pain.