Associations Among Tremor Amplitude, Activities of Daily Living, and Quality of Life in Patients with Essential Tremor.

Background: Essential tremor (ET) is a disabling syndrome consisting of tremor, primarily in the upper limbs. We assessed the correlation of The Essential Tremor Rating Assessment Scale (TETRAS) Performance Item 4 ratings of upper limb tremor with the TETRAS activities of daily living (ADL) subscale and with 2 quality of life (QoL) scales. Methods: This noninterventional, cross-sectional, point-in-time survey of neurologists(n = 60), primary care physicians (n = 38), and their patients with ET (n = 1,003) used real-world data collected through the Adelphi ET Disease Specific Programme™. Physician-reported measures (TETRAS Performance Item 4 and TETRAS ADL total) and patient-reported QoL measures (generic EuroQol-5 Dimension 5 Level [EQ-5D-5 L] and ET-specific Quality of Life in Essential Tremor Questionnaire (QUEST)) were assessed with bivariate and multivariable analyses. Sensitivity analyses were also conducted. Results: The bivariate association between TETRAS Performance Item 4 score and TETRAS ADL total score was high (Pearson r = 0.761, P < 0.001). The bivariate associations between TETRAS Performance Item 4 score and EQ-5D-5 L index score (r = -0.410, P < 0.001) and between TETRAS ADL total score and EQ-5D-5 L index score (r = -0.543, P < 0.001) were moderate. The bivariate associations between TETRAS Performance Item 4 score and QUEST total score (r = 0.457, P < 0.001), and between TETRAS ADL total score and QUEST total score (r = 0.630, P < 0.001) were also moderate. These associations were unaltered by the inclusion of covariates. Discussion: This study showed that greater tremor severity (TETRAS Performance Item 4) was positively correlated with ADL impairment (TETRAS ADL) and negatively associated with QoL (EQ-5D-5 L and QUEST). TETRAS Performance Item 4 score is a robust predictor of TETRAS ADL total score, and TETRAS Performance Item 4 and TETRAS ADL total scores were robust predictors of the 2 QoL scales. The results demonstrate the value of TETRAS scores as valid endpoints for future clinical trials. Highlights: This real-world study assessed TETRAS scores as predictors of impaired QoL in ET. TETRAS Performance Item 4 and ADL were associated with EQ-5D-5 L and QUEST. TETRAS scores may serve as valid endpoints for future clinical trials.

Validation of a New Patient-Reported Outcome Measure of the Functional Impact of Essential Tremor on Activities of Daily Living.

Background: The Essential Tremor Rating Assessment Scale (TETRAS) is a popular scale for essential tremor (ET), but its activities of daily living (ADL) and performance (P) subscales are based on a structured interview and physical exam. No patient-reported outcome (PRO) scale for ET has been developed according to US regulatory guidelines. Objective: Develop and validate a TETRAS PRO subscale. Methods: Fourteen items, rated 0-4, were derived from TETRAS ADL and structured cognitive interviews of 18 ET patients. Convergent validity analyses of TETRAS PRO versus TETRAS ADL, TETRAS-P, and the Quality of Life in Essential Tremor Questionnaire (QUEST) were computed for 67 adults with ET or ET plus. Test-retest reliability was computed at intervals of 1 and 30 days. The influence of mood (Hospital Anxiety and Depression Scale, HADS) and coping behaviors (Essen Coping Questionnaire, ECQ) was examined with multiple linear regression. Results: TETRAS PRO was strongly correlated (r > 0.7) with TETRAS ADL, TETRAS-P, and QUEST and exhibited good to excellent reliability (Cronbach alpha 95%CI = 0.853-0.926; 30-day test-retest intraclass correlation 95%CI = 0.814-0.921). The 30-day estimate of minimum detectable change (MDC) was 6.6 (95%CI 5.2-8.0). TETRAS-P (rsemipartial = 0.607), HADS depression (rsemipartial = 0.384), and the coping strategy of information seeking and exchange of experiences (rsemipartial = 0.176) contributed statistically to TETRAS PRO in a multiple linear regression (R2 = 0.67). Conclusions: TETRAS PRO is a valid and reliable scale that is influenced strongly by tremor severity, moderately by mood (depression), and minimally by coping skills. The MDC for TETRAS PRO is probably sufficient to detect clinically important change.

Design and Feasibility Analysis of a Smartphone-Based Digital Cognitive Assessment Study in the Framingham Heart Study.

BACKGROUND: Smartphone-based digital technology is increasingly being recognized as a cost-effective, scalable, and noninvasive method of collecting longitudinal cognitive and behavioral data. Accordingly, a state-of-the-art 3-year longitudinal project focused on collecting multimodal digital data for early detection of cognitive impairment was developed. METHODS AND RESULTS: A smartphone application collected 2 modalities of cognitive data, digital voice and screen-based behaviors, from the FHS (Framingham Heart Study) multigenerational Generation 2 (Gen 2) and Generation 3 (Gen 3) cohorts. To understand the feasibility of conducting a smartphone-based study, participants completed a series of questions about their smartphone and app use, as well as sensory and environmental factors that they encountered while completing the tasks on the app. Baseline data collected to date were from 537 participants (mean age=66.6 years, SD=7.0; 58.47% female). Across the younger participants from the Gen 3 cohort (n=455; mean age=60.8 years, SD=8.2; 59.12% female) and older participants from the Gen 2 cohort (n=82; mean age=74.2 years, SD=5.8; 54.88% female), an average of 76% participants agreed or strongly agreed that they felt confident about using the app, 77% on average agreed or strongly agreed that they were able to use the app on their own, and 81% on average rated the app as easy to use. CONCLUSIONS: Based on participant ratings, the study findings are promising. At baseline, the majority of participants are able to complete the app-related tasks, follow the instructions, and encounter minimal barriers to completing the tasks independently. These data provide evidence that designing and collecting smartphone application data in an unsupervised, remote, and naturalistic setting in a large, community-based population is feasible.

Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research.

Most research using digital technologies builds on existing methods for staff-administered evaluation, requiring a large investment of time, effort, and resources. Widespread use of personal mobile devices provides opportunities for continuous health monitoring without active participant engagement. Home-based sensors show promise in evaluating behavioral features in near real time. Digital technologies across these methodologies can detect precise measures of cognition, mood, sleep, gait, speech, motor activity, behavior patterns, and additional features relevant to health. As a neurodegenerative condition with insidious onset, Alzheimer disease and other dementias (AD/D) represent a key target for advances in monitoring disease symptoms. Studies to date evaluating the predictive power of digital measures use inconsistent approaches to characterize these measures. Comparison between different digital collection methods supports the use of passive collection methods in settings in which active participant engagement approaches are not feasible. Additional studies that analyze how digital measures across multiple data streams can together improve prediction of cognitive impairment and early-stage AD are needed. Given the long timeline of progression from normal to diagnosis, digital monitoring will more easily make extended longitudinal follow-up possible. Through the American Heart Association-funded Strategically Focused Research Network, the Boston University investigative team deployed a platform involving a wide range of technologies to address these gaps in research practice. Much more research is needed to thoroughly evaluate limitations of passive monitoring. Multidisciplinary collaborations are needed to establish legal and ethical frameworks for ensuring passive monitoring can be conducted at scale while protecting privacy and security, especially in vulnerable populations.

Comparing Cognitive Tests and Smartphone-Based Assessment in 2 US Community-Based Cohorts.

BACKGROUND: Smartphone-based cognitive assessments have emerged as promising tools, bridging gaps in accessibility and reducing bias in Alzheimer disease and related dementia research. However, their congruence with traditional neuropsychological tests and usefulness in diverse cohorts remain underexplored. METHODS AND RESULTS: A total of 406 FHS (Framingham Heart Study) and 59 BHS (Bogalusa Heart Study) participants with traditional neuropsychological tests and digital assessments using the Defense Automated Neurocognitive Assessment (DANA) smartphone protocol were included. Regression models investigated associations between DANA task digital measures and a neuropsychological global cognitive Z score (Global Cognitive Score [GCS]), and neuropsychological domain-specific Z scores. FHS participants' mean age was 57 (SD, 9.75) years, and 44% (179) were men. BHS participants' mean age was 49 (4.4) years, and 28% (16) were men. Participants in both cohorts with the lowest neuropsychological performance (lowest quartile, GCS1) demonstrated lower DANA digital scores. In the FHS, GCS1 participants had slower average response times and decreased cognitive efficiency scores in all DANA tasks (P<0.05). In BHS, participants in GCS1 had slower average response times and decreased cognitive efficiency scores for DANA Code Substitution and Go/No-Go tasks, although this was not statistically significant. In both cohorts, GCS was significantly associated with DANA tasks, such that higher GCS correlated with faster average response times (P<0.05) and increased cognitive efficiency (all P<0.05) in the DANA Code Substitution task. CONCLUSIONS: Our findings demonstrate that smartphone-based cognitive assessments exhibit concurrent validity with a composite measure of traditional neuropsychological tests. This supports the potential of using smartphone-based assessments in cognitive screening across diverse populations and the scalability of digital assessments to community-dwelling individuals.

Large Language Models in Neurology Research and Future Practice.

Recent advancements in generative artificial intelligence, particularly using large language models (LLMs), are gaining increased public attention. We provide a perspective on the potential of LLMs to analyze enormous amounts of data from medical records and gain insights on specific topics in neurology. In addition, we explore use cases for LLMs, such as early diagnosis, supporting patient and caregivers, and acting as an assistant for clinicians. We point to the potential ethical and technical challenges raised by LLMs, such as concerns about privacy and data security, potential biases in the data for model training, and the need for careful validation of results. Researchers must consider these challenges and take steps to address them to ensure that their work is conducted in a safe and responsible manner. Despite these challenges, LLMs offer promising opportunities for improving care and treatment of various neurologic disorders.

American Football Play and Parkinson Disease Among Men.

Importance: Parkinsonism and Parkinson disease (PD) are known to result from repetitive head impacts from boxing. Repetitive head impacts from American football may also be associated with increased risk of neurodegenerative pathologies that cause parkinsonism, yet in vivo research on the association between football play and PD is scarce and limited by small samples and equivocal findings. Objective: To evaluate the association between football participation and self-reported parkinsonism or PD diagnosis. Design, Setting, and Participants: This cross-sectional study leveraged data from the online Fox Insight study. Participants completed online questionnaires and self-reported whether they currently had a diagnosis of Parkinson disease or parkinsonism by a physician or other health care professional. In November 2020, the Boston University Head Impact Exposure Assessment was launched for data collection on repetitive head impacts. Data used for this manuscript were obtained from the Fox Insight database on June 9, 2022. A total of 1875 men who endorsed playing any organized sport were included. Former athletes were divided into those who participated in football (n = 729 [38.9%]) and those who participated in other sports (reference group). Exposures: Self-reported participation in football, duration and level of football play, age at first exposure. Main Outcomes and Measures: Logistic regression tested associations between PD status and history of football play, duration of football play, highest level played, and age at first exposure, controlling for age, education, history of diabetes or heart disease, body mass index, history of traumatic brain injury with loss of consciousness, and family history of PD. Results: In this sample of 1875 men (mean [SD] age, 67.69 [9.84] years) enriched for parkinsonism or PD (n = 1602 [85.4%]), 729 (38.9%) played football (mean [SD] duration, 4.35 [2.91] years). History of playing football was associated with higher odds of having a parkinsonism or PD diagnosis (odds ratio [OR], 1.61; 95% CI, 1.19-2.17). Among the entire sample, longer duration of play was associated with higher odds of having a parkinsonism or PD diagnosis (OR, 1.12; 95% CI, 1.06-1.19). Among football players, longer duration of football play (OR, 1.12; 95% CI, 1.02-1.23) and higher level of play (OR, 2.93; 95% CI, 1.28-6.73) were associated with higher odds of having parkinsonism or PD. Conclusions and Relevance: In this cross-sectional study of participants enriched for PD, participation in football was associated with higher odds of having a reported parkinsonism or PD diagnosis.

Parkinson's disease - current treatment.

PURPOSE OF REVIEW: The purpose is to review the results and impact of recent studies for current and future treatment of both motor and non-motor symptoms in Parkinson's disease (PD). RECENT FINDINGS: New formulations of levodopa further optimize motor fluctuations, allowing for more on-time and less dyskinesia. On demand apomorphine continues to showcase itself as an effective and tolerable tool for treating motor off-periods. Though there are no clear treatment guidelines for PD-related constipation and sleep related disorders, several new agents for these non-motor symptoms show promising preliminary data. Expiratory muscle strength training may represent a useful and cost-effective strategy to alleviate oropharyngeal dysphagia associated with PD. There is evidence to suggest that the use of shorter pulse width and directional deep brain stimulation leads can results in a greater therapeutic window. SUMMARY: Though no interventions currently exist to significantly modify the disease progression of PD, new studies continue to give insight into optimal symptomatic management. Clinicians should be familiar with expanding the repertoire of tools available to treat the diverse range of symptoms and challenges associated with PD.

Machine Learning in Clinical Trials: A Primer with Applications to Neurology.

We reviewed foundational concepts in artificial intelligence (AI) and machine learning (ML) and discussed ways in which these methodologies may be employed to enhance progress in clinical trials and research, with particular attention to applications in the design, conduct, and interpretation of clinical trials for neurologic diseases. We discussed ways in which ML may help to accelerate the pace of subject recruitment, provide realistic simulation of medical interventions, and enhance remote trial administration via novel digital biomarkers and therapeutics. Lastly, we provide a brief overview of the technical, administrative, and regulatory challenges that must be addressed as ML achieves greater integration into clinical trial workflows.

Global Epidemiology of Movement Disorders: Rare or Underdiagnosed?

In this manuscript, we review the epidemiology of movement disorders including Parkinson's disease (PD), atypical parkinsonism, essential tremor, dystonia, functional movement disorders, tic disorders, chorea, and ataxias. We emphasize age-, sex-, and geography-based incidence and prevalence, as well as notable trends including the rising incidence and prevalence of PD. Given the growing global interest in refining clinical diagnostic skills in recognizing movement disorders, we highlight some key epidemiological findings that may be of interest to clinicians and health systems tasked with diagnosing and managing the health of patients with movement disorders.

Does essential tremor increase risk of cognitive impairment and dementia? Yes.

Essential Tremor (ET), by definition, is a disorder of movement. Yet over the years, epidemiologic, clinical, pathologic, and neuroimaging studies have converged to reveal a cognitive side of ET. The cognitive symptoms in ET are heterogeneous and are likely to reflect heterogeneous underlying mechanisms. In this chapter, we review and synthesize a diverse set of studies from both population-based settings to cohorts with more detailed investigations into cognition to consider the various mechanisms by which cognitive symptoms may emerge in a subset of individuals with ET. As part of our analysis, we consider questions surrounding ET diagnosis and the possibility of comorbid disease as potential factors that, upon closer examination, appear to strengthen the argument in favor of ET as a risk factor for dementia. Importantly, we also consider the clinical relevance of cognitive impairment in ET. While ET is not universally characterized by significant cognitive deficits, the data from epidemiological, cognitive, neuroimaging, and postmortem neuropathologic studies converge to reveal an increased risk for cognitive impairment and dementia among individuals with ET. We conclude by offering directions for future research, and a neurocognitive framework with which to consider existing findings and to use in the design of novel studies dedicated to clarifying the basis, nature, and course of cognitive impairments in ET.

Multimodal deep learning for Alzheimer's disease dementia assessment.

Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis.

A Randomized Controlled Trial of Local Delivery of a Rho Inhibitor (VX-210) in Patients with Acute Traumatic Cervical Spinal Cord Injury.

Acute traumatic spinal cord injury (SCI) can result in severe, lifelong neurological deficits. After SCI, Rho activation contributes to collapse of axonal growth cones, failure of axonal regeneration, and neuronal loss. This randomized, double-blind, placebo-controlled phase 2b/3 study evaluated the efficacy and safety of Rho inhibitor VX-210 (9 mg) in patients after acute traumatic cervical SCI. The study enrolled patients 14-75 years of age with acute traumatic cervical SCIs, C4-C7 (motor level) on each side, and American Spinal Injury Association Impairment Scale (AIS) Grade A or B who had spinal decompression/stabilization surgery commencing within 72 h after injury. Patients were randomized 1:1 with stratification by age (<30 vs. ≥30 years) and AIS grade (A vs. B with sacral pinprick preservation vs. B without sacral pinprick preservation). A single dose of VX-210 or placebo in fibrin sealant was administered topically onto the dura over the site of injury during decompression/stabilization surgery. Patients were evaluated for medical, neurological, and functional changes, and serum was collected for pharmacokinetics and immunological analyses. Patients were followed up for up to 12 months after treatment. A planned interim efficacy-based futility analysis was conducted after ∼33% of patients were enrolled. The pre-defined futility stopping rule was met, and the study was therefore ended prematurely. In the final analysis, the primary efficacy end-point was not met, with no statistically significant difference in change from baseline in upper-extremity motor score at 6 months after treatment between the VX-210 (9-mg) and placebo groups. This work opens the door to further improvements in the design and conduct of clinical trials in acute SCI.

Acute readmission following deep brain stimulation surgery for Parkinson's disease: A nationwide analysis.

INTRODUCTION: Deep brain stimulation (DBS) surgery is an efficacious, underutilized treatment for Parkinson's disease (PD). Studies of DBS post-operative outcomes are often restricted to data from a single center and consider DBS in isolation. National estimates of DBS readmission and post-operative outcomes are needed, as are comparisons to commonly performed surgeries. METHODS: This study used datasets from the 2013 and 2014 Nationwide Readmissions Database (NRD). Our sample was restricted to PD patients discharged alive after hospitalization for DBS surgery. Descriptive analyses examined patient, clinical, hospital and index hospitalization characteristics. The all-cause, non-elective 30-day readmission rate after DBS was calculated, and logistic regression models were built to examine factors associated with readmission. Readmission rates for the most common surgical procedures were calculated and compared to DBS. RESULTS: There were 6058 DBS surgeries for PD in our sample, most often involving a male aged 65 and older, who lived in a high socioeconomic status zip code. DBS patients had an average of four comorbidities. With respect to outcomes, the majority of patients were discharged home (95.3%). Non-elective readmission was rare (4.9%), and was associated with socioeconomic status, comorbidity burden, and teaching hospital status. Much higher acute, non-elective readmission rates were observed for common procedures such as upper gastrointestinal endoscopy (16.2%), colonoscopy (14.0%), and cardiac defibrillator and pacemaker procedures (11.1%). CONCLUSION: Short-term hospitalization outcomes after DBS are generally favorable. Socioeconomic disparities in DBS use persist. Additional efforts may be needed to improve provider referrals for and patient access to DBS.

Mapping holmes tremor circuit using the human brain connectome.

OBJECTIVE: Holmes tremor is a debilitating movement disorder with limited treatment options. Lesions causing Holmes tremor can occur in multiple different brain locations, leaving the neuroanatomical substrate unclear. Here, we test whether lesion locations that cause Holmes tremor map to a connected brain circuit and whether this circuit might serve as a useful therapeutic target. METHODS: Case reports of Holmes tremor caused by focal brain lesions were identified through a systematic literature search. Connectivity between each lesion location and the rest of the brain was computed using resting state functional connectivity magnetic resonance imaging data from 1,000 healthy volunteers. Commonalities across lesion locations were identified. This Holmes tremor circuit was then compared to neurosurgical treatment targets and clinical efficacy. RESULTS: We identified 36 lesions causing Holmes tremor, which were scattered across multiple different brain regions. However, all lesion locations were connected to a common brain circuit with nodes in the red nucleus, thalamus, globus pallidus, and cerebellum. In cases with effective neurosurgical treatment, the treatment target was connected with the lesion location, indicating that a second hit to the same circuit might be beneficial. Commonly used deep brain stimulation targets such as the ventral intermediate nucleus and subthalamic nucleus fell outside our Holmes tremor circuit, whereas the globus pallidus target was close, consistent with published clinical response rates for these targets. INTERPRETATION: Lesions causing Holmes tremor are part of a single connected brain circuit that may serve as an improved therapeutic target. ANN NEUROL 2019;86:812-820.

Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson's disease.

Clinical signs in Parkinson's disease (PD), including parkinsonian gait, are often asymmetric, but mechanisms underlying gait asymmetries in PD remain poorly understood. A translational toolkit, a set of standardized measures to capture gait asymmetries in relevant mouse models and patients, would greatly facilitate research efforts. We validated approaches to quantify asymmetries in placement and timing of limbs in mouse models of parkinsonism and human PD subjects at speeds that are relevant for human walking. In mice, we applied regression analysis to compare left and right gait metrics within a condition. To compare alternation ratios of left and right limbs before and after induction of parkinsonism, we used circular statistics. Both approaches revealed asymmetries in hind- and forelimb step length in a unilateral PD model, but not in bilateral or control models. In human subjects, a similar regression approach showed a step length asymmetry in the PD but not control group. Sub-analysis of cohorts with predominant postural instability-gait impairment and with predominant tremor revealed asymmetries for step length in both cohorts and for swing time only in the former cohort. This translational approach captures asymmetries of gait in mice and patients. Application revealed striking differences between models, and that spatial and temporal asymmetries may occur independently. This approach will be useful to investigate circuit mechanisms underlying the heterogeneity between models.

Identifying therapeutic targets from spontaneous beneficial brain lesions.

Brain damage can occasionally result in paradoxical functional benefit, which could help identify therapeutic targets for neuromodulation. However, these beneficial lesions are rare and lesions in multiple different brain locations can improve the same symptom. Using a technique called lesion network mapping, we show that heterogeneous lesion locations resulting in tremor relief are all connected to common nodes in the cerebellum and thalamus, the latter of which is a proven deep brain stimulation target for tremor. These results suggest that lesion network mapping can identify the common substrate underlying therapeutic lesions and effective therapeutic targets. Ann Neurol 2018;83:153-157.

National randomized controlled trial of virtual house calls for Parkinson disease.

OBJECTIVE: To determine whether providing remote neurologic care into the homes of people with Parkinson disease (PD) is feasible, beneficial, and valuable. METHODS: In a 1-year randomized controlled trial, we compared usual care to usual care supplemented by 4 virtual visits via video conferencing from a remote specialist into patients' homes. Primary outcome measures were feasibility, as measured by the proportion who completed at least one virtual visit and the proportion of virtual visits completed on time; and efficacy, as measured by the change in the Parkinson's Disease Questionnaire-39, a quality of life scale. Secondary outcomes included quality of care, caregiver burden, and time and travel savings. RESULTS: A total of 927 individuals indicated interest, 210 were enrolled, and 195 were randomized. Participants had recently seen a specialist (73%) and were largely college-educated (73%) and white (96%). Ninety-five (98% of the intervention group) completed at least one virtual visit, and 91% of 388 virtual visits were completed. Quality of life did not improve in those receiving virtual house calls (0.3 points worse on a 100-point scale; 95% confidence interval [CI] -2.0 to 2.7 points; p = 0.78) nor did quality of care or caregiver burden. Each virtual house call saved patients a median of 88 minutes (95% CI 70-120; p < 0.0001) and 38 miles per visit (95% CI 36-56; p < 0.0001). CONCLUSIONS: Providing remote neurologic care directly into the homes of people with PD was feasible and was neither more nor less efficacious than usual in-person care. Virtual house calls generated great interest and provided substantial convenience. CLINICALTRIALSGOV IDENTIFIER: NCT02038959. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that for patients with PD, virtual house calls from a neurologist are feasible and do not significantly change quality of life compared to in-person visits. The study is rated Class III because it was not possible to mask patients to visit type.