Movement Disorder Specialists Research Articles

Apomorphine titration with and without anti-emetic pretreatment in patients with Parkinson’s disease experiencing OFF episodes: A modified Delphi panel

IntroductionIn the United States (US), prophylactic treatment with the antiemetic trimethobenzamide has been used before initiating apomorphine therapy. However, US trimethobenzamide stores have been depleted, leaving uncertainty regarding whether antiemetic pretreatment is needed. MethodsThis modified Delphi panel aimed to inform circumstances when apomorphine is initiated without antiemetic pretreatment. During Round 1, a panel of 9 US movement disorder specialists rated the appropriateness of prescribing apomorphine therapy with and without antiemetic pretreatment across 192 patient scenarios and were able to review their scores in relation to other scores. During the Round 2, consensus was defined for each scenario as either strong (>75 % agreement) or moderate (66 % agreement). ResultsThere was strong consensus on 118 of 192 scenario’s (97 as appropriate and 21 as inappropriate), moderate consensus on 29 scenarios, some agreement on 32 scenarios, and lack of agreement on 13 scenarios. In the absence of an antiemetic, there was strong consensus that titration schedules should be flexible and based on dose response. However, the group only reached moderate consensus on the speed of titration, highlighting the need for more systematic information on this area. In the presence of an antiemetic, panelists considered usual initial dosing and flexible titration to be appropriate in most scenarios except for when the patient is already experiencing dopaminergic adverse events. ConclusionsExperts generally reached consensus that apomorphine can usually be prescribed without antiemetic pretreatment. Recommendations described here reflect the areas of greatest agreement among a panel of experts based on current available evidence.

Machine learning model comparison for freezing of gait prediction in advanced Parkinson's disease.

Freezing of gait (FOG) is a paroxysmal motor phenomenon that increases in prevalence as Parkinson's disease (PD) progresses. It is associated with a reduced quality of life and an increased risk of falls in this population. Precision-based detection and classification of freezers are critical to developing tailored treatments rooted in kinematic assessments. This study analyzed instrumented stand-and-walk (SAW) trials from advanced PD patients with STN-DBS. Each patient performed two SAW trials in their OFF Medication-OFF DBS state. For each trial, gait summary statistics from wearable sensors were analyzed by machine learning classification algorithms. These algorithms include k-nearest neighbors, logistic regression, naïve Bayes, random forest, and support vector machines (SVM). Each of these models were selected for their high interpretability. Each algorithm was tasked with classifying patients whose SAW trials MDS-UPDRS FOG subscore was non-zero as assessed by a trained movement disorder specialist. These algorithms' performance was evaluated using stratified five-fold cross-validation. A total of 21 PD subjects were evaluated (average age 64.24 years, 16 males, mean disease duration of 14 years). Fourteen subjects had freezing of gait in the OFF MED/OFF DBS. All machine learning models achieved statistically similar predictive performance (p < 0.05) with high accuracy. Analysis of random forests' feature estimation revealed the top-ten spatiotemporal predictive features utilized in the model: foot strike angle, coronal range of motion [trunk and lumbar], stride length, gait speed, lateral step variability, and toe-off angle. These results indicate that machine learning effectively classifies advanced PD patients as freezers or nonfreezers based on SAW trials in their non-medicated/non-stimulated condition. The machine learning models, specifically random forests, not only rely on but utilize salient spatial and temporal gait features for FOG classification.

Social Interactions and Comprehensive Education Programs: What the Society Related to Parkinson's Disease Wants in the Context of Iran: Content Analysis and Delphi Approach

Background: The physical and psychological symptoms of Parkinson's disease can disrupt patients' social lives, leading them to withdraw from social situations. Objectives: The objective of the present study is to identify the social needs and priorities of patients with Parkinson's disease from the perspectives of patients, family caregivers, and health care providers. Methods: The present study employed a qualitative content analysis method to collect data to identify the needs of patients with Parkinson's disease. Semi-structured interviews were conducted with 28 participants using a purposive sampling strategy with maximum diversity in Tehran in 2023. Data analysis was performed using the conventional content analysis approach based on Granheim and Lundman's model. A two-stage Delphi technique was used to identify patients' priorities with 53 participants. Results: The 28 participants included 11 patients (7 male, 4 female, mean age = 66.27), 11 family caregivers (7 daughters, 3 spouses, 1 son, mean age = 43.81), 4 nurses, and 2 physicians. Three main categories and 12 subcategories were extracted. In the category of "Interactionism by leaving unwanted isolation," the subcategories identified were maintaining and promoting social interactions, maintaining aspects of the job and continuing some professional skills, voluntary membership in groups and institutional participation, and participation in social activities. The category "Continuity of healthcare services delivery" included four subcategories: Continued access to movement disorder specialists, access to coordinated multidisciplinary services, access to supporting organizations and associations, and appropriate insurance coverage. The category "Individual-oriented and community-oriented advocacy programs" included four subcategories: Financial support, social belonging and effective communication, self-care, and comprehensive education programs with multiple target groups. The prioritization was completed after two Delphi steps with a high agreement of 86.90% from 16 patients, 14 family caregivers, and 23 health care providers from eight disciplines. Conclusions: The results of the study show that patients with Parkinson's disease experience various social needs. Since the nature of Parkinson's disease affects social interactions, patients and their caregivers view social interactions as the missing link to addressing their social needs. Meanwhile, health care providers prioritize educating patients and families and holding specialized Parkinson's disease courses. Policymakers should consider necessary social support programs for these patients and focus on the specialized training of healthcare providers in the field of Parkinson's disease, in addition to providing appropriate care, support, and social services.

Cannabis Use in Parkinson’s Disease: Patient Access to Medical Cannabis and Physician Perspective on Product Safety

The rate of medical cannabis use has increased in parallel with the number of states legalizing its use. Parkinson’s disease (PD) patients are of particular concern due to their higher cannabis use rate than in the general US population (25-40% PD patient cannabis users vs. ~18% in the general population), as well as their susceptibility to environmental contaminants in cannabis, including pesticides, toxic elements, solvents, microbes, and mycotoxins. In order to address the complex nature of this industry, we examined the changes in PD-related qualifying conditions in the U.S. from 2019 to 2023. We also conducted an online survey to gain insight into the knowledge, risk perceptions, and opinions regarding medical cannabis and contamination issues from physicians who treated PD patients. The number of states including PD-related qualifying conditions increased over the past 5 years from 28 to 36 states. These conditions included PD (increasing from 14 to 16 states), muscle spasms (14 to 24), anxiety (1 to 5), and pain (17 to 35). State-by-state comparisons revealed high variability in the language used to describe the different qualifying conditions. Online surveys were sent out to 45 neurologists and movement disorder specialists who primarily treated PD patients. The response rate was 44% from nine states (AZ, CA, FL, MA, MN, WI, PA, IL, and NM). When asked if they were aware of any contaminants in cannabis products, we found that 65% of the physicians were unaware of any contaminants commonly found in cannabis and only 25%, 15%, and 15% of them were aware of pesticide, toxic element, and solvent contaminants, respectively. In their free-text opinion response on the health impact of cannabis-borne contaminants, “long-term effect” (35%) and “comorbidities and PD prognosis” (40%) were identified as the two most common themes. These results point to the need for further regulatory deliberation regarding risks and susceptibility to cannabis contaminants. Additionally, education is needed to inform physicians on cannabis safety issues. Further research will identify the implementation strategies to reduce contaminant exposure and protect patient health.

Using sustained vowels to identify patients with mild Parkinson's disease in a Chinese dataset.

Parkinson's disease (PD) is the second most common neurodegenerative disease and affects millions of people. Accurate diagnosis and subsequent treatment in the early stages can slow down disease progression. However, making an accurate diagnosis of PD at an early stage is challenging. Previous studies have revealed that even for movement disorder specialists, it was difficult to differentiate patients with PD from healthy individuals until the average modified Hoehn-Yahr staging (mH&Y) reached 1.8. Recent researches have shown that dysarthria provides good indicators for computer-assisted diagnosis of patients with PD. However, few studies have focused on diagnosing patients with PD in the early stages, specifically those with mH&Y ≤ 1.5. We used a machine learning algorithm to analyze voice features and developed diagnostic models for differentiating between healthy controls (HCs) and patients with PD, and for differentiating between HCs and patients with mild PD (mH&Y ≤ 1.5). The models were independently validated using separate datasets. Our results demonstrate that, a remarkable diagnostic performance of the model in identifying patients with mild PD (mH&Y ≤ 1.5) and HCs, with area under the ROC curve 0.93 (95% CI: 0.851.00), accuracy 0.85, sensitivity 0.95, and specificity 0.75. The results of our study are helpful for screening PD in the early stages in the community and primary medical institutions where there is a lack of movement disorder specialists and special equipment.

A survey-based approach on restless legs syndrome: practices and perspectives among Italian neurologists.

Restless Legs Syndrome (RLS) is a widely prevalent and complex neurological disorder. Despite notable advancements in managing RLS, the disorder continues to face challenges related to its recognition and management. This study seeks to gain comprehensive insights into the knowledge and clinical practices among Italian neurologists regarding RLS diagnosis, management, and treatment, comparing approaches among general neurologists, movement disorder specialists, and sleep experts. Members of the Italian Society of Neurology, the Italian Society of Parkinson and Movement Disorders, and the Italian Association of Sleep Medicine were invited to participate in a 19-question online survey. Among the 343 surveyed neurologists, 60% categorized RLS as a "sleep-related movement disorder." Forty% indicated managing 5-15 RLS patients annually, with sleep specialists handling the highest patient volume. Of note, only 34% adhered strictly to all five essential diagnostic criteria. The majority (69%) favored low-dosage dopamine agonists as their first-line treatment, with movement disorder specialists predominantly endorsing this approach, while sleep experts preferred iron supplementation. Regular screening for iron levels was widespread (91%), with supplementation typically guided by serum iron alterations. In cases of ineffective initial treatments, escalating dopamine agonist dosage was the preferred strategy (40%). These findings underscore a lack of a clear conceptualization of RLS, with a widespread misconception of the disorder as solely a movement disorder significantly influencing treatment approaches. Disparities in RLS understanding across neurology subspecialties underscore the necessity for improved diagnostic accuracy, targeted educational initiatives, and management guidelines to ensure consistent and effective RLS management.

Improvement by Medication Less than Expected in Parkinson's Disease: Blinded Evaluation of Levodopa Response.

The latest Movement Disorder Society (MDS) diagnostic criteria require a good and sustained response to medication to get a diagnosis of Parkinson's disease, PD. The aim of this study was to evaluate levodopa response in a group of patients with probable PD, diagnosed by movement disorder specialists. An acute levodopa challenge test (LDCT) was performed after pausing the dopaminergic medication for 6 half-times. The motor part of the Unified Parkinson's Disease Rating Scale was performed in the OFF-state and after LDCT (ON). A good effect was defined as >30% improvement. A video-protocol was used to secure standardized motor examination with blinded assessments of the UPDRS-III OFF and ON. An age-matched group of control subjects (CS) was included but did not go through LDCT. All participants were evaluated with Montreal Cognitive Assessment (MoCA) and Beck's Depression Inventory (BDI). In the statistical analysis, 37 patients were included. Twenty-one patients showed an improvement ≤30%, while 16 patients showed an improvement >30%. LDCT showed an overall mean improvement of 27.3% of motor UPDRS. In 43.2%, there was a discrepancy between the effect seen with the LDCT and the patients' self-perceived medicine evaluation. Patients with PD had a significantly lower MoCA score and more depressive symptoms compared to CS. We showed an acute effect of levodopa using LDCT that was around 30% improvement. While it lends support to the use of this limit in the MDS diagnostic criteria, an acute effect of less than 30% should be considered acceptable in some patients. Our study highlights a discrepancy in the objective measure of medicine effect on motor symptoms and the patient's subjective evaluation.

Parkinson Disease Genetics Extended to African and Hispanic Ancestries in the VA Million Veteran Program.

Nearly all genetic analyses of Parkinson disease (PD) have been in populations of European ancestry. We sought to test the ability of a machine learning method to extract accurate PD diagnoses from an electronic medical record (EMR) system, to see whether genetic variants identified in European populations generalize to individuals of African and Hispanic ancestries, and to compare the rates of PD across ancestries. A machine learning method using natural language processing was applied to EMRs of US veterans participating in the VA Million Veteran Program (MVP) to identify individuals with PD. These putative cases were vetted via blind chart review by a movement disorder specialist. A polygenic risk score (PRS) of 90 established genetic variants whose genotypes were imputed from a customized Axiom Biobank Array was evaluated in different case groups. The EMR prediction scores had a distinct trimodal distribution, with 97% of the high group and only 30% of the middle group having a credible diagnosis of PD. Using the 3,542 cases from the high group matched 4:1 to controls, the PRS was highly predictive in individuals of European ancestry (n = 3,137 cases; OR = 1.82; p = 8.01E-48), and nearly identical effect sizes were seen in individuals of African (n = 184; OR = 2.07; p = 3.4E-4) and Hispanic ancestries (n = 221; OR = 2.13; p = 3.9E-6). The PRS was much less predictive for the 2,757 European ancestry cases who had an ICD code for PD but for whom the machine learning method had a lower confidence in their diagnosis. No novel ancestry-specific genetic variants were identified. Individuals with African ancestry had one-quarter the rate of PD compared with European or Hispanic ancestries aged 60-70 years and one half the rate in the 70-80 years age range. African American cases had a higher proportion of their DNA originating in Europe compared with African American controls. Machine learning can reliably classify PD using data from a large EMR. Larger studies of non-European populations are required to confirm the generalizability of PD risk variants identified in populations of European ancestry and the increased risk coming from a higher proportion of European DNA in African Americans.

Movement disorders following mechanical thrombectomy resulting in ischemic lesions of the basal ganglia: An emerging clinical entity.

Post-stroke movement disorders (PMDs) following ischemic lesions of the basal ganglia (BG) are a known entity, but data regarding their incidence are lacking. Ischemic strokes secondary to proximal middle cerebral artery (MCA) occlusion treated with thrombectomy represent a model of selective damage to the BG. The aim of this study was to assess the prevalence and features of movement disorders after selective BG ischemia in patients with successfully reperfused acute ischemic stroke (AIS). We enrolled 64 consecutive subjects with AIS due to proximal MCA occlusion treated with thrombectomy. Patients were clinically evaluated by a movement disorders specialist for PMDs onset at baseline, and after 6 and 12 months. None of the patients showed an identifiable movement disorder in the subacute phase of the stroke. At 6 and 12 months, respectively, 7/25 (28%) and 7/13 (53.8%) evaluated patients developed PMDs. The clinical spectrum of PMDs encompassed parkinsonism, dystonia and chorea, either isolated or combined. In most patients, symptoms were contralateral to the lesion, although a subset of patients presented with bilateral involvement and prominent axial signs. Post-stroke movement disorders are not uncommon in long-term follow-up of successfully reperfused AIS. Follow-up conducted by a multidisciplinary team is strongly advisable in patients with selective lesions of the BG after AIS, even if asymptomatic at discharge.

Standardizing default electronic health record tools to improve safety for hospitalized patients with Parkinson's disease.

Electronic Health Record (EHR) systems are often configured to address challenges and improve patient safety for persons with Parkinson's disease (PWP). For example, EHR systems can help identify Parkinson's disease (PD) patients across the hospital by flagging a patient's diagnosis in their chart, preventing errors in medication and dosing through the use of clinical decision support, and supplementing staff education through care plans that provide step-by-step road maps for disease-based care of a specific patient population. However, most EHR-based solutions are locally developed and, thus, difficult to scale widely or apply uniformly across hospital systems. In 2020, the Parkinson's Foundation, a national and international leader in PD research, education, and advocacy, and Epic, a leading EHR vendor with more than 35% market share in the United States, launched a partnership to reduce risks to hospitalized PWP using standardized EHR-based solutions. This article discusses that project which included leadership from physician informaticists, movement disorders specialists, hospital quality officers, the Parkinson's Foundation and members of the Parkinson's community. We describe the best practice solutions developed through this project. We highlight those that are currently available as standard defaults or options within the Epic EHR, discuss the successes and limitations of these solutions, and consider opportunities for scalability in environments beyond a single EHR vendor. The Parkinson's Foundation and Epic launched a partnership to develop best practice solutions in the Epic EHR system to improve safety for PWP in the hospital. The goal of the partnership was to create the EHR tools that will have the greatest impact on outcomes for hospitalized PWP.

Interdisciplinary network care collaboration in Parkinson’s disease: a baseline evaluation in Germany

BackgroundThe strengthening of interdisciplinary care collaboration in Parkinson's disease is taking on increasing importance in daily medical routine. Therefore, care providers worldwide are organizing themselves in disease-specific regional network structures. However, the existing networks are heterogeneous, and the driving key players are yet unidentified.ObjectivesTo systematically identify key factors of the composition of health care professionals, who are initially interested in the development of a Parkinson network for interdisciplinary care collaboration, their motivation, and expectations, we conducted a basic evaluation in three different German regions covering a total number of 23,405 people with Parkinson’s.MethodsA specially developed semi-open questionnaire focusing on socio-demographic information, ways of contact, interdisciplinary collaboration, and connectedness was used. Statistical analyses were performed based on a predesigned codebook.ResultsThe most crucial professions were outpatient therapists (physio-, occupational-, speech therapists) (36.7%), average case load of 10.1 patients/3 months and inpatient movement disorder specialists (21.1%), average case load of 197.4 patients/3 months. Before implementation of PD networks, 48.9% of outpatient therapists did not have any contact with neurologists. 58.9% of caregivers considered the current frequency of collaboration to be insufficient. The lack of political support as well as a lack of time were identified as main hurdles to increased collaboration.ConclusionThe identified driving forces in strengthened care collaboration are assigned to different healthcare sectors. This makes networks which provide tools for specialized education and interdisciplinary, cross-sectoral communication indispensable. For an areawide rollout, a rethinking of political frameworks towards network care is strongly necessary.

Classifying Tremor Dominant and Postural Instability and Gait Difficulty Subtypes of Parkinson's Disease from Full-Body Kinematics.

Characterizing motor subtypes of Parkinson's disease (PD) is an important aspect of clinical care that is useful for prognosis and medical management. Although all PD cases involve the loss of dopaminergic neurons in the brain, individual cases may present with different combinations of motor signs, which may indicate differences in underlying pathology and potential response to treatment. However, the conventional method for distinguishing PD motor subtypes involves resource-intensive physical examination by a movement disorders specialist. Moreover, the standardized rating scales for PD rely on subjective observation, which requires specialized training and unavoidable inter-rater variability. In this work, we propose a system that uses machine learning models to automatically and objectively identify some PD motor subtypes, specifically Tremor-Dominant (TD) and Postural Instability and Gait Difficulty (PIGD), from 3D kinematic data recorded during walking tasks for patients with PD (MDS-UPDRS-III Score, 34.7 ± 10.5, average disease duration 7.5 ± 4.5 years). This study demonstrates a machine learning model utilizing kinematic data that identifies PD motor subtypes with a 79.6% F1 score (N = 55 patients with parkinsonism). This significantly outperformed a comparison model using classification based on gait features (19.8% F1 score). Variants of our model trained to individual patients achieved a 95.4% F1 score. This analysis revealed that both temporal, spectral, and statistical features from lower body movements are helpful in distinguishing motor subtypes. Automatically assessing PD motor subtypes simply from walking may reduce the time and resources required from specialists, thereby improving patient care for PD treatments. Furthermore, this system can provide objective assessments to track the changes in PD motor subtypes over time to implement and modify appropriate treatment plans for individual patients as needed.

Upper Extremity Dystonia Features in People With Spastic Cerebral Palsy.

Dystonia in cerebral palsy (CP) is debilitating and common, but underdiagnosed, especially when coexistent with spasticity. With dedicated research-based assessment, dystonia is found in most people with spastic CP but is only clinically diagnosed in the minority. To begin addressing the high rates of dystonia underdiagnosis in this population, we determined the key feature experts use to assess upper extremity dystonia in people with spastic CP. In this prospective cohort study, 3 pediatric movement disorder specialists assessed upper extremity dystonia in neurologic examination videos of people with spastic CP and isolated periventricular leukomalacia (PVL) on brain MRI (i.e., those with a brain injury pattern typical for spastic CP). Dystonia severity was rated using the 10-point Global Dystonia Severity Rating Scale, first by each expert independently and then again after consensus-building discussion. Conventional content analysis of these discussions revealed salient features ("codes") that experts used to assess upper extremity dystonia. Code frequency distributions were compared between dystonia severity categories using χ2 tests. We identified 96 people with spastic CP with isolated PVL on brain MRI seen in the St. Louis Children's Hospital CP Center between 2005 and 2018. Of them, 26 people were able and willing to be recorded while doing a standardized set of upper extremity examination maneuvers (age 4-25 years; 28% nonambulatory, 77% White). When assessing their videos, experts cited the "hand" less often and "shoulder" more often with increasing dystonia severity (p < 0.005, χ2 test). "Mirror movements" and the "hand open/close" examination maneuver were cited significantly more frequently in videos when experts were attempting to distinguish between no dystonia and mild dystonia (p < 0.005). Expert clinicians use distinct movement features to assess upper extremity dystonia in people with spastic CP and PVL. Attention to involuntary shoulder (vs hand) movements can help gauge dystonia severity. Differentiation between mirror movements and dystonia, particularly during the hand open/close examination maneuver, may help identify mild dystonia. These results can help guide upper extremity dystonia assessment in people with spastic CP, thus potentially helping mitigate dystonia underdiagnosis.

Risk of hospitalization in synucleinopathies and impact of psychosis.

Few studies have investigated the risk of hospitalization among patients with synucleinopathies (Parkinson disease, Dementia with Lewy Bodies, Parkinson disease dementia, Multiple System Atrophy) with associated psychosis and the impact of antipsychotic treatments on hospital admissions and duration of the stay. To determine the risk of hospitalization among patients with synucleinopathies and in patients with associated psychosis. To evaluate the impact of antipsychotic treatments on hospital admission of patients with synucleinopathies and psychosis in an incident cohort study in Olmsted County, Minnesota (MN). We used the Rochester Epidemiology Project (REP) to define an incident cohort of patients with clinically diagnosed synucleinopathies (1991-2010) in Olmsted County, MN. A movement disorder specialist reviewed all medical records to confirm the clinical diagnosis of synucleinopathies using the NINDS/NIMH unified diagnostic criteria. We included 416 incident cases of clinically diagnosed synucleinopathies from 2,669 hospitalizations. 409 patients (98.3%) were admitted to the hospital at least once for any cause after the onset of parkinsonism. The median number of hospitalizations for a single patient was 5. In total, 195 (46.9%) patients met the criteria for psychosis: patients with psychosis had a 49% (HR = 1.49, p < 0.01) increased risk of hospitalization compared to patients without psychosis. Among patients with psychosis, 76 (39%) received antipsychotic medication. Treatment with antipsychotic medications did not affect the risk of hospitalization (HR = 0.93, p = 0.65). The median length of hospitalization among the entire cohort was 1 (IQR 0-4) day. There was no difference between hospitalization length for patients with no psychosis and patients with active psychosis (RR = 1.08, p = 0.43) or patients with resolved psychosis (RR = 0.79, p = 0.24). Psychosis increases the risk of hospitalization in patients with clinically defined synucleinopathies; however, it does not affect the length of hospital stays in our cohort. Antipsychotic treatment does not affect the risk of hospitalization in our study.

40-Year Incidence of Early-Onset Parkinson's Disease in Southeast Minnesota.

Parkinson's disease (PD) most commonly surfaces at middle age. An earlier onset is named early-onset Parkinson's disease (EOPD), but the exact definition is a matter of ongoing scientific debate. To investigate 40-year EOPD incidence trends in a population-based cohort of parkinsonism in Olmsted County, Minnesota. We used the Rochester Epidemiology Project (REP) to identify all incident EOPD cases in Olmsted County, 1976-2015. A movement-disorder specialist reviewed all cases to confirm the EOPD diagnosis. For EOPD definition, we used two age cut-offs: motor-symptom onset at or before 50 and 55 years. EOPD incidence was 1.43/100,000 person-years for ≤55 and 0.55/100,000 for ≤50 years. Men had a higher incidence in both groups [1.84 vs. 1.03 (p = 0.04); and 0.70 vs. 0.40 (p = 0.24), respectively]. EOPD incidence of patients with motor-symptom onset before age 55 increased from 1.02/100.000 person-year 1976-1985, to 1.32/100.000 person-year 2006-2015. A similar trend was observed when ≤50 years cut-off was used (0.28/100,000 person-years 1976-1985, to 0.59/100,000 person-year 2006-2015). However, negative binomial regression found no significant change in incidence per 10 years (RR = 1.04 and 1.24 in the two groups). Incidence was consistently higher in men than women. Median time from EOPD-symptom onset to death was shorter in the EOPD ≤55 group (21.9 years) compared to the EOPD ≤50 group (25.6 years). We observed an increased trend in the incidence of EOPD with both cut-off ages. Overall, incidence of EOPD was 1.43 (≤55) and 0.55 (≤50) cases per 100,000 person-years, higher in men.

The Muddle of Myoclonus: Many Guises, 2 Disciplines, Consensus Needed.

Myoclonus is often approached in different ways by epileptologists and movement disorder specialists, leading to confusion in the literature. Multiplicity and inconsistency over the past 2 centuries resulted in a lack of precision and ambiguity of the terminology. We show that this is a current problem in which one phenomenon has been described with many terms and vice versa. Of more importance, we discuss the conceptualization of myoclonus from perspectives of both fields and focus on the borderland that exists, especially in the spectrum of cortical and epileptic myoclonus. By giving 2 examples, we illustrate the conundrum: the spectrum of progressive myoclonus epilepsies and progressive myoclonic ataxias and "cortical tremor" observed in familial cortical myoclonic tremor with epilepsy or familial adult myoclonic epilepsy. We attempt to facilitate to bridge these subspecialties and form the base for a uniform understanding to take this issue forward toward future classifications, discussions, and scientific research.

User and Usability Testing of a Web-Based Genetics Education Tool for Parkinson Disease: Mixed Methods Study

Background Genetic testing is essential to identify research participants for clinical trials enrolling people with Parkinson disease (PD) carrying a variant in the glucocerebrosidase (GBA) or leucine-rich repeat kinase 2 (LRRK2) genes. The limited availability of professionals trained in neurogenetics or genetic counseling is a major barrier to increased testing. Telehealth solutions to increase access to genetics education can help address issues around counselor availability and offer options to patients and family members. Objective As an alternative to pretest genetic counseling, we developed a web-based genetics education tool focused on GBA and LRRK2 testing for PD called the Interactive Multimedia Approach to Genetic Counseling to Inform and Educate in Parkinson’s Disease (IMAGINE-PD) and conducted user testing and usability testing. The objective was to conduct user and usability testing to obtain stakeholder feedback to improve IMAGINE-PD. Methods Genetic counselors and PD and neurogenetics subject matter experts developed content for IMAGINE-PD specifically focused on GBA and LRRK2 genetic testing. Structured interviews were conducted with 11 movement disorder specialists and 13 patients with PD to evaluate the content of IMAGINE-PD in user testing and with 12 patients with PD to evaluate the usability of a high-fidelity prototype according to the US Department of Health and Human Services Research-Based Web Design &amp; Usability Guidelines. Qualitative data analysis informed changes to create a final version of IMAGINE-PD. Results Qualitative data were reviewed by 3 evaluators. Themes were identified from feedback data of movement disorder specialists and patients with PD in user testing in 3 areas: content such as the topics covered, function such as website navigation, and appearance such as pictures and colors. Similarly, qualitative analysis of usability testing feedback identified additional themes in these 3 areas. Key points of feedback were determined by consensus among reviewers considering the importance of the comment and the frequency of similar comments. Refinements were made to IMAGINE-PD based on consensus recommendations by evaluators within each theme at both user testing and usability testing phases to create a final version of IMAGINE-PD. Conclusions User testing for content review and usability testing have informed refinements to IMAGINE-PD to develop this focused, genetics education tool for GBA and LRRK2 testing. Comparison of this stakeholder-informed intervention to standard telegenetic counseling approaches is ongoing.

Identification of genetic risk loci and causal insights associated with Parkinson's disease in African and African admixed populations: a genome-wide association study

An understanding of the genetic mechanisms underlying diseases in ancestrally diverse populations is an important step towards development of targeted treatments. Research in African and African admixed populations can enable mapping of complex traits, because of their genetic diversity, extensive population substructure, and distinct linkage disequilibrium patterns. We aimed to do a comprehensive genome-wide assessment in African and African admixed individuals to better understand the genetic architecture of Parkinson's disease in these underserved populations. We performed a genome-wide association study (GWAS) in people of African and African admixed ancestry with and without Parkinson's disease. Individuals were included from several cohorts that were available as a part of the Global Parkinson's Genetics Program, the International Parkinson's Disease Genomics Consortium Africa, and 23andMe. A diagnosis of Parkinson's disease was confirmed clinically by a movement disorder specialist for every individual in each cohort, except for 23andMe, in which it was self-reported based on clinical diagnosis. We characterised ancestry-specific risk, differential haplotype structure and admixture, coding and structural genetic variation, and enzymatic activity. We included 197 918 individuals (1488 cases and 196 430 controls) in our genome-wide analysis. We identified a novel common risk factor for Parkinson's disease (overall meta-analysis odds ratio for risk of Parkinson's disease 1·58 [95% CI 1·37-1·80], p=2·397 × 10-14) and age at onset at the GBA1 locus, rs3115534-G (age at onset β=-2·00 [SE=0·57], p=0·0005, for African ancestry; and β=-4·15 [0·58], p=0·015, for African admixed ancestry), which was rare in non-African or non-African admixed populations. Downstream short-read and long-read whole-genome sequencing analyses did not reveal any coding or structural variant underlying the GWAS signal. The identified signal seems to be associated with decreased glucocerebrosidase activity. Our study identified a novel genetic risk factor in GBA1 in people of African ancestry, which has not been seen in European populations, and it could be a major mechanistic basis of Parkinson's disease in African populations. This population-specific variant exerts substantial risk on Parkinson's disease as compared with common variation identified through GWAS and it was found to be present in 39% of the cases assessed in this study. This finding highlights the importance of understanding ancestry-specific genetic risk in complex diseases, a particularly crucial point as the Parkinson's disease field moves towards targeted treatments in clinical trials. The distinctive genetics of African populations highlights the need for equitable inclusion of ancestrally diverse groups in future trials, which will be a valuable step towards gaining insights into novel genetic determinants underlying the causes of Parkinson's disease. This finding opens new avenues towards RNA-based and other therapeutic strategies aimed at reducing lifetime risk of Parkinson's disease. The Global Parkinson's Genetics Program, which is funded by the Aligning Science Across Parkinson's initiative, and The Michael J Fox Foundation for Parkinson's Research.

Association of Caregiver Depression Risk With Patient Outcomes in Parkinson Disease

Caregivers are integral to Parkinson disease (PD) care, but little information exists regarding how caregivers impact patient outcomes. To assess the association between caregivers reporting depression symptoms and patient quality of life (QOL), emergency department (ED) visits, and hospitalizations. This retrospective cohort study was conducted at 15 Parkinson's Foundation Centers of Excellence within the US. The Parkinson's Foundation Parkinson Outcomes Project registry was used to collect baseline data from January 1, 2016, to December 31, 2018, with subsequent annual study visits through July 31, 2020. Data were analyzed from August 5, 2020, to June 9, 2023. A convenience sample of 454 patients with PD and their caregivers was recruited during routine clinical visits with movement disorder specialists. Patients with a physician diagnosis of idiopathic PD who lived at home and had 1 or more follow-up study visits were included. Caregiver depression symptoms using the Center for Epidemiologic Studies Depression Scale. Patient health-related QOL (measured by the 39-item Parkinson Disease Questionnaire), number of annual ED visits, and number of annual hospitalizations were measured. The independent association between caregivers reporting depression symptoms and patient outcomes was assessed using linear mixed-effects and Poisson regression models. The a priori hypotheses were that a greater number of depression symptoms reported via the Center for Epidemiologic Studies Depression Scale would be associated with worse patient QOL and a greater number of ED visits and hospitalizations. Among 454 patient-caregiver dyads (patients: mean [SD] age, 67.3 [8.4] years; 320 men [70.5%]; caregivers: mean [SD] age, 65.9 [8.7] years; 326 women [71.8%]), the mean (SD) follow-up was 2.0 (1.4) study visits. Greater depression symptoms among caregivers were associated with worse patient QOL as measured by the Parkinson Disease Questionnaire (mean [SD] score, 33.78 [17.71], on a scale of 0-100, with higher scores indicating worse QOL, among patients with caregivers who had depression symptoms vs 24.50 [14.19] among patients with caregivers who did not have depression symptoms; β = 0.43; 95% CI, 0.28-0.58; P < .001) and more annual ED visits (β = 0.02; 95% CI, 0 to 0.04; P = .03) but not more hospitalizations (β = 0.02; 95% CI, -0.01 to 0.03; P = .10). In this cohort study, patients with PD who had caregivers at higher risk of depression were more likely to have worse QOL and higher ED use than patients who had caregivers not at higher risk of depression. Additional caregiving resources and interventions to reduce caregiver depression symptoms could potentially improve patient outcomes.

Pattern and frequency of involuntary movements: hospital-based study

BackgroundThis study aims to detect pattern and frequency and risk factors of movement disorders in Assiut university hospital.MethodsThis is a hospital-based study, all patients with involuntary movements, attending Assiut university hospital; inpatient and outpatient clinics.ResultsMost of cases were males (58.5%), within the age group between 20 and 60 years (59.2%) and illiterate (62.8%). In our study parkinsonism was the most common movement disorder (32.1%), followed by chorea (22.5%), then dystonia (17.8%).ConclusionsMovement disorders are common cause of disability of patients in our study, with high frequency attending our hospital inpatient department and outpatient clinic, highlighting the need for future specialized movement disorder clinic in our hospital, promoting health care and management of patients. With the need of further studies regarding management of such patients.