Movement Disorder Specialists Research Articles

Design of a virtual longitudinal observational study in Parkinson's disease (AT-HOME PD).

ObjectiveThe expanding power and accessibility of personal technology provide an opportunity to reduce burdens and costs of traditional clinical site‐centric therapeutic trials in Parkinson’s disease and generate novel insights. The value of this approach has never been more evident than during the current COVID‐19 pandemic. We sought to (1) establish and implement the infrastructure for longitudinal, virtual follow‐up of clinical trial participants, (2) compare changes in smartphone‐based assessments, online patient‐reported outcomes, and remote expert assessments, and (3) explore novel digital markers of Parkinson’s disease disability and progression.MethodsParticipants from two recently completed phase III clinical trials of inosine and isradipine enrolled in Assessing Tele‐Health Outcomes in Multiyear Extensions of Parkinson’s Disease trials (AT‐HOME PD), a two‐year virtual cohort study. After providing electronic informed consent, individuals complete annual video visits with a movement disorder specialist, smartphone‐based assessments of motor function and socialization, and patient‐reported outcomes online.ResultsFrom the two clinical trials, 226 individuals from 42 states in the United States and Canada enrolled. Of these, 181 (80%) have successfully downloaded the study’s smartphone application and 161 (71%) have completed patient‐reported outcomes on the online platform.InterpretationIt is feasible to conduct a large‐scale, international virtual observational study following the completion of participation in brick‐and‐mortar clinical trials in Parkinson’s disease. This study, which brings research to participants, will compare established clinical endpoints with novel digital biomarkers and thereby inform the longitudinal follow‐up of clinical trial participants and design of future clinical trials.

Magnetic resonance imaging evaluation of nigrosome 1 and neuromelanin can assist Parkinson's disease diagnosis, but requires an expert neuroradiologist

IntroductionParkinson's disease (PD) is the second most common neurodegenerative disease. However, the rate of misdiagnosis remains high, even at specialized movement disorder centers. PurposeTo assess the accuracy of nigrosome 1 and midbrain neuromelanin evaluation in the diagnosis of PD, and to identify possible differences in diagnostic accuracy between neuroradiologists of different experience levels in analyzing these structures. MethodsA case-control study was conducted between April 2017 and January 2019. We prospectively evaluated 41 PD patients and 21 control individuals. Participants underwent axial, T2*-weighted, multi-echo gradient echo (GRE), and susceptibility-weighted imaging phase (SWIp) magnetic resonance imaging (MRI) sequences to evaluate nigrosome 1 and axial, T1-weighted, turbo spin-echo magnetization transfer contrast (MTC) MRI sequences to evaluate midbrain neuromelanin. All MRI sequences were acquired at 3.0 T. The images were analyzed by two experienced neuroradiologists, one with and one without expertise in nigrosome 1 and neuromelanin imaging. The sensitivity, specificity, and accuracy of the diagnoses were calculated between PD patients vs. healthy participants and between the two neuroradiologists. ResultsThe sensitivity and specificity of each imaging sequence for PD diagnosis were as follows: multi-echo, 100% and 86%; SWIp, 91% and 88%; and T1 MTC, 90% and 93%, respectively. The accuracy of clinical PD diagnosis was higher for the expert neuroradiologist compared to the neuroradiologist lacking expertise. ConclusionNigrosome 1 and midbrain neuromelanin represent useful tools for PD diagnosis. However, these structures should be evaluated by experienced neuroradiologists in order to ensure high accuracy and reproducibility.

Characterizing the cognitive phenotype of Parkinson’s disease

AbstractBackgroundParkinson’s disease (PD) is a complex neurodegenerative disease in which combinations of motor and non‐motor symptoms result in a wide range of phenotypic presentations and disease progression. Precise characterization of these clinical endophenotypes can guide clinical practice. Such endophenotypes can also be powerful to identify genetic factors for complex diseases, like PD. Given the prevalence and impact of cognitive impairment in PD, we aimed to characterize cognitive endophenotypes in a cohort of PD patients with longitudinal assessments.MethodWe reviewed the medical records of 1028 individuals diagnosed with PD by a movement disorders specialist at our institution. We extracted scores from all available Mini‐Mental Status Examinations (MMSE). We fit proportional odds models with patient specific random effects to estimate odds ratios for higher versus lower cognition in association with age, sex and follow‐up time.ResultAmong the 237 patients with at least one MMSE, 108 had ≥2 time points and 118 were cognitively impaired (MMSE<27). The mean age was 71 years, 63 (27%) were female and the mean follow‐up time was 2.56 years. Overall, females with PD had higher MMSE scores than males with an odds ratio at age 70 of 2.43 (95% CI: 1.29, 4.97). However, MMSE scores decline with age at a faster rate in females than males (p=0.002) with ORs for a 1 year of 0.85 (0.79, 0.91) and 0.94 (95%CI: 0.91, 0.97), respectively. Within patients, declines in MMSE per year had an OR of 0.76 (0.60, 0.97) for females and 0.85 (0.75, 0.95) for males though this difference was not statistically significant. Corresponding expected MMSE trajectories are shown in the figure.ConclusionOur findings demonstrate sex differences in the cognitive phenotypes of PD. In particular, cognitive scores tend to be higher in females compared to males, but decline faster in females. These findings have clinical implications regarding counseling of patients with PD. We are currently expanding this approach to specific cognitive domains, other validated tests of cognition, and investigating the influence of genetic risk factors, such as APOE on cognitive decline in PD.

Differential diagnosis of parkinsonism: a head-to-head comparison of FDG PET and MIBG scintigraphy

[18F]fluorodeoxyglucose (FDG) PET and [123I]metaiodobenzylguanidine (MIBG) scintigraphy may contribute to the differential diagnosis of neurodegenerative parkinsonism. To identify the superior method, we retrospectively evaluated 54 patients with suspected neurodegenerative parkinsonism, who were referred for FDG PET and MIBG scintigraphy. Two investigators visually assessed FDG PET scans using an ordinal 6-step score for disease-specific patterns of Lewy body diseases (LBD) or atypical parkinsonism (APS) and assigned the latter to the subgroups multiple system atrophy (MSA), progressive supranuclear palsy (PSP), or corticobasal syndrome. Regions-of-interest analysis on anterior planar MIBG images served to calculate the heart-to-mediastinum ratio. Movement disorder specialists blinded to imaging results established clinical follow-up diagnosis by means of guideline-derived case vignettes. Clinical follow-up (1.7 ± 2.3 years) revealed the following diagnoses: n = 19 LBD (n = 17 Parkinson’s disease [PD], n = 1 PD dementia, and n = 1 dementia with Lewy bodies), n = 31 APS (n = 28 MSA, n = 3 PSP), n = 3 non-neurodegenerative parkinsonism; n = 1 patient could not be diagnosed and was excluded. Receiver operating characteristic analyses for discriminating LBD vs. non-LBD revealed a larger area under the curve for FDG PET than for MIBG scintigraphy at statistical trend level for consensus rating (0.82 vs. 0.69, p = 0.06; significant for investigator #1: 0.83 vs. 0.69, p = 0.04). The analysis of PD vs. MSA showed a similar difference (0.82 vs. 0.69, p = 0.11; rater #1: 0.83 vs. 0.69, p = 0.07). Albeit the notable differences in diagnostic performance did not attain statistical significance, the authors consider this finding clinically relevant and suggest that FDG PET, which also allows for subgrouping of APS, should be preferred.

Timeline of Rapid Eye Movement Sleep Behavior Disorder in Overt Alpha-Synucleinopathies.

The aim was to analyze the timeline, prevalence, and survival of rapid eye movement (REM) sleep behavior disorder (RBD) in patients who developed alpha-synucleinopathies (Parkinson disease, dementia with Lewy bodies, and Parkinson disease dementia) compared with age- and sex-matched controls in a population-based incident-cohort study. We used a population-based, 1991 to 2010 incident-cohort study of alpha-synucleinopathies. A movement-disorder specialist reviewed medical records to confirm diagnoses. RBD was diagnosed by reported dream-enactment symptoms or polysomnography. Probable RBD and polysomnographically confirmed RBD were analyzed separately and combined. Among the 444 incident cases of alpha-synucleinopathy, 86 were clinically diagnosed with RBD (19.8%), including 30 (35%) by polysomnography and 56 (65%) as probable. The prevalence of idiopathic RBD at alpha-synucleinopathy diagnosis was 3.4%, increasing to 23.8% after 15 years. Cumulative lifetime incidence was 53 times greater in alpha-synucleinopathy patients than in controls (odds ratio [OR] = 53.1, 95% confidence interval [CI]: 13.0-217.2, p < 0.0001), higher in dementia with Lewy bodies than in Parkinson disease (OR = 2.57, 95% CI: 1.50-4.40, p = 0.0004), and higher in men than in women with Parkinson disease, dementia with Lewy bodies, or Parkinson disease dementia (OR = 3.70, 95% CI: 2.07-6.62, p < 0.0001), but did not increase mortality risk. Our cohort had RBD incidence of 3.4%. Overall RBD increased to 23.8% after 15 years, with an overall incidence of 2.5 cases per 100 person-years. With 53 times greater lifetime incidence in alpha-synucleinopathy patients than in controls, RBD was more likely to develop in dementia with Lewy bodies than in Parkinson disease or Parkinson disease dementia, and in men than in women, but did not increase mortality risk within our cohort. ANN NEUROL 2021;89:293-303.

Characteristics of advanced Parkinson's disease patients seen in movement disorder clinics - Australian results from the cross-sectional OBSERVE study

ObjectivesTo evaluate the proportion of Parkinson's disease (PD) patients identified as having advanced Parkinson's disease (APD) according to physician's judgement in Australia. MethodsThis cross-sectional, non-interventional observational study was performed in movement disorder clinics from 18 countries. Results from Australia are presented. Participants included consecutive adults with PD attending routine clinical visits, or inpatients, who could speak English. The primary outcome was the proportion of patients diagnosed with APD via physician judgement. Results100 patients were recruited in Australia: 61.0% (95% CI 51.4–70.6%) diagnosed with APD by physician judgement. Patients were 66.6 ± 8.5 years, 65% were male, were living at home (97%), and diagnosed with PD for median 10.7 years (0–30.5 years). Motor fluctuations were present in 68%. For those with APD, referral was predominantly to enable access to device assisted therapies (DAT) (49%), while for non-APD, referral was largely for diagnostic purposes (41%). Patients had a median follow-up at the movement disorder clinic of 4.8 years for those with APD, or 3.6 years for non-APD. While 62% were eligible for DAT, only two-thirds of these received them. The most commonly used DAT was deep brain stimulation (64.3%). There was fair agreement between physician's judgement and the APD criteria by Delphi method (Cohen's kappa) 0.325 (95% CI 0.150–0.500) in the Australian subset. ConclusionsThe definition of APD requires refinement in order to facilitate greater agreement among movement disorder specialists. A third of APD patients eligible for DAT remain untreated. Better referral and education of patients with APD is needed.

Seeing the unseen: Could Eulerian video magnification aid clinician detection of subclinical Parkinson’s tremor?

IntroductionEulerian magnification amplifies very small movements in video, revealing otherwise invisible motion. This raises the possibility that it could enable clinician visualisation of subclinical tremor using a standard camera. We tested whether Eulerian magnification of apparently atremulous hands reveals a Parkinsonian tremor more frequently in Parkinson’s than in controls. MethodWe applied Eulerian magnification to smartphone video of 48 hands that appeared atremulous during recording (22 hands from 11 control participants, 26 hands from 17 idiopathic Parkinson’s participants). Videos were rated for Parkinsonian tremor appearance (yes/no) before and after Eulerian magnification by three movement disorder specialist neurologists. ResultsThe proportion of hands correctly classified as Parkinsonian or not by clinicians was significantly higher after Eulerian magnification (OR = 2.67; CI = [1.39, 5.17]; p < 0.003). Parkinsonian-appearance tremors were seen after magnification in a number of control hands, but the proportion was greater in the Parkinson’s hands. ConclusionEulerian magnification slightly improves clinician ability to identify apparently atremulous hands as Parkinsonian. This suggests that some of the apparent tremor revealed may be subclinical Parkinson’s (pathological) tremor, and Eulerian magnification may represent a first step towards contactless visualisation of such tremor. However, the technique also reveals apparent tremor in control hands. Therefore, our method needs additional elaboration and would not be of direct clinical use in its current iteration.

Telemedicine tailored to patient's needs: Assessing usability and user experience in patients with Parkinson's disease

Objective: Continuous access to care by trained movement disorder specialists improves the quality of life and the survival rate in patients with Parkinson's disease (Willis et al. 2011; Cheng et al. 2007). Telemedical approaches are a promising method to provide care for a higher number of patients (Achey et al. 2014). The TelePark project has the objective to develop a holistic telemedicine-platform for patients with Parkinson's disease. It combines app-based disease management and monitoring (self-questionnaires, electronic medication-management, structured patient-physician contacts, video-telemedicine, active digital-testing) with sensor-based monitoring systems (Motognosis Amsa®, PD Monitor®, gait-sensor-sock and smartphone).

Multi-Dimensional, Short-Timescale Quantification of Parkinson's Disease and Essential Tremor Motor Dysfunction.

Introduction: Parkinson's disease (PD) is a progressive movement disorder characterized by heterogenous motor dysfunction with fluctuations in severity. Objective, short-timescale characterization of this dysfunction is necessary as therapies become increasingly adaptive.Objectives: This study aims to characterize a novel, naturalistic, and goal-directed tablet-based task and complementary analysis protocol designed to characterize the motor features of PD.Methods: A total of 26 patients with PD and without deep brain stimulation (DBS), 20 control subjects, and eight patients with PD and with DBS completed the task. Eight metrics, each designed to capture an aspect of motor dysfunction in PD, were calculated from 1-second, non-overlapping epochs of the raw positional and pressure data captured during task completion. These metrics were used to generate a classifier using a support vector machine (SVM) model to produce a unifying, scalar “motor error score” (MES). The data generated from these patients with PD were compared to same-day standard clinical assessments. Additionally, these data were compared to analogous data generated from a separate group of 12 patients with essential tremor (ET) to assess the task's specificity for different movement disorders. Finally, an SVM model was generated for each of the eight patients with PD and with DBS to differentiate between their motor dysfunction in the “DBS On” and “DBS Off” stimulation states.Results: The eight metrics calculated from the raw positional and force data captured during task completion were non-redundant. MES generated by the SVM analysis protocol showed a strong correlation with MDS-UPDRS-III scores assigned by movement disorder specialists. Analysis of the relative contributions of each of the eight metrics showed a significant difference between the motor dysfunction of PD and ET. Much of this difference was attributable to the homogenous, tremor-dominant phenotype of ET motor dysfunction. Finally, in individual patients with PD with DBS, task performance and subsequent SVM classification effectively differentiated between the “DBS On” and “DBS Off” stimulation states.Conclusion: This tablet-based task and analysis protocol correlated strongly with expert clinical assessments of PD motor dysfunction. Additionally, the task showed specificity for PD when compared to ET, another common movement disorder. This specificity was driven by the relative heterogeneity of motor dysfunction of PD compared to ET. Finally, the task was able to distinguish between the “DBS On” and “DBS Off” states within single patients with PD. This task provides temporally-precise and specific information about motor dysfunction in at least two movement disorders that could feasibly correlate to neural activity.

Gradient boosting for Parkinson\u2019s disease diagnosis from voice recordings

BackgroundParkinson’s Disease (PD) is a clinically diagnosed neurodegenerative disorder that affects both motor and non-motor neural circuits. Speech deterioration (hypokinetic dysarthria) is a common symptom, which often presents early in the disease course. Machine learning can help movement disorders specialists improve their diagnostic accuracy using non-invasive and inexpensive voice recordings.MethodWe used “Parkinson Dataset with Replicated Acoustic Features Data Set” from the UCI-Machine Learning repository. The dataset included 44 speech-test based acoustic features from patients with PD and controls. We analyzed the data using various machine learning algorithms including Light and Extreme Gradient Boosting, Random Forest, Support Vector Machines, K-nearest neighborhood, Least Absolute Shrinkage and Selection Operator Regression, as well as logistic regression. We also implemented a variable importance analysis to identify important variables classifying patients with PD.ResultsThe cohort included a total of 80 subjects: 40 patients with PD (55% men) and 40 controls (67.5% men). Disease duration was 5 years or less for all subjects, with a mean Unified Parkinson’s Disease Rating Scale (UPDRS) score of 19.6 (SD 8.1), and none were taking PD medication. The mean age for PD subjects and controls was 69.6 (SD 7.8) and 66.4 (SD 8.4), respectively. Our best-performing model used Light Gradient Boosting to provide an AUC of 0.951 with 95% confidence interval 0.946–0.955 in 4-fold cross validation using only seven acoustic features.ConclusionsMachine learning can accurately detect Parkinson’s disease using an inexpensive and non-invasive voice recording. Light Gradient Boosting outperformed other machine learning algorithms. Such approaches could be used to inexpensively screen large patient populations for Parkinson’s disease.

Hypomimia in Parkinson's disease: an axial sign responsive to levodopa.

Hypomimia is a prominent clinical feature in people with Parkinson's disease (PD), but it remains under-investigated. We aimed to examine the clinical correlates of hypomimia in PD and to determine whether this is a levodopa-responsive sign. We included 89 people with PD. Hypomimia was assessed from digital video recordings by movement disorder specialists. Clinical evaluation included use of the Unified Parkinson's Disease Rating Scale part III (UPDRS-III), and assessment of motor and non-motor symptoms using standardized clinical scales. The relationships between hypomimia and other clinical data were analysed using Mann-Whitney U-tests and regression analysis. Hypomimia occurred in up to 70% of patients with PD. Patients with hypomimia had worse UPDRS-III 'off-medication' scores, mainly driven by bradykinesia and rigidity subscores. Patients with hypomimia also had worse apathy than patients without hypomimia. Finally, we found that hypomimia was levodopa-responsive and its improvement mirrored the change by levodopa in axial motor symptoms. Our study provides novel information regarding the clinical correlates of hypomimia in people with PD. A better understanding of hypomimia may be relevant for improving treatment and quality of life in PD.

Association of MAPT subhaplotypes with clinical and demographic features in Parkinson's disease.

ObjectiveTo determine whether distinct microtubule‐associated protein tau MAPT H1 subhaplotypes are associated with clinical and demographic features in Parkinson’s disease.MethodsA retrospective cohort study included 855 unrelated Caucasian patients with Parkinson’s disease who were seen by Movement Disorder specialists at the Mayo Clinic Florida between 1998 and 2016. The primary outcome measures were specific demographic and clinical features of Parkinson’s disease, including age at onset, disease progression, survival, motor signs, dementia, dystonia, dyskinesia, autonomic dysfunction, impulse control disorder, psychiatric features, REM sleep behavior disorder, restless legs syndrome, and Parkinson’s disease subtype. Specific clinical features were measured at the initial visit and most recent visit. These outcomes were assessed for association with MAPT H1 subhaplotypes, which were defined by six haplotype tagging variants.ResultsMedian onset age was 64 years (range: 22‐94 years); 548 (64%) of patients were male. Significant associations (P < 0.0029) were observed between MAPT H1b and orthostatic hypotension (OR = 1.72, P = 0.001); between H1j and rest tremor (OR = 0.15; P < 0.001) as well as REM sleep behavior disorder (OR = 3.87, P < 0.001); between H1r and bradykinesia (OR = 0.11; P < 0.001); and between H1v and restless legs syndrome (OR = 4.02, P = 0.002).InterpretationFour MAPT H1 subhaplotypes, but not the H2 haplotype, were significantly associated with specific clinical features in Parkinson’s disease. MAPT haplotypic structure may explain some of the phenotypic variability in disease. Replication of our findings will be critical to fully resolve the Parkinson’s disease risk association signal at Chr17q21.

Analysis of Motor Complication and Relative Factors in a Cohort of Chinese Patients with Parkinson's Disease.

Objective Motor complications are common in Parkinson's disease (PD). The reported occurrence of motor complications varies across regions and races. The aim of our study was to describe the development of dyskinesias and motor fluctuations among Chinese PD patients and the relative risk factors. Methods In the current cross-sectional survey study, PD patients with motor fluctuations and dyskinesia were enrolled from March to November 2018 in Shaanxi province, a northwest area of China. Data were collected by the movement disorder specialists. A self-designed questionnaire was utilized during face-to-face interviews. In addition, the relevant factors of motor complications were analyzed by univariable and multivariable analyses. Results Of the166 PD patients recruited, 52 (31.33%) and 25 (15.06%) patients had motor fluctuations and dyskinesia, respectively, which occurred in 6.76 ± 3.77 and 8.61 ± 4.46 years after the onset of motor symptoms and 5.37 ± 3.33 and 6.80 ± 3.43 years after the treatment of levodopa therapy, respectively. Patients with motor fluctuations and dyskinesias had longer disease duration, younger onset age, higher Hoehn–Yahr stages and UPDRS III scores, higher daily levodopa dosage and levodopa equivalent daily dose (LEDD), and longer duration of levodopa treatment (P < 0.05). Bradykinesia-rigidity dominant patients had higher incidences of motor fluctuations (61.54% vs 38.46%) and dyskinesias (68.00% vs 32.00%) than tremor-dominant patients (P < 0.05). Results of the multivariate logistic regression analyses showed that the duration of levodopa therapy, age of the onset, and bradykinesia-rigidity dominant type were independent risk factors of motor fluctuations (P < 0.05). In addition, duration of disease and bradykinesia-rigidity dominant type were independent risk factors of dyskinesia (P < 0.05). Conclusions The rate of motor fluctuations was higher than dyskinesias in Chinese patients with Parkinson's disease. Patients with younger age onset, bradykinesia-rigidity dominant type, longer disease duration, and longer duration of levodopa therapy are more likely to develop motor complications.

Optimizing Treatment in Undertreated Late-Stage Parkinsonism: A Pragmatic Randomized Trial.

Treatment of patients with late-stage parkinsonism is often sub-optimal. To test the effectiveness of recommendations by a movement disorder specialist with expertise in late-stage parkinsonism. Ninety-one patients with late-stage parkinsonism considered undertreated were included in apragmatic a pragmatic multi-center randomized-controlled trial with six-month follow-up. The intervention group received a letter with treatment recommendations to their primary clinician based on an extensive clinical assessment. Controls received care as usual. The primary outcome was the Unified Parkinson Disease Rating Scale (UPDRS)part-II (Activities of Daily Living). Other outcomes included quality-of-life (PDQ-8), mental health (UPDRS-I), motor function (UPDRS-III), treatment complications (UPDRS-IV), cognition (Mini-mental-state-examination), non-motor symptoms (Non-Motor-Symptoms-scale), health status (EQ-5D-5L) and levodopa-equivalent-daily-dose (LEDD). We also assessed adherence to recommendations. In addition to intention-to-treat analyses, a per-protocol analysis was conducted. Sample size calculation required 288 patients, but only 91 patients could be included. Treating physicians followed recommendations fully in 16 (28%) and partially in 21 (36%) patients. The intention-to-treat analysis showed no difference in primary outcome (between-group difference = -1.2, p = 0.45), but there was greater improvement for PDQ-8 in the intervention group (between-group difference = -3.7, p = 0.02). The per-protocol analysis confirmed these findings, and showed less deterioration in UPDRS-part I, greater improvement on UPDRS-total score and greater increase in LEDD in the intervention group. The findings suggest that therapeutic gains may be reached even in this vulnerable group of patients with late-stage parkinsonism, but also emphasize that specialist recommendations need to be accompanied by better strategies to implement these to further improve outcomes.

Movement disorders in children with congenital Zika virus syndrome

BackgroundCongenital Zika Virus Syndrome (CZVS) denotes the neurologic and developmental sequelae of congenital infection of the Zika virus. While prior studies have detailed the associated clinical phenotypes, new findings continue to be identified. Abnormal postures and movements have been previously described in children with CZVS, but not in detail. ObjectiveTo examine a cohort of infants with CZVS and characterize the spectrum of motor abnormalities, especially movement disorders. DesignCross-sectional prospective study of 21 infants with confirmed CZVS. SettingSingle-center cohort of 32 patients with serologically confirmed CZVS cared for in a referral center in Brazil. Participants21 children (67% female), evaluated by two child neurologists and one movement disorders specialist, with clinical and laboratory diagnosis of CZVS aged between 16 and 30 months, with a mean age of 16 months at the time of the last examination. Main outcome(s) and measure(s)Prospective neurologic examination by a team of three neurologists, including one movement disorders specialist. Sixteen (76.2%) children had a longitudinal evaluation with a six-month interval. The same team of experts analyzed recorded videos of all patients to characterize motor abnormalities and movement disorders. Neuroimaging findings were also analyzed to correlate with clinical findings. ResultsTwenty (95.2%) patients presented with dystonic postures, including “125” posture of the fingers in 17 (80.1%), “swan neck” posture of the fingers in three (18.8%), oromandibular dystonia in nine (42.9%), extensor axial hypertonia in eight (38.1%) and internal rotation of the shoulder posture in two (9.5%). Four (19%) patients had tremor. All children had malformations of cortical development, and in 13 (61.9%), the pattern was consistent with a severe and diffuse gyral simplification. Seventeen children (81%) had calcification in the transition of grey and white matter, whereas 11 (52.4%) patients had basal ganglia calcifications. Conclusion and relevanceIn our series, dystonic postures and other extrapyramidal signs were frequent and potentially disabling. Although children with CZVS are assessed and treated for spasticity, dystonia and other movement disorders remain neglected. This study emphasizes that extrapyramidal findings may potentially influence optimal strategies for rehabilitation and management.

Early autonomic and cognitive dysfunction in PD, DLB and MSA: blurring the boundaries between α-synucleinopathies.

Differential diagnosis between Parkinson's disease, dementia with Lewy bodies and multiple system atrophy can be difficult, especially because in early phase they might present with overlapping clinical features. Notably, orthostatic hypotension and cognitive dysfunction are common nonmotor aspects of parkinsonian syndromes and can be both present from the earliest stages of all α-synucleinopathies, indicating a common neurobiological basis in their strong relationship. In view of the increasing awareness about the prevalence of mild cognitive dysfunction in multiple system atrophy, the relevance of autonomic dysfunction in demented parkinsonian patients, the critical role of non-motor symptoms in clustering Parkinson's disease patients and the shift to studying patients in the prodromal phase, we will discuss some intrinsic limitations of current clinical diagnostic criteria, even when applied by movement disorder specialists. In particular, we will focus on the early coexistence of autonomic and cognitive dysfunction in the setting of overt or latent parkinsonism as pitfalls in the differential diagnosis of α-synucleinopathies. As early and accurate diagnosis remains of outmost importance for counselling of patients and timely enrolment into disease-modifying clinical trials, a continuous effort of research community is ongoing to further improve the clinical diagnostic accuracy of α-synucleinopathies.

Health care for chronic neurological patients after COVID-19.

Health care for chronic neurological patients after COVID-19.

Parkinson's disease polygenic risk score is not associated with impulse control disorders: A longitudinal study

ObjectiveTo examine the relationship between a Parkinson's disease (PD) polygenic risk score (PRS) and impulse control disorders (ICDs) in PD. BackgroundGenome wide association studies (GWAS) have brought forth a PRS associated with increased risk of PD and younger disease onset. ICDs are frequent adverse effects of dopaminergic drugs and are also more frequent in patients with younger disease onset. It is unknown whether ICDs and PD share genetic susceptibility. MethodsWe used data from a multicenter longitudinal cohort of PD patients with annual visits up to 6 years (DIG-PD). At each visit ICDs, defined as compulsive gambling, buying, eating, or sexual behavior were evaluated by movement disorders specialists. We genotyped DNAs using the Megachip assay (Illumina) and calculated a weighted PRS based on 90 SNPs associated with PD. We estimated the association between PRS and prevalence of ICDs at each visit using Poisson generalized estimating equations, adjusted for dopaminergic treatment and other known risk factors for ICDs. ResultsOf 403 patients, 185 developed ICDs. Patients with younger age at onset had a higher prevalence of ICDs (p < 0.001) as well as higher PRS values (p = 0.06). At baseline, there was no association between the PRS and ICDs (overall, p = 0.84). The prevalence of ICDs increased over time similarly across the quartiles of the PRS (overall, p = 0.88; DA users, p = 0.99). ConclusionDespite younger disease onset being associated with both higher PRS and ICD prevalence, our findings are not in favor of common susceptibility genes for PD and ICDs.

A Simple Bedside Screening Tool for Spasticity Referral.

Background and ObjectivesSpasticity is common in long-term care facilities; however, this often-disabling condition is largely underdiagnosed in this setting and therefore left untreated. This study aimed to test the ability of a three-question flowchart used at the bedside by primary care providers in the long-term care setting to identify residents in need of referral to a specialist for spasticity consultation.MethodsAll residents of a single long-term care facility were approached for participation in this cross-sectional, observational study. Spasticity diagnostic evaluations by a movement disorders specialist neurologist (reference standard) were compared with referral determinations made by two primary care providers [a primary care physician (PCP) and a nurse practitioner (NP)] using the simple flowchart.ResultsThe analysis included 49 residents (80% male, age 78.2±9.0 years) who were evaluated by the reference standard neurologist and at least one primary care provider. The bedside referral tool demonstrated high sensitivity and moderate specificity when used by the PCP (92% and 78%, respectively; AUC=0.84) and NP (80% and 53%, respectively; AUC=0.67).ConclusionThis simple tool may be useful for primary care providers to identify residents to be referred to a specialist for evaluation and treatment of spasticity. These results warrant further investigation of the potential utility of this screening tool across multiple long-term care facilities and various types of care providers.

Differential diagnosis of parkinsonian syndromes: a comparison of clinical and automated - metabolic brain patterns' based approach.

Differentiation among parkinsonian syndromes may be clinically challenging, especially at early disease stages. In this study, we used 18F-FDG-PET brain imaging combined with an automated image classification algorithm to classify parkinsonian patients as Parkinson's disease (PD) or as an atypical parkinsonian syndrome (APS) at the time when the clinical diagnosis was still uncertain. In addition to validating the algorithm, we assessed its utility in a "real-life" clinical setting. One hundred thirty-seven parkinsonian patients with uncertain clinical diagnosis underwent 18F-FDG-PET and were classified using an automated image-based algorithm. For 66 patients in cohort A, the algorithm-based diagnoses were compared with their final clinical diagnoses, which were the gold standard for cohort A and were made 2.2 ± 1.1years (mean ± SD) later by a movement disorder specialist. Seventy-one patients in cohort B were diagnosed by general neurologists, not strictly following diagnostic criteria, 2.5 ± 1.6years after imaging. The clinical diagnoses were compared with the algorithm-based ones, which were considered the gold standard for cohort B. Image-based automated classification of cohort A resulted in 86.0% sensitivity, 92.3% specificity, 97.4% positive predictive value (PPV), and 66.7% negative predictive value (NPV) for PD, and 84.6% sensitivity, 97.7% specificity, 91.7% PPV, and 95.5% NPV for APS. In cohort B, general neurologists achieved 94.7% sensitivity, 83.3% specificity, 81.8% PPV, and 95.2% NPV for PD, while 88.2%, 76.9%, 71.4%, and 90.9% for APS. The image-based algorithm had a high specificity and the predictive values in classifying patients before a final clinical diagnosis was reached by a specialist. Our data suggest that it may improve the diagnostic accuracy by 10-15% in PD and 20% in APS when a movement disorder specialist is not easily available.