Increasing exercise with a mobile app in people with Parkinson's disease: a pilot study.

Background Exercise is crucial for the well-being of people with Parkinson's disease (PD). Although there are challenges to exercising with PD, mobile apps are seen as potential solutions, though their impact is not yet fully understood. We developed a mobile app and a home-based exercise program specialised for people with PD and investigated the effect of the mobile exercise app for the people with PD. Methods Participants from the Movement Disorder Clinic were prompted to download and actively use our app for a duration of 2 weeks. Before commencing, we assessed their self-rated smartphone proficiency. Both at the start and after the 2-week period, we employed the International Physical Activity Questionnaire-Short Form and the PD Questionnaire-39 (PDQ-39) to evaluate their physical activity and overall quality of life (QoL). Exercise metrics were quantified in terms of metabolic equivalent minutes per week (MET-min/week). Furthermore, we gathered feedback on user satisfaction with the app at the end of the study. Results Out of 41 recruited patients, 25 completed the 2-week program and 16 dropped out. Median MET-min/week rose from 1386.0 to 3210.0 (P = 0.009), primarily in moderate activities (P = 0.049) and walking (P = 0.002). Median PDQ-39 scores showed improvement from 17.2 to 8.5 (P = 0.005) after the program. Conclusion The mobile app holds potential to enhance exercise and QoL for people with PD. For optimal benefits, future studies should focus on e-health literacy education, app quality enhancements, and a broader exercise program variety.

Effectiveness of Live-Streaming Tele-Exercise Intervention in Patients With Parkinson's Disease: A Pilot Study.

OBJECTIVE: Exercise can improve both motor and nonmotor symptoms in people with Parkinson's disease (PwP), but there is an unmet need for accessible and sustainable exercise options. This study aimed to evaluate the effect, feasibility, and safety of a regularly performed live-streaming tele-exercise intervention for PwP. METHODS: A live-streaming exercise intervention for PwP was implemented twice a week for 12 weeks. We measured the motor and nonmotor symptom scores of the included patients before and after the intervention. Changes in clinical scores from baseline to postintervention were analyzed using paired t-tests. Factors associated with improvements in clinical scores and compliance were analyzed using Pearson's correlation analysis. RESULTS: Fifty-six participants were enrolled in the study. There were significant improvements in Hospital Anxiety and Depression Scale (HADS)-anxiety (p = 0.007), HADS-depression (p < 0.001), Unified Parkinson's Disease Rating Scale (UPDRS) part III (p < 0.001), UPDRS total (p = 0.015), Hoehn and Yahr stage (p = 0.027), and Parkinson's Disease Fatigue Scale-16 (p = 0.026) scores after the intervention. Improvements in motor symptoms were associated with improvements in mood symptoms and fatigue. Higher motor impairment at baseline was associated with a greater compliance rate and better postintervention composite motor and nonmotor outcomes (ΔUPDRS total score). Overall, the 12-week tele-exercise program was feasible and safe for PwP. No adverse events were reported. The overall adherence rate was 60.0% in our cohort, and 83.4% of the participants were able to participate in more than half of the exercise routines. CONCLUSION: The live-streaming tele-exercise intervention is a safe, feasible, and effective nonpharmacological treatment option that can alleviate fatigue and improve mood and motor symptoms in PwP.

Nonarteritic anterior ischemic optic neuropathy and incidence of Parkinson's disease based on a nationwide population based study.

This study aimed to investigate the association between nonarteritic anterior ischemic optic neuropathy (NAION) and Parkinson's disease (PD) using a retrospective, nationwide, population-based cohort in South Korea. This study utilized data from the Korean National Health Insurance database, including 43,960 NAION patients and 219,800 age- and sex-matched controls. Cox proportional hazards regression models were used to assess the risk of developing PD in the NAION group compared to the control group after adjusting for various confounding factors. Subgroup analyses were conducted based on sex, age, and comorbidities. The incidence rate of PD was higher in the NAION group (1.326 per 1000 person-years) than in the control group (0.859 per 1000 person-years). After adjusting for confounding factors, the risk of developing PD was significantly higher in the NAION group (adjusted hazard ratio [aHR] 1.516, 95% confidence interval [CI] 1.300-1.769). Subgroup analyses did not reveal a significant difference in the risk of PD development based on sex, age, or comorbidities. This retrospective, nationwide, population-based cohort study revealed a significant association between NAION and an increased risk of developing PD in a South Korean population. The incidence rate of PD was observed to be higher in individuals diagnosed with NAION than in age- and sex-matched controls even after adjusting for potential confounding variables, with the risk being approximately 51.6% higher in the NAION group. Further research is necessary to elucidate the underlying pathophysiological mechanisms linking NAION to PD and to determine whether similar associations exist in other ethnic and geographical populations.

Risk of Parkinson disease in stroke patients: A nationwide cohort study in South Korea.

BACKGROUND AND PURPOSE: Previous studies have examined the risk of stroke in patients with Parkinson disease (PD), but the incidence of PD onset among stroke patients and its risk according to severity of poststroke disabilities have scarcely been investigated. This study aims to determine whether the risk of PD is increased among stroke patients using a retrospective cohort with a large population-based database. METHODS: We used data collected by the Korean National Health Insurance Service from 2010 to 2018 and examined 307,361 stroke patients and 380,917 sex- and age-matched individuals without stroke to uncover the incidence of PD. Cox proportional hazards regression was used to calculate the hazard ratio (HR) and 95% confidence interval (CI), and the risk of PD was compared according to presence and severity of disability. RESULTS: During 4.31 years of follow-up, stroke patients had a 1.67 times higher risk of PD compared to individuals without stroke (adjusted HR = 1.67, 95% CI = 1.57-1.78). The risk of PD was greater among stroke patients with disabilities than among those without disabilities, even after adjustment for multiple covariates (adjusted HR = 1.72, 95% CI = 1.55-1.91; and adjusted HR = 1.66, 95% CI = 1.56-1.77, respectively). CONCLUSIONS: Our study demonstrated an increased risk of PD among stroke patients. Health professionals need to pay careful attention to detecting movement disorders as clues for diagnosing PD.

Subjective cognitive complaints in patients with progressive supranuclear palsy.

Introduction: Subjective cognitive complaints (SCC) refer to self-reported cognitive decline that may or may not be reflected in objective neuropsychological evaluations. Such SCC are prevalent in neurodegenerative diseases, including Parkinson's disease (PD), but the prevalence and clinical features in patients with progressive supranuclear palsy (PSP) have not been investigated. Methods: We recruited 83 PSP patients without dementia and investigated their SCC using a semi-structured interview. Comprehensive neuropsychological test results and patient clinical features were compared according to presence of SCC and underlying cognitive state. Results: Among the 83 patients, 16 had normal cognition (NC), 67 had mild cognitive impairment (MCI), and 36 (43.4%) reported SCC. Among NC patients, 37.5% (6/16) had SCC, while 44.8% (30/67) of MCI patients reported SCC. There were no differences between the neuropsychological test results or demographic and clinical characteristics of PSP patients with or without SCC in the NC group. The demographic and clinical characteristics of the MCI+SCC (MCI with SCC)and MCI-SCC (MCI without SCC) groups were comparable, but the MCI+SCC group had significantly worse neuropsychological scores than the MCI-SCC group, particularly in tests assessing attention, language, visual memory, and fronto-executive function domains. Discussion: While SCC are commonly reported by PSP patients, patients with PSP and MCI+SCC had worse cognitive function than those who did not report SCC. These findings suggest that SCC in PSP patients with MCI could be a worsening sign of cognitive function. Therefore, it is crucial for physicians to assess SCC in PSP patients and to provide timely diagnosis and management of cognitive decline.

Waiting impulsivity in progressive supranuclear palsy-Richardson's syndrome.

Background: Waiting impulsivity in progressive supranuclear palsy-Richardson's syndrome (PSP-RS) is difficult to assess, and its regulation is known to involve nucleus accumbens (NAc) subregions. We investigated waiting impulsivity using the "jumping the gun" (JTG) sign, which is defined as premature initiation of clapping before the start signal in the three-clap test and compared clinical features of PSP-RS patients with and without the sign and analyzed neural connectivity and microstructural changes in NAc subregions. Materials and methods: A positive JTG sign was defined as the participant starting to clap before the start sign in the three-clap test. We classified participants into the JTG positive (JTG +) and JTG negative (JTG-) groups and compared their clinical features, microstructural changes, and connectivity between NAc subregions using diffusion tension imaging. The NAc was parcellated into core and shell subregions using data-driven connectivity-based methods. Results: Seventy-seven patients with PSP-RS were recruited, and the JTG + group had worse frontal lobe battery (FAB) scores, more frequent falls, and more occurrence of the applause sign than the JTG- group. A logistic regression analysis revealed that FAB scores were associated with a positive JTG sign. The mean fiber density between the right NAc core and right medial orbitofrontal gyrus was higher in the JTG + group than the JTG- group. Discussion: We show that the JTG sign is a surrogate marker of waiting impulsivity in PSP-RS patients. Our findings enrich the current literature by deepening our understanding of waiting impulsivity in PSP patients and introducing a novel method for its evaluation.

Whole exome sequencing and clinical investigation of young onset dystonia: What can we learn?

BACKGROUND: Dystonia is a heterogeneous movement disorder involving various genetic backgrounds, and the implication of whole exome sequencing (WES) has yet to be clearly elucidated. In this study, we performed WES in Korean patients with young-onset dystonia. METHODS: We recruited patients with young-onset dystonia based on the new MDS dystonia classification at Samsung Medical Centre from 2015 to 2019. We excluded subjects diagnosed by single gene tests (GCH1, TOR1A, PANK2, PRRT2, and SGCE) or levodopa trials and subjects with focal or possible secondary dystonia. We performed WES in all enrolled subjects and confirmed the results with Sanger sequencing. RESULTS: Of the 43 patients, we detected 11 disease-causing variants, classified as either pathogenic or likely pathogenic, in 9 patients (20.9%). Generalized dystonia, infancy-childhood-onset dystonia, and other combined neurologic manifestations were related with PV/LPV. When we retrospectively reviewed the patients with PV/LPV, brain imaging was diagnostic in 3 subjects (HTRA1, SCL20A, and WDR45), clinical characteristics of paroxysmal presentation were observed in 2 (ADCY5 and ATP1A3), and microcephaly was noted in 1 patient (KMT2B). CONCLUSION: Clinical exome sequencing is helpful for the diagnosis of dystonia, especially for that with infancy-childhood onset, and generalized dystonia with other neurologic manifestations. Additionally, careful evaluations and examinations could provide information for selecting candidates for genetic testing.

Automatic stridor detection using small training set via patch-wise few-shot learning for diagnosis of multiple system atrophy.

Stridor is a rare but important non-motor symptom that can support the diagnosis and prediction of worse prognosis in multiple system atrophy. Recording sounds generated during sleep by video-polysomnography is recommended for detecting stridor, but the analysis is labor intensive and time consuming. A method for automatic stridor detection should be developed using technologies such as artificial intelligence (AI) or machine learning. However, the rarity of stridor hinders the collection of sufficient data from diverse patients. Therefore, an AI method with high diagnostic performance should be devised to address this limitation. We propose an AI method for detecting patients with stridor by combining audio splitting and reintegration with few-shot learning for diagnosis. We used video-polysomnography data from patients with stridor (19 patients with multiple system atrophy) and without stridor (28 patients with parkinsonism and 18 patients with sleep disorders). To the best of our knowledge, this is the first study to propose a method for stridor detection and attempt the validation of few-shot learning to process medical audio signals. Even with a small training set, a substantial improvement was achieved for stridor detection, confirming the clinical utility of our method compared with similar developments. The proposed method achieved a detection accuracy above 96% using data from only eight patients with stridor for training. Performance improvements of 4%-13% were achieved compared with a state-of-the-art AI baseline. Moreover, our method determined whether a patient had stridor and performed real-time localization of the corresponding audio patches, thus providing physicians with support for interpreting and efficiently employing the results of this method.

Comparative validation of AI and non-AI methods in MRI volumetry to diagnose Parkinsonian syndromes.

Automated segmentation and volumetry of brain magnetic resonance imaging (MRI) scans are essential for the diagnosis of Parkinson's disease (PD) and Parkinson's plus syndromes (P-plus). To enhance the diagnostic performance, we adopt deep learning (DL) models in brain MRI segmentation and compared their performance with the gold-standard non-DL method. We collected brain MRI scans of healthy controls ([Formula: see text]) and patients with PD ([Formula: see text]), multiple systemic atrophy ([Formula: see text]), and progressive supranuclear palsy ([Formula: see text]) at Samsung Medical Center from January 2017 to December 2020. Using the gold-standard non-DL model, FreeSurfer (FS), we segmented six brain structures: midbrain, pons, caudate, putamen, pallidum, and third ventricle, and considered them as annotated data for DL models, the representative convolutional neural network (CNN) and vision transformer (ViT)-based models. Dice scores and the area under the curve (AUC) for differentiating normal, PD, and P-plus cases were calculated to determine the measure to which FS performance can be reproduced as-is while increasing speed by the DL approaches. The segmentation times of CNN and ViT for the six brain structures per patient were 51.26 ± 2.50 and 1101.82 ± 22.31 s, respectively, being 14 to 300 times faster than FS (15,735 ± 1.07 s). Dice scores of both DL models were sufficiently high (> 0.85) so their AUCs for disease classification were not inferior to that of FS. For classification of normal vs. P-plus and PD vs. P-plus (except multiple systemic atrophy - Parkinsonian type) based on all brain parts, the DL models and FS showed AUCs above 0.8, demonstrating the clinical value of DL models in addition to FS. DL significantly reduces the analysis time without compromising the performance of brain segmentation and differential diagnosis. Our findings may contribute to the adoption of DL brain MRI segmentation in clinical settings and advance brain research.

Central retinal microvasculature damage is associated with orthostatic hypotension in Parkinson's disease.

Orthostatic hypotension (OH) is a common non-motor symptom in Parkinson's disease (PD). OH can cause cerebral and retinal hypoperfusion and is associated with microvascular damage in PD. Optical coherence tomography angiography (OCTA) is a non-invasive technology that can be used to visualize the retinal microvasculature and detect microvascular damage in PD. In the present study, 51 PD patients (OH+, n = 20, 37 eyes; OH-, n = 32, 61 eyes) and 51 healthy controls (100 eyes) were evaluated. The Unified Parkinson's Disease Rating Scale III, Hoehn and Yahr scale, Montreal Cognitive Assessment, levodopa equivalent daily dose, and vascular risk factors, including hypertension, diabetes, and dyslipidemia, were investigated. PD patients underwent a head-up tilt (HUT) test. The PD patients had a lower superficial retinal capillary plexus (SRCP) density in the central region than control patients. The PDOH+ group had lower vessel density in the SRCP of the central region compared with the control group and lower vessel density in the DRCP of the central region than the PDOH- and control groups. The changes in systolic and diastolic blood pressure during the HUT test in PD patients showed a negative correlation with the vessel density in the DRCP central region. The presence of OH was a critical factor associated with central microvasculature damage in PD. These findings indicate that OCTA can be a useful and non-invasive tool for detecting microvasculature damage in PD patients.

Orthostatic Hypotension Is a Predictor of Fatigue in Drug-Naïve Parkinson's Disease.

Introduction: Fatigue and orthostatic hypotension (OH) are common and disabling nonmotor symptoms (NMSs) of Parkinson's disease (PD), but none of the studies have reported on the longitudinal association between fatigue and OH. Methods: Drug-naïve PD patients were recruited from a hospital-based cohort and evaluated with the Parkinson Fatigue Scale (PFS), head-up tilt test, Unified PD Rating Scale, Hoehn and Yahr stage, Montreal Cognitive Assessment, Scale for Outcomes in PD-Autonomic (SCOPA-AUT), Beck Depression Inventory (BDI), Beck Anxiety Inventory, PD Sleep Scale, and medications at the baseline and follow-up visits. Results: A total of 80 patients were included, and the mean ages were 66.6 and 63.8 years in the fatigue and nonfatigue groups, respectively. The prevalence of fatigue was 17.5% (14/80) at the baseline and follow-up (mean follow-up: 23.3 ± 9.9 months). The prevalence of OH in the fatigue group was 57.1%, and it was significantly higher than that of the nonfatigue group. Six of the 14 patients (42.9%) in the fatigue group had persistent fatigue at the follow-up, and eight of them (57.1%) converted to the nonfatigue group. Logistic regression analysis demonstrated that the changes of BDI and the presence of OH at the baseline were the predictors for fatigue in drug-naïve PD. Conclusion: Fatigue is a common NMS in PD but can vary depending on the disease course. OH and depression are the most relevant predictors for the development of fatigue in drug-naïve PD. The present study suggests that the management of autonomic symptoms and depression might be helpful for managing fatigue in PD.

M1 and Cerebellar tDCS for MSA-C: a Double-Blind, Randomized, Sham-Controlled, Crossover Study.

The effect of transcranial direct current stimulation (tDCS) for cerebellar-dominant multiple-system atrophy (MSA-C) is not well elucidated, yet. This study aimed to investigate the effect of tDCS on the primary motor cortex (M1) and cerebellum in patients with MSA-C. We recruited probable MSA-C patients and performed three single sessions of tDCS at each visit in random order (M1, cerebellum or sham). Cerebellar ataxia was evaluated with the International Cooperative Ataxia Rating Scale (ICARS) and objective gait and static balance analyses both before and after each stimulation session. Additionally, we also evaluated the factors related with objective improvement from each stimulation. Sixteen participants were enrolled, and one dropped out after 2 sessions of stimulation due to consent withdrawal. The gait velocity, step time and single support time all significantly improved after the M1 and cerebellar tDCS treatment compared with the sham stimulation while there was no difference in the improvement of ICARS and posturography results among 3 stimulations. In terms of the related factors with improvement of gait velocity, the disease duration, baseline gait speed and single support times were correlated after M1 stimulation, while a higher ICARS score and baseline gait speed in cerebellar stimulation. There were no adverse effects reported after the tDCS sessions. Our results demonstrated that both M1 and cerebellar tDCS demonstrated benefits for MSA-C patients without significant complications. Considering the different related factors with improvement at each stimulation, the mechanism would be different between M1 and cerebellar stimulations.

Risk of Parkinson's disease in multiple sclerosis and neuromyelitis optica spectrum disorder: a nationwide cohort study in South Korea.

BACKGROUND: Neurodegeneration is associated with pathogenesis of both multiple sclerosis (MS) and neuromyelitis optica (NMOSD). Parkinson's disease (PD) is a representative neurodegenerative disease, however, whether MS or NMOSD is associated with risk of PD is not known. METHODS: MS and NMOSD cohorts were collected from the Korean National Health Insurance Service between 1 January 2010 and 31 December 2017, using International Classification of Diseases 10th revision diagnosis codes and information in the Rare Intractable Disease management programme. The PD incidence rate that occurred after a 1-year lag period was calculated and compared with that of a control cohort matched for age, sex, hypertension, diabetes and dyslipidaemia in a 1:5 ratio. RESULTS: The incidence rates of PD in patients with MS and NMOSD were 3.38 and 1.27 per 1000 person-years, respectively, and were higher than that of their matched control groups. The adjusted HR of PD was 7.73 (95% CI, 3.87 to 15.47) in patients with MS and 2.61 (95% CI, 1.13 to 6.02) in patients with NMOSD compared with matched controls. In both patients with MS and NMOSD, there were no significant differences in relative risk when stratified by sex, age, diabetes, hypertension and dyslipidaemia. CONCLUSION: The PD risk was higher in patients with MS and NMOSD compared with healthy controls and was particularly high in patients with MS. Further investigations should be performed to determine the pathophysiology and occurrence of PD in patients with MS and NMOSD.

Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks.

Dysarthria may present during the natural course of many degenerative neurological conditions. Hypokinetic and ataxic dysarthria are common in movement disorders and represent the underlying neuropathology. We developed an artificial intelligence (AI) model to distinguish ataxic dysarthria and hypokinetic dysarthria from normal speech and differentiate ataxic and hypokinetic speech in parkinsonian diseases and cerebellar ataxia. We screened 804 perceptual speech analyses performed in the Samsung Medical Center Neurology Department between January 2017 and December 2020. The data of patients diagnosed with parkinsonian disorders or cerebellar ataxia were included. Two speech tasks (numbering from 1 to 50 and reading nine sentences) were analyzed. We adopted convolutional neural networks and developed a patch-wise wave splitting and integrating AI system for audio classification (PWSI-AI-AC) to differentiate between ataxic and hypokinetic speech. Of the 395 speech recordings for the reading task, 76, 112, and 207 were from normal, ataxic dysarthria, and hypokinetic dysarthria subjects, respectively. Of the 409 recordings of the numbering task, 82, 111, and 216 were from normal, ataxic dysarthria, and hypokinetic dysarthria subjects, respectively. The reading and numbering task recordings were classified with 5-fold cross-validation using PWSI-AI-AC as follows: hypokinetic dysarthria vs. others (area under the curve: 0.92 ± 0.01 and 0.92 ± 0.02), ataxia vs. others (0.93 ± 0.04 and 0.89 ± 0.02), hypokinetic dysarthria vs. ataxia (0.96 ± 0.02 and 0.95 ± 0.01), hypokinetic dysarthria vs. none (0.86 ± 0.03 and 0.87 ± 0.05), and ataxia vs. none (0.87 ± 0.07 and 0.87 ± 0.09), respectively. PWSI-AI-AC showed reliable performance in differentiating ataxic and hypokinetic dysarthria and effectively augmented data to classify the types even with limited training samples. The proposed fully automatic AI system outperforms neurology residents. Our model can provide effective guidelines for screening related diseases and differential diagnosis of neurodegenerative diseases.

Daily Exercise Patterns and Their Differences between Parkinson's Disease Patients with and without Postural Instability.

Background: Due to the clinical impact of exercise in patients with Parkinson's disease (PD), management should include personalized and effective exercises according to patient's PD stage. We investigated the detailed exercise behaviors of patients with mild to advanced PD and compared their patterns between PD with and without postural instability (PI). Methods: We enrolled PD patients from September to December 2019. Clinical data on parkinsonism, exercise behaviors, and Physical Activity Scale of the Elderly (PASE) scores were collected and compared between mild PD without PI (Hoehn-Yahr (HY) stages 1 and 2) and advanced PD with PI (HY stages 3 and 4). Results: In total, 263 PD patients were recruited. The mean exercise frequency was 4.7 ± 2.1 times/week, and the average duration was 7.8 ± 6.7 hours/week. The most common exercise was an aerobic exercise (71.9%) of mild-to-moderate intensity, with active walking being the most common (49.0%). The mild PD patients demonstrated a higher duration and intensity of exercise and more physical activity than the advanced PD patients. However, the frequency of exercise was not significantly different between the two groups. The PASE score was significantly higher in mild PD patients than in advanced PD patients (p < 0.001). Conclusion: PD patients focused mostly on aerobic exercises, especially active walking. With the disease progression, the amount and intensity of exercise decreased while frequency remained. Higher intensity of exercise is needed in the mild PD group, while the advanced PD group requires the increment of duration for each exercise session.