Movement Disorders最新文献

{"title":"Movement Disorders: Volume 40, Number 3, March 2025","authors":"","doi":"10.1002/mds.30177","DOIUrl":"10.1002/mds.30177","url":null,"abstract":"","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":"40 3","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mds.30177","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conversion between NMSS and MDS‐NMS in Parkinson's Disease","authors":"Michela Garon, José‐Manuel Rojo‐Albuin, K. Ray Chaudhuri, Alexandra Rizos, Carmen Rodriguez‐Blazquez, Eugenia Mamikonyan, Roberta Biundo, Anette Schrag, Daniel Weintraub, Angelo Antonini, Per Odin, Pablo Martinez‐Martin","doi":"10.1002/mds.30172","DOIUrl":"https://doi.org/10.1002/mds.30172","url":null,"abstract":"BackgroundThe burden of non‐motor symptoms in Parkinson's disease (PD) can be measured with the Non‐Motor Symptoms Scale (NMSS) and the International Parkinson and Movement Disorder Society Non‐Motor Rating Scale (MDS‐NMS), for which scoring systems, structure and clinical coverage differ.ObjectivesThe goal was to develop conversion formulas between the NMSS and the MDS‐NMS scores.MethodsData from 402 patients with PD participating in the primary MDS‐NMS validation study were used. The association between domain and total scores of both scales was assessed by the Spearman rank correlation coefficient and Kendall's <jats:italic>W</jats:italic> concordance coefficient. Equations for between‐scale transformation of total score were constructed from weighted linear regression models.ResultsSpearman rank correlations showed that MDS‐NMS domains correlated 0.39 to 0.88 with the corresponding NMSS domains. The equation for transforming the NMSS total score to MDS‐NMS total score is: MDS‐NMS = 11.629 + 1.624 × NMSS (<jats:italic>P</jats:italic> &lt; 0.001, <jats:italic>R</jats:italic><jats:sup>2</jats:sup> = 0.748). For converting the MDS‐NMS total score to NMSS total score, the formula is NMSS = 2.475 + 0.495 × MDS‐NMS (<jats:italic>P</jats:italic> &lt; 0.001, <jats:italic>R</jats:italic><jats:sup>2</jats:sup> = 0.771).ConclusionsOur conversion equations enable direct comparison of the NMSS and MDS‐NMS instruments, facilitating data comparability across studies. © 2025 International Parkinson and Movement Disorder Society.","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":"49 1","pages":""},"PeriodicalIF":8.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Heart of the Matter: Cardiac Denervation Casts Doubt on the Brain‐First Versus Body‐First Hypothesis of Parkinson's Disease","authors":"Tomoko Totsune, Toru Baba, Takafumi Hasegawa, Atsushi Takeda","doi":"10.1002/mds.30174","DOIUrl":"https://doi.org/10.1002/mds.30174","url":null,"abstract":"","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":"7 1","pages":""},"PeriodicalIF":8.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143653418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is Parkinson Disease Better Defined Solely by Biology or as a Clinical-Biological Entity? Lessons to be Learned from Alzheimer's Disease on Biological Definition and Staging.","authors":"Tiago A Mestre, Cristina Sampaio","doi":"10.1002/mds.30173","DOIUrl":"https://doi.org/10.1002/mds.30173","url":null,"abstract":"","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":" ","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Antidopaminergic Medications and Clinical Changes in Measures of Huntington's Disease: A Causal Analysis","authors":"Michal Geva, Y. Paul Goldberg, Henk Schuring, Andrew M. Tan, Jeffrey D. Long, Michael R. Hayden","doi":"10.1002/mds.30164","DOIUrl":"https://doi.org/10.1002/mds.30164","url":null,"abstract":"BackgroundAntidopaminergic medications (ADM) are often used for symptom management of Huntington's disease (HD). Evidence from past research suggests that ADMs are associated with worse clinical outcomes in HD, but their impact on various domains remains underexplored.ObjectiveWe used causal inference analysis to understand the impact of ADM use on measures of clinical progression in HD across multiple domains over 2 years.MethodsWe used the Enroll‐HD database with a new‐user design, which compared a cohort that initiated ADM use after the first visit with an unexposed cohort that remained <jats:italic>off</jats:italic> ADMs. To control for 27 covariates, we used a doubly robust <jats:italic>targeted maximum likelihood estimation</jats:italic> and conducted two analyses. First, we analyzed ADM treatment 2 years post‐baseline and separately for 12 outcome measures. Second, we examined the association of ADM dose with measures of clinical outcomes.ResultsThe ADM‐exposed group exhibited faster change in measures of clinical outcome compared with the <jats:italic>off</jats:italic>‐ADM group, which was statistically reliable in cognitive and functional outcome measures, and the composite Unified Huntington's Disease Rating Scale (cUHDRS). Motor domain analyses showed faster change in bradykinesia in the ADM‐exposed group versus <jats:italic>off</jats:italic>‐ADM but no difference in chorea or total motor score (TMS). Higher ADM doses also showed greater differences compared to the <jats:italic>off</jats:italic>‐ADM group.ConclusionsADM use was associated with more rapid change in clinical measures, particularly in cognitive and functional domains. However, assumptions required to establish causation between ADM use and disease progression may not have been fully met, and further research is warranted. © 2025 The Author(s). <jats:italic>Movement Disorders</jats:italic> published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":"9 1","pages":""},"PeriodicalIF":8.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143653427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Term Stability of Spatial Distribution and Peak Dynamics of Subthalamic Beta Power in Parkinson's Disease Patients.","authors":"Jennifer K Behnke, Robert L Peach, Jeroen G V Habets, Johannes L Busch, Jonathan Kaplan, Jan Roediger, Varvara Mathiopoulou, Lucia K Feldmann, Moritz Gerster, Juliette Vivien, Gerd-Helge Schneider, Katharina Faust, Patricia Krause, Andrea A Kühn","doi":"10.1002/mds.30169","DOIUrl":"https://doi.org/10.1002/mds.30169","url":null,"abstract":"<p><strong>Background: </strong>Subthalamic beta oscillations are a biomarker for bradykinesia and rigidity in Parkinson's disease (PD), incorporated as a feedback signal in adaptive deep brain stimulation with potential for guiding electrode contact selection. Understanding their longitudinal stability is essential for successful clinical implementation.</p><p><strong>Objectives: </strong>We aimed to analyze the long-term dynamics of beta peak parameters and beta power distribution along electrodes.</p><p><strong>Methods: </strong>We recorded local field potentials from 12 channels per hemisphere of 33 PD patients at rest, in a therapy-off state at two to four sessions (0, 3, 12, 18-44 months) post-surgery. We analyzed bipolar beta power (13-35 Hz) and estimated monopolar beta power in subgroups with consistent recordings.</p><p><strong>Results: </strong>During the initial 3 months, beta peak power increased (P < 0.0001). While detection of high-beta peaks was more consistent, low- and high-beta peak frequencies shifted substantially in some hemispheres during all periods. Spatial distribution of beta power correlated over time. Maximal beta power across segmented contact levels and directions was significantly stable compared with chance and increased in stability over time. Active contacts for therapeutic stimulation showed consistently higher normalized beta power than inactive contacts (P < 0.0001).</p><p><strong>Conclusions: </strong>Our findings indicate that beta power is a stable chronic biomarker usable for beta-guided programming. For adaptive stimulation, high-beta peaks might be more reliable over time. Greater stability of beta power, center frequency, and spatial distribution beyond an initial stabilization period suggests that the microlesional effect significantly impacts neuronal oscillations, which should be considered in routine clinical practice when using beta activity for automated programming algorithms. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</p>","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":" ","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Treatment for Dyskinesia in Parkinson's Disease: A Network Meta-analysis of Randomized Controlled Trials.","authors":"Rui Yan, Xiaoqing Zheng, Yixuan Yin, Junjiao Zhang, Yusha Cui, Dongning Su, Zhirong Wan, Tao Feng","doi":"10.1002/mds.30179","DOIUrl":"https://doi.org/10.1002/mds.30179","url":null,"abstract":"<p><strong>Background: </strong>Dyskinesia is a motor complication of Parkinson's disease (PD) posing therapeutic challenges. The optimal therapy for dyskinesia in PD has not been identified due to the lack of comprehensive evaluation of treatments.</p><p><strong>Objective: </strong>The aim was to compare the efficacy and safety of interventions for alleviating levodopa-induced dyskinesia in PD.</p><p><strong>Methods: </strong>We conducted a Bayesian network meta-analysis (NMA) by systematically searching PubMed, Web of Science, Embase, Cochrane Library, ClinicalTrials.gov, and EudraCT databases up to April 1, 2024. The primary efficacy outcome was the change in scores on dyskinesia rating scales from baseline.</p><p><strong>Results: </strong>The study included 85 randomized controlled trials (RCT) involving 13,826 PD patients, comprising 39 interventions. Nine treatments were significantly more effective in reducing scores on dyskinesia rating scales than control (placebo, sham surgery, sham repetitive transcranial magnetic stimulation, or best medical treatment). Globus pallidus interna deep brain stimulation (GPi-DBS) had the highest probability to be the most effective (standardized mean difference, 95% credible interval: -1.27, -1.65 to -0.88; surface under the cumulative ranking curve [SUCRA]: 97.4%), followed by levodopa-carbidopa intestinal gel infusion (SUCRA = 89.7%), subthalamic nucleus (STN)-DBS (SUCRA = 89%), immediate-release (IR) amantadine (SUCRA = 86.5%), pallidotomy (SUCRA = 84.9%), ADS-5102 (SUCRA = 82.9%), clozapine (SUCRA = 77.2%), OS320 (SUCRA = 64.8%), and AFQ056 (SUCRA = 54.5%). GPi-DBS was superior to STN-DBS, and pallidotomy ranked higher than subthalamotomy. ADS-5102 and OS320 had higher adverse event (AE) rates compared to control, whereas AFQ056 and ADS-5102 were linked to more serious AEs.</p><p><strong>Conclusions: </strong>This RCT-based NMA identifies and ranks nine efficacious interventions for dyskinesia in PD. GPi-DBS may be the most effective therapy for treating dyskinesia, with IR amantadine ranking highest among oral medications. Novel anti-dyskinetic medications are associated with less-favorable tolerance profiles. © 2025 International Parkinson and Movement Disorder Society.</p>","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":" ","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"NLX‐112 Randomized Phase 2A Trial: Safety, Tolerability, Anti‐Dyskinetic, and Anti‐Parkinsonian Efficacy","authors":"Per Svenningsson, Per Odin, Filip Bergquist, Karin Wirdefeldt, Dag Nyholm, Mattias Andréasson, Ioanna Markaki, Anders C. Johansson, Måns Jergil, Christopher Jankosky, Mark A. Varney, Fabienne Herbrecht, Steven A. Johnson, Adrian Newman‐Tancredi","doi":"10.1002/mds.30175","DOIUrl":"https://doi.org/10.1002/mds.30175","url":null,"abstract":"BackgroundLevodopa‐induced dyskinesia (LID) in Parkinson's disease (PD) is associated with ‘false neurotransmitter’ release of dopamine from serotonin (5‐HT) neurons. NLX‐112 is a first‐in‐class, highly selective 5‐HT<jats:sub>1A</jats:sub> receptor agonist which counteracts LIDs in experimental PD models.ObjectivesThe primary objective was to evaluate the safety and tolerability of NLX‐112 compared with placebo in people with PD. The secondary objective was to assess the preliminary efficacy of NLX‐112 in reducing LID and its effects on PD symptoms.MethodsParticipants received NLX‐112 or placebo (2:1 ratio) alongside stable Parkinson's medications, with 22 participants completing the study. Dosing was up‐titrated over 28 days to 2 mg/day (1 mg twice daily), stabilized for 14 days (to day 42), and down‐titrated for 14 days. Efficacy was measured using the Unified Dyskinesia Rating Scale (UDysRS), Unified Parkinson's Disease Rating Scale (UPDRS), and Clinical Global Impression of Change (CGI‐C) following a levodopa challenge (150% of usual dose).ResultsAdverse events (AEs) were mainly central nervous system (CNS)‐related and mostly occurred during up‐titration, with no serious AEs in the NLX‐112 group. There were no treatment‐induced clinically significant changes in vital signs, electrocardiogram, or laboratory parameters. NLX‐112 reduced LID from baseline levels: at day 42, UDysRS total score decreased by 6.3 points, whereas placebo group changes were not significant (−2.4). NLX‐112 also reduced parkinsonism from baseline values: UPDRS Part 3 scores decreased by 3.7 points, whereas placebo group changes were non‐significant (+0.1). In CGI‐C assessment, the NLX‐112 group showed greater improvement than the placebo group (53% vs. 29%).ConclusionThese results support further clinical investigation of NLX‐112 for treatment of PD LID. © 2025 Neurolixis SAS. <jats:italic>Movement Disorders</jats:italic> published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":"90 1","pages":""},"PeriodicalIF":8.6,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning–Based Artificial Intelligence Algorithm to Classify Tremors from Hand‐Drawn Spirals","authors":"Reghu Anandapadmanabhan, Aayushi Vishnoi, Geetha Raman, Jeena Thachan, Beulah Amulyavathi Gangaraju, Divya Radhakrishnan, Venugopalan Yamuna Vishnu, Nitish Kamble, Vikram Holla, Praveen James, Achal Srivastava, Deepak Joshi, Ashish Mahabal, Syam Krishnan, Pramod Pal, Roopa Rajan","doi":"10.1002/mds.30176","DOIUrl":"https://doi.org/10.1002/mds.30176","url":null,"abstract":"BackgroundNo objective biomarkers exist for diagnosing and classifying tremor syndromes.ObjectiveThe aim was to develop and validate a deep learning (DL) algorithm for classifying tremors from hand‐drawn pen‐on‐paper spirals.MethodsWe recruited participants with dystonic tremor (DT), essential tremor (ET), essential tremor plus (ETP), Parkinson's disease (PD), cerebellar ataxia (AT), and healthy volunteers (HV). Participants drew free‐hand spirals on paper, which were used to train a DL algorithm based on transfer learning using InceptionResNetV2 and Keras sequential model. We validated the model externally in two independent tremor cohorts, evaluating accuracy and F1 scores, and compared its performance to expert raters.ResultsWe recruited 521 participants and obtained 2078 spirals (365 DT, 215 ET, 208 ETP, 212 PD, 78 AT, and 525 HV). Mean age of the participants was 46.1 ± 12.4 years, duration of illness was 8.9 ± 8.3 years, and the mean Fahn–Tolosa–Marin Tremor Rating Scale score in patients was 32.4 ± 14.7. The DL classifier demonstrated an overall accuracy of 81% [95% confidence interval, CI: 0.77–0.85] in distinguishing among tremor syndromes. To mitigate the potential risks of data leakage and digital fingerprinting, the algorithm was redeveloped and reanalyzed, yielding an adjusted accuracy of 70% [95% CI: 0.66–0.74]. External validation on an independent cohort of 1535 spiral drawings resulted in an accuracy of 61% [95% CI: 0.59–0.63], with the adjusted algorithm achieving 59% [95% CI: 0.58–0.60], outperforming human raters (accuracy: 46%).ConclusionSupervised DL algorithms can effectively detect tremor syndromes from hand‐drawn spirals, offering unbiased, feature‐independent classification with higher accuracy than human raters. © 2025 International Parkinson and Movement Disorder Society.","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":"1 1","pages":""},"PeriodicalIF":8.6,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Obituary for C. Warren Olanow","authors":"José A. Obeso MD, PhD,&nbsp;Anthony H.V. Schapira MD, DSc, FRCP,&nbsp;Fabrizio Stocchi MD, PhD","doi":"10.1002/mds.30137","DOIUrl":"10.1002/mds.30137","url":null,"abstract":"","PeriodicalId":213,"journal":{"name":"Movement Disorders","volume":"40 3","pages":"398-399"},"PeriodicalIF":7.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}