NPJ Parkinson's Disease最新文献_第5页

Parkinson's disease: spatiotemporal regulation and therapeutic prospects of TREM2-mediated microglial responses. 帕金森病：trem2介导的小胶质细胞反应的时空调节和治疗前景

IF 8.7 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-13 DOI: 10.1038/s41531-025-01247-x

Keyuan Hou,Zhaowu An,Yuxiang Xu,Jing Wang,Meiru Zhou,Ye Liu,Xianfeng Zhu,Jianshe Wei

Parkinson's disease (PD) presents a challenge, with neuroinflammation and immune dysregulation central to its pathogenesis. This review examines TREM2-a microglial receptor governing phagocytosis, metabolic adaptation, and immune phenotypes-as an important orchestrator of innate immunity across PD, with roles that appear stage- and context-dependent. We synthesize structure, signaling, and heterogeneity; integrate single-cell multi-omics, animal models, and clinical data; outline conserved mechanisms; and consider translational implications as an investigational biomarker and therapeutic target, emphasizing spatiotemporal dynamics.

帕金森病（PD）提出了一个挑战，神经炎症和免疫失调是其发病机制的核心。这篇综述研究了trem2 -一种控制吞噬、代谢适应和免疫表型的小胶质受体-作为PD先天性免疫的重要协调者，其作用似乎与阶段和环境相关。我们综合了结构、信号和异质性；整合单细胞多组学、动物模型和临床数据；概述保守机制；并考虑作为研究生物标志物和治疗靶点的翻译意义，强调时空动态。

引用次数: 0

Data-driven clinical decision support tool for diagnosing mild cognitive impairment in Parkinson's disease. 诊断帕金森病轻度认知障碍的数据驱动临床决策支持工具。

IF 8.7 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-12 DOI: 10.1038/s41531-025-01222-6

Gabriel Martínez Tirado,Patricia Martins Conde,Stefano Sapienza,Holger Fröhlich,Claire Pauly,Valerie E Schröder,Sonja Jónsdóttir,Olena Tsurkalenko,Rejko Krüger,Jochen Klucken,

Parkinson's disease (PD) is a neurodegenerative condition that may affect both motor and cognitive function. Mild cognitive impairment (MCI) is a known risk factor for the progression to dementia in the later stages of the disease. Lengthy and time-consuming neuropsychological assessments, by trained experts, often make MCI diagnosis impractical in routine care. In this context, machine learning (ML) may offer promising support for MCI diagnosis. Thus, we analysed longitudinal data from 115 people with Parkinson's disease (PwPD) and 226 healthy control participants from the Luxembourg Parkinson's Study, combining ML with clinical data to support MCI diagnosis in PwPD. The data-driven model showed a non-inferior performance to the clinical diagnostic reference test (MDS PD-MCI Level II) and identified a subgroup of MCI individuals that was not captured by the clinical test. This finding suggests that ML models can complement clinical assessments, by facilitating the detection of MCI and complementing the diagnostic characterisation of PwPD.

帕金森病（PD）是一种神经退行性疾病，可能影响运动和认知功能。轻度认知障碍（MCI）是已知的疾病后期发展为痴呆的危险因素。由训练有素的专家进行冗长而耗时的神经心理学评估，往往使轻度认知障碍的诊断在常规护理中不切实际。在这种情况下，机器学习（ML）可能为MCI诊断提供有希望的支持。因此，我们分析了来自卢森堡帕金森研究的115名帕金森病患者（PwPD）和226名健康对照者的纵向数据，结合ML和临床数据来支持PwPD的MCI诊断。数据驱动模型的表现不逊于临床诊断参考测试（MDS PD-MCI II级），并确定了临床测试未捕获的MCI个体亚组。这一发现表明，ML模型可以通过促进MCI的检测和补充PwPD的诊断特征来补充临床评估。

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引用次数: 0

Delphinidin modulates neuroinflammation and behavioral deficits in a Parkinson's disease mouse model. 飞燕草苷调节帕金森病小鼠模型的神经炎症和行为缺陷。

IF 8.7 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-12 DOI: 10.1038/s41531-025-01244-0

A Grotemeyer,S Alexander,L Frieß,J Roewer,E E Bankoglu,M Badr,J Wu,H Stopper,J Volkmann,N Roewer,C W Ip

Neuroinflammation is deeply intertwined with dopaminergic (DA) neurodegeneration in Parkinson's disease (PD). We tested whether delphinidin, an anthocyanidin with reported inflammasome/NF-κB modulatory activity, alters neuroinflammation and nigrostriatal integrity in a progressive AAV1/2-A53T α-synuclein (hαSYN) mouse model. Once-daily intraperitoneal delphinidin for nine weeks modestly ameliorated asymmetric forepaw use, attenuated the hαSYN-induced loss of striatal TH⁺ terminal density, and was associated with modest alterations in dopamine turnover, yet did not prevent the loss of DA neurons in the substantia nigra (SN). On the immunological level, delphinidin attenuated the innate immune response by reducing the number and activity of CD11b+ microglia in both the SN and striatum. In contrast, CD4+-mediated adaptive inflammation remained unchanged, while the number of CD8+ T cells increased in the SN. Notably, approximately 48% of CD8+ T cells in the SN of these mice were identified as CD8+CD122+ regulatory T cells, known for their anti-inflammatory properties. In conclusion, delphinidin was associated with a partial attenuation of neuroinflammatory changes and a context-dependent shift towards a more anti-inflammatory CD8⁺CD122+ T cell phenotype in the SN. However, these changes did not translate into protection of SN DA somata, revealing a dissociation between striatal terminal preservation and nigral cell body survival, and underscoring the limitations of targeting innate immunity alone under the current dosing paradigm.

帕金森氏病（PD）的神经炎症与多巴胺能（DA）神经退行性变密切相关。在进行性AAV1/2-A53T α-突触核蛋白（h -syn）小鼠模型中，我们检测了飞鸽苷（一种报道具有炎性体/NF-κB调节活性的花青素）是否会改变神经炎症和黑质纹状体完整性。连续9周每天一次腹腔注射海啡肽可适度改善前爪不对称使用，减轻hα syn诱导的纹状体TH +终端密度的损失，并与多巴胺周转量的适度改变相关，但不能防止黑质（SN） DA神经元的损失。在免疫学水平上，飞鸽苷通过降低SN和纹状体中CD11b+小胶质细胞的数量和活性来减弱先天免疫反应。相比之下，CD4+介导的适应性炎症保持不变，而SN中CD8+ T细胞数量增加。值得注意的是，这些小鼠SN中约48%的CD8+ T细胞被鉴定为CD8+CD122+调节性T细胞，以其抗炎特性而闻名。总之，飞燕草苷与SN中神经炎症变化的部分衰减和向更抗炎的CD8 + CD122+ T细胞表型的环境依赖性转变有关。然而，这些变化并没有转化为SN DA体细胞的保护，揭示了纹状体终末保存和黑质细胞体存活之间的分离，并强调了在目前的剂量模式下仅针对先天免疫的局限性。

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引用次数: 0

Moving beyond the hospital: in-depth characterization of daily-life mobility in patients with atypical Parkinsonian disorders. 超越医院：非典型帕金森病患者日常生活活动能力的深入表征。

IF 8.7 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-12 DOI: 10.1038/s41531-025-01242-2

Victoria Sidoroff,Hamid Moradi,Gaëlle Prigent,Frank Jagusch,Isabelle Teckenburg,Marzieh Asalian,Nina Hergenroeder-Lenzner,Marijus Giraitis,Eva Tabea Schoenfeldt-Reichmann,Jean-Pierre Ndayisaba,Georg Goebel,Klaus Seppi,Anisoara Ionescu,Florian Krismer,David Benninger,Juergen Winkler,Bjoern M Eskofier,Jochen Klucken,Kamiar Aminian,Gregor Wenning,Stefano Sapienza,Heiko Gassner,Cecilia Raccagni,

This study evaluates mobility in patients with multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and Parkinson's disease (PD) by integrating clinical assessments, instrumented gait analysis (IGA) in the hospital, and 1 week of physical activity monitoring (PAM) at home, using wearable sensors. Clinical scores provide a broad measure of disease severity but lack precision in quantifying gait impairments. IGA offers objective gait metrics under standardized conditions, identifying deficits in stride dynamics and postural control. However, these controlled assessments do not reflect real-world mobility. PAM addresses this gap by continuously tracking movement patterns and physical activity during daily-life, offering insights into how patients walk beyond clinical settings. The combination of IGA and PAM provides a more comprehensive understanding of mobility limitations, particularly in MSA and PSP, where gait and balance impairments differ from PD. This dual approach enhances patient assessment, supports personalized disease management, and improves clinical decision-making. Trial registration: ClinicalTrials.gov, NCT04608604, date of registration: 19/10/2020, first patient enrollment: 01/02/2021.

本研究通过综合临床评估、医院的仪器步态分析（IGA）和家中1周的可穿戴传感器身体活动监测（PAM），评估多系统萎缩（MSA）、进行性核上性麻痹（PSP）和帕金森病（PD）患者的活动能力。临床评分提供了疾病严重程度的广泛测量，但在量化步态障碍方面缺乏准确性。IGA在标准化条件下提供客观的步态指标，识别步幅动力学和姿势控制的缺陷。然而，这些受控评估并不能反映现实世界的流动性。PAM通过持续跟踪日常生活中的运动模式和身体活动来解决这一差距，为患者在临床环境之外的行走方式提供见解。IGA和PAM的结合提供了对活动受限的更全面的理解，特别是在MSA和PSP中，步态和平衡障碍不同于PD。这种双重方法增强了患者评估，支持个性化疾病管理，并改善了临床决策。试验注册：ClinicalTrials.gov, NCT04608604，注册日期：2020年10月19日，首次患者入组：2021年2月1日。

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引用次数: 0

Data-driven subtyping of early Parkinson's disease via mutual cross-attention fusion of EEG and dual-task gait features. 通过相互交叉注意融合EEG和双任务步态特征的早期帕金森病数据驱动亚型。

IF 8.7 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-12 DOI: 10.1038/s41531-026-01258-2

Deyu Wang,Yu Shi,Jun Pang,Xiaodong Zhu,Lin Meng,Dong Ming

Parkinson's disease (PD) exhibits marked clinical heterogeneity, which poses challenges for diagnosis, prognosis, and therapeutic precision, especially for early-stage PD patients. Existing subtyping approaches often rely on subjective clinical scales and single-modality data, which limits their sensitivity in capturing subtle but clinically relevant differences across patients. To reveal clinically meaningful PD subtypes, we propose a data-driven multimodal framework that integrates resting-state electroencephalography (EEG) and dual-task gait features using mutual cross-attention (MCA) fusion. Forty idiopathic early-stage PD patients were enrolled in a prospective study. EEG biomarkers were encoded via a convolutional neural network for the prediction of motor severity (MDS-UPDRS-III), while dual-task gait features were derived to capture subtle motor dysfunctions. The MCA enabled bidirectional attention-guided integration of EEG and gait features, which were then clustered using an unsupervised method. The analysis revealed three distinct subtypes, with dual-task-based fusion providing superior clinical separation. Subtype I was characterized by pronounced motor deficits; Subtype II showed moderate symptoms with relatively preserved quality of life; and Subtype III presented mild motor impairments but exhibited poorer cognitive and psychosocial outcomes. Feature contribution analyses highlighted central beta and theta EEG activity, along with dual-task gait metrics (e.g., stride length during turning), as key drivers of subtype differentiation. Longitudinal follow-up demonstrated subtype-specific rehabilitation responses, with Subtype II showing an insufficient response compared to other subtypes. In conclusion, this study enables digital phenotyping of PD with prognostic implications for personalized rehabilitation strategies and accelerates precision medicine.

帕金森病（PD）具有明显的临床异质性，这给诊断、预后和治疗精度带来了挑战，尤其是对早期PD患者。现有的亚型分型方法通常依赖于主观临床量表和单模态数据，这限制了它们在捕捉患者之间细微但临床相关差异方面的敏感性。为了揭示具有临床意义的PD亚型，我们提出了一个数据驱动的多模式框架，该框架使用相互交叉注意（MCA）融合将静息状态脑电图（EEG）和双任务步态特征集成在一起。40名特发性早期PD患者参加了一项前瞻性研究。脑电图生物标志物通过卷积神经网络编码，用于预测运动严重程度（MDS-UPDRS-III），同时推导双任务步态特征，以捕获细微的运动功能障碍。MCA实现了双向注意引导的EEG和步态特征整合，然后使用无监督方法对其进行聚类。分析显示了三种不同的亚型，双任务融合提供了优越的临床分离。亚型1以明显的运动缺陷为特征；亚型II表现为中度症状，生活质量相对保持；亚型III表现为轻度运动障碍，但表现出较差的认知和社会心理结局。特征贡献分析强调了中央β和θ脑电图活动，以及双任务步态指标（例如，转弯时的步长）是亚型分化的关键驱动因素。纵向随访显示亚型特异性康复反应，与其他亚型相比，亚型II表现出不足的反应。总之，这项研究使PD的数字表型具有个性化康复策略和加速精准医疗的预后意义。

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引用次数: 0

An eight-year follow-up of the CMSAR: assessing how the new MDS criteria and biomarkers impact diagnostic accuracy. CMSAR的8年随访：评估新的MDS标准和生物标志物如何影响诊断准确性。

IF 8.2 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-10 DOI: 10.1038/s41531-025-01217-3

Alexandra Pérez Soriano, Cèlia Painous, Manel Fernandez, Jesica Pérez, Raquel Ruiz-Garcia, Laura Naranjo, Ana Camara, Iban Aldecoa, Laura Molina, Yaroslau Compta, Esteban Muñoz, Maria J Martí

Multiple system atrophy (MSA) is a rare, progressive neurodegenerative disorder with high mortality and diagnostic uncertainty. We re-evaluated 80 cases from the Catalan MSA Registry (CMSAR), applying the 2022 MDS diagnostic criteria and cerebrospinal fluid biomarkers, including α-synuclein seeding assays (asyn-SAA) and neurofilament light chain (NfL). Clinical and biomarker reassessment was performed in 2022-2023. At re-evaluation, 20 patients were alive; 14 were reclassified as non-MSA and three as unclassifiable. MSA cases had shorter survival (8.8 vs 14.8 years, p = 0.001), and dysphagia predicted poorer outcomes. The 2022 criteria showed higher specificity (94% for clinically established, 71% for probable) than the 2008 criteria. NfL levels were significantly higher in MSA (p = 0.005) and predicted mortality. Asyn-SAA was negative in confirmed MSA cases and positive in three suspected Parkinson's disease cases. These findings support the added diagnostic value of integrating updated criteria and CSF biomarkers to improve MSA classification and long-term monitoring.

多系统萎缩（MSA）是一种罕见的进行性神经退行性疾病，具有高死亡率和诊断不确定性。我们应用2022年MDS诊断标准和脑脊液生物标志物，包括α-突触核蛋白种子测定（asyna - saa）和神经丝轻链（NfL），对来自加泰罗尼亚MSA Registry （CMSAR）的80例患者进行了重新评估。在2022-2023年进行临床和生物标志物重新评估。重新评估时，20例患者存活；14个被重新分类为非msa， 3个被重新分类为不可分类。MSA患者的生存期较短（8.8年vs 14.8年，p = 0.001），吞咽困难预示着较差的预后。与2008年的标准相比，2022年的标准显示出更高的特异性（94%为临床确定，71%为可能）。MSA患者的NfL水平显著升高（p = 0.005）并预测死亡率。在MSA确诊病例中，asyns - saa呈阴性，在3例帕金森病疑似病例中呈阳性。这些发现支持整合更新的标准和CSF生物标志物来改善MSA分类和长期监测的附加诊断价值。

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引用次数: 0

Metabolomic breath landscape analysis unravels lipid biomarker candidates in patients with genetic and idiopathic Parkinson's disease. 代谢组学呼吸景观分析揭示了遗传性和特发性帕金森病患者的脂质生物标志物候选物。

IF 8.2 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-10 DOI: 10.1038/s41531-025-01255-x

Madiha Malik, Norbert Brüggemann, Tatiana Usnich, Max Borsche, Tobias Demetrowitsch, Björn-Hergen Laabs, Karin Schwarz, Peter Bauer, Katja Lohmann, Christine Klein, Thomas Kunze

Parkinson's disease (PD) is the fastest growing neurodegenerative disorder. The current lack of efficient early diagnostic tools necessitates novel approaches to biomarker discovery. We propose an untargeted metabolomics approach using non-invasive exhaled breath analysis. Breath samples, collected from 73 PD patients, encompassing both genetic (LRRK2: n = 12, GBA1: n = 35, PRKN: n = 6) and idiopathic PD (n = 20), 4 unaffected LRRK2 pathogenic variant carriers, and 90 controls underwent extreme-resolution FT-ICR-MS analysis. Findings were compared with metabolomics data from blood plasma. Biostatistical analyses identified discernible metabolic patterns in both biofluids, enabling differentiation of PD patients from healthy controls (OOB error < 1%). Metabolomic breath profiling of PD patients yielded 7 significant metabolites putatively identified as tricosanoic acid, docosanamide, eicosanoic acid, homophytanic acid, nonadecyl-MG, stearic acid, and palmitic acid in PD patients, irrespective of the genetic status. Five of these metabolites were also found in unaffected carriers of pathogenic variants in LRRK2 when compared to controls. Most of the proposed structures are intermediates in fatty acid metabolism, introducing new candidate biomarkers for breath analysis in PD, although their identities require MS/MS confirmation. Breath analysis effectively distinguishes between PD patients and healthy controls and can identify metabolites that could serve as noninvasive biomarkers for PD, potentially including its presymptomatic stage.

帕金森病（PD）是发展最快的神经退行性疾病。目前缺乏有效的早期诊断工具，需要新的方法来发现生物标志物。我们提出了一种使用无创呼气分析的非靶向代谢组学方法。采集73例PD患者的呼吸样本，包括遗传性（LRRK2: n = 12, GBA1: n = 35, PRKN: n = 6）和特发性PD (n = 20)， 4名未受影响的LRRK2致病变异携带者和90名对照组，进行了极分辨率FT-ICR-MS分析。研究结果与血浆代谢组学数据进行了比较。生物统计学分析确定了两种生物体液中可识别的代谢模式，从而能够将PD患者与健康对照组区分开来（OOB误差< 1%）。PD患者的代谢组学呼吸分析得出了7种重要的代谢物，这些代谢物被推定为PD患者的三糖酸、二十二糖酰胺、二十糖酸、同型植物酸、壬烷基- mg、硬脂酸和棕榈酸，与遗传状况无关。与对照组相比，在LRRK2致病性变异未受影响的携带者中也发现了其中五种代谢物。大多数被提出的结构是脂肪酸代谢的中间体，为PD的呼吸分析提供了新的候选生物标志物，尽管它们的身份需要MS/MS确认。呼吸分析可以有效地区分PD患者和健康对照组，并可以识别代谢物，这些代谢物可以作为PD的无创生物标志物，可能包括其症状前阶段。

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引用次数: 0

Subthalamic nucleus in patients with Parkinson’s disease encodes changes and magnitude of applied force 帕金森病患者的丘脑下核编码施加力的变化和大小

IF 8.7 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-10 DOI: 10.1038/s41531-025-01237-z

Joseph Olson, Shaikh Sharar Wahid, Zachary T. Irwin, Daniel Kuhman, Christopher L. Gonzalez, Maria Boolos, Sarah Black, Barton L. Guthrie, Thomas Wichmann, Harrison C. Walker

引用次数: 0

Video-based machine learning models for predicting deep brain stimulation outcomes in Parkinson's disease patients. 基于视频的机器学习模型用于预测帕金森病患者的深部脑刺激结果。

IF 8.7 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-09 DOI: 10.1038/s41531-025-01252-0

Tianxue Hu,Quan Zhang,Zixiao Yin,Yichen Xu,Boya Dong,Qi An,Yanwen Wang,Yifei Gan,Houyou Fan,Zehua Zhao,Zhaoting Zheng,Rujin Wang,Xianze Li,Pengda Yang,Hutao Xie,Jianguo Zhang,Anchao Yang

Current levodopa challenge test (LCT) for deep brain stimulation (DBS) candidate screening in Parkinson's disease (PD) relies on subjective clinical scales, limiting its predictive capacity for postoperative motor outcomes. We developed video-based machine learning models using quantified kinematic metrics during preoperative LCT in seventy PD patients who underwent DBS surgery. Objective multi-domain motor features were extracted via validated motor assessment software. Binary classification defined patients' outcomes as DBS+ (≥30% improvement in MDS-UPDRS Part III) or DBS- (<30%). Ternary classification further categorized outcomes as DBS + + (≥ 60%) and DBS+ - (30-60%). Results show: (1) For binary classification (DBS + /DBS - ), Linear Discriminant Analysis (LDA) achieved an F1 score of 0.87 (Receiver Operating Characteristic Area Under Curve (ROC AUC) = 0.77, accuracy = 0.8). (2) For ternary efficacy stratification, LDA attained a weighted F1 score of 0.67 (average ROC AUC = 0.67, accuracy = 0.67). (3) Models combining video-derived features with conventional clinical predictors significantly outperformed the baseline logistic regression model that included only conventional clinical predictors. (4) Clinical interpretation: Velocity-driven domains demonstrated key contributions in both binary and ternary outcome predictions, while amplitude- and stability-related metrics also played a supporting role. Axial parameter aided in identifying DBS responsiveness, and asymmetric levodopa response patterns were found to stratify efficacy tiers. Although linear models performed well, non-monotonic relationships between specific metrics and motor outcomes were identified. This analytical approach serves as a complementary tool for specialists, strengthening preoperative screening through objective motor-responsiveness profiles derived from LCT video, potentially promoting data-driven patient selection and personalized surgical consultation in the future.

目前用于帕金森病（PD）深部脑刺激（DBS）候选筛查的左旋多巴激发试验（LCT）依赖于主观临床量表，限制了其对术后运动预后的预测能力。我们在70例接受DBS手术的PD患者术前LCT期间使用量化的运动学指标开发了基于视频的机器学习模型。目的利用经过验证的运动评估软件提取多域运动特征。二元分类将患者的预后定义为DBS+ （MDS-UPDRS第三部分改善≥30%）或DBS-(<30%)。三元分类进一步将结果分为DBS+ +(≥60%)和DBS+ -(30-60%)。结果表明：(1)对于二元分类（DBS + /DBS -），线性判别分析（LDA）的F1得分为0.87（受试者工作特征曲线下面积(ROC AUC) = 0.77，准确率= 0.8）。(2)对于三元疗效分层，LDA的加权F1评分为0.67（平均ROC AUC = 0.67，准确率= 0.67）。(3)视频衍生特征与常规临床预测因子相结合的模型显著优于仅包含常规临床预测因子的基线逻辑回归模型。(4)临床解释：速度驱动域在二元和三元预后预测中都发挥了关键作用，而振幅和稳定性相关指标也发挥了辅助作用。轴向参数有助于识别DBS反应性，发现不对称左旋多巴反应模式可分层疗效等级。虽然线性模型表现良好，但确定了特定指标与运动结果之间的非单调关系。这种分析方法可以作为专家的补充工具，通过LCT视频获得的客观运动反应性资料加强术前筛查，潜在地促进数据驱动的患者选择和个性化手术咨询。

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引用次数: 0

Propensity-matched multicenter comparison of Parkinson’s disease outcomes with and without deep brain stimulation 倾向匹配的帕金森病结果的多中心比较，有和没有深部脑刺激

IF 8.7 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease

Pub Date : 2026-01-08 DOI: 10.1038/s41531-025-01251-1

Alireza Gharabaghi, Farzin Negahbani, Marius Keute

Subthalamic deep brain stimulation is established for Parkinson’s disease, reducing funding for randomized trials and necessitating complementary approaches to assess outcomes in broader clinical contexts. Using publicly available multicenter data, we compared propensity-matched patients with and without stimulation. The intervention was associated with improved mid-term patient-reported motor and non-motor experiences of daily living, while ongoing follow-up will clarify long-term effects. This demonstrates feasibility of matched comparisons in open observational cohorts.

丘脑下深部脑刺激被用于治疗帕金森病，减少了对随机试验的资助，并需要在更广泛的临床背景下评估结果的补充方法。使用公开的多中心数据，我们比较了倾向匹配的患者有和没有刺激。干预与中期患者报告的日常生活运动和非运动体验的改善有关，而正在进行的随访将阐明长期效果。这证明了在开放观察队列中进行匹配比较的可行性。

引用次数: 0