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帕金森病专家对常见脑深部电刺激编程实践的调查。

Survey of common deep brain stimulation programming practices by experts in Parkinson's Disease.

作者信息

Cunningham J E, Cabrera L Y, Mahajan A, Aslam S, De Jesus S, Brennan R, Jimenez-Shahed J, Aquino C C, Xie T, Vaou E O, Patel N, Spindler M, Mills K A, Zhang L, Bertoni J, Sidiropoulos C, Miocinovic S, Walter B L, Panov F, Zauber S E, Sarva H

机构信息

College of Human Medicine, Michigan State University, East Lansing, MI, USA.

Department of Engineering Science and Mechanics, Center for Neural Engineering, and Rock Ethics Institute, The Pennsylvania State University, W-316 Millennium Science Complex, University Park, PA, 16802, USA.

出版信息

J Neurol. 2024 Dec 12;272(1):49. doi: 10.1007/s00415-024-12751-0.

DOI:10.1007/s00415-024-12751-0
PMID:39666124
Abstract

OBJECTIVE

Identify consensus and variability in deep brain stimulation (DBS) programming practices for Parkinson's disease.

BACKGROUND

DBS programming relies on the personal experience and skills of programmers. Despite consensus statements, there aren't official guidelines for DBS programming, making it likely for protocols to vary among providers.

METHODS

We administered an online survey to the Functional Neurosurgery Working Group of the Parkinson's Study Group to capture those actively programming DBS patients. We performed descriptive statistics and comparisons of responses based on career stage: early (0-10 years) versus later (>10 years).

RESULTS

Boston Scientific (n = 15/31, 48%) and Medtronic (n = 14/35, 40%) are the two DBS systems ranked as most used, with less reported frequency of Abbott devices (n = 4/32, 12.5). Traditional monopolar review ranked as the most common initial programming strategy by 23/29 (79%) respondents, regardless of the device type implanted. Monopolar omnidirectional testing was the most often used approach for contact configuration at initial programming (24/33, 73%).For treating dyskinesia, tremor, bradykinesia, rigidity, speech-related side effects, non-motor adverse effects, or swallowing-related side effects, the most likely optimization strategy selected was to modify amplitude of the active contact. When treating freezing of gait, there was a divergence between first modifying amplitude (n = 11/29, 38%) or frequency (n = 12/33, 36%).

CONCLUSION

Initial programming practices generally align with published recommendations, which can reassure less experienced clinicians in practices with near consensus and allow them to devote more time to areas with wider variety of practice. Our data also highlights aspects of DBS programming with less consensus, demonstrating the need for future evidence.

摘要

目的

确定帕金森病深部脑刺激(DBS)编程实践中的共识和变异性。

背景

DBS编程依赖于程序员的个人经验和技能。尽管有共识声明,但尚无DBS编程的官方指南,这使得不同提供者的方案可能存在差异。

方法

我们对帕金森研究组功能神经外科工作组进行了一项在线调查,以了解那些积极为DBS患者进行编程的人员。我们根据职业阶段(早期[0 - 10年]与后期[>10年])进行描述性统计和反应比较。

结果

波士顿科学公司(n = 15/31,48%)和美敦力公司(n = 14/35,40%)是被列为使用最多的两种DBS系统,雅培设备的报告使用频率较低(n = 4/32,12.5%)。23/29(79%)的受访者将传统单极复查列为最常见的初始编程策略,无论植入的设备类型如何。单极全向测试是初始编程时最常用的触点配置方法(24/33,73%)。对于治疗异动症、震颤、运动迟缓、僵硬、言语相关副作用、非运动不良反应或吞咽相关副作用,最常选择的优化策略是调整有源触点的幅度。在治疗步态冻结时,首先调整幅度(n = 11/29,38%)或频率(n = 12/33,36%)之间存在差异。

结论

初始编程实践总体上与已发表的建议一致,这可以让经验不足的临床医生在接近共识的实践中放心,并使他们能够将更多时间投入到实践差异较大的领域。我们的数据还突出了DBS编程中共识较少的方面,表明未来需要更多证据。

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本文引用的文献

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Premotor cortical beta synchronization and the network neuromodulation of externally paced finger tapping in Parkinson's disease.帕金森病患者外部节拍手指敲击的运动前皮质β同步和网络神经调节。
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EEG-based biomarkers for optimizing deep brain stimulation contact configuration in Parkinson's disease.基于脑电图的生物标志物用于优化帕金森病深部脑刺激的触点配置
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Local Field Potentials Predict Motor Performance in Deep Brain Stimulation for Parkinson's Disease.
局部场电位可预测帕金森病深部脑刺激中的运动表现。
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Feasibility of local field potential-guided programming for deep brain stimulation in Parkinson's disease: A comparison with clinical and neuro-imaging guided approaches in a randomized, controlled pilot trial.帕金森病深部脑刺激中局部场电位引导编程的可行性:一项随机对照试验中与临床和神经影像学引导方法的比较
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StimFit-A Data-Driven Algorithm for Automated Deep Brain Stimulation Programming.StimFit-A:一种用于自动深部脑刺激编程的数据驱动算法
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Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning.使用功能磁共振成像和机器学习预测帕金森病的最佳深部脑刺激参数。
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Effect of Deep Brain Stimulation on Swallowing Function: A Systematic Review.深部脑刺激对吞咽功能的影响:一项系统综述
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