机器学习解释了深部脑刺激对帕金森病患者生活质量的影响。

IF 12.4 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Enrico Ferrea, Farzin Negahbani, Idil Cebi, Daniel Weiss, Alireza Gharabaghi
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引用次数: 0

摘要

改善与健康相关的生活质量(QoL)对于帕金森病的治疗至关重要。然而,眼下核(STN)深部脑刺激(DBS)后的 QoL 结果差异很大。目前的方法缺乏对人口统计学、患者报告、神经影像学和神经生理学数据的整合,无法理解这种差异性。本研究使用可解释的机器学习分析了影响 QoL 变化的多模式因素(通过帕金森病问卷 (PDQ-39) 测量 63 名患者的 QoL 变化),并量化了每个变量的贡献。结果显示,术前的 PDQ-39 评分和左侧 STN 的上贝塔带活动(>20 Hz)是预测 QoL 变化的关键因素。较低的初始 QoL 负担预示着恶化,而改善则与较高的β活动相关。此外,沿上-下轴的电极位置,尤其是相对于标准空间中 z = -7 坐标的电极位置,也会影响结果,在此标记上下的 QoL 有改善也有恶化。这项研究强调了一种量身定制、以数据为依据的方法,以优化 DBS 治疗并改善患者的 QoL。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Machine learning explains response variability of deep brain stimulation on Parkinson’s disease quality of life

Machine learning explains response variability of deep brain stimulation on Parkinson’s disease quality of life

Machine learning explains response variability of deep brain stimulation on Parkinson’s disease quality of life
Improving health-related quality of life (QoL) is crucial for managing Parkinson’s disease. However, QoL outcomes after deep brain stimulation (DBS) of the subthalamic nucleus (STN) vary considerably. Current approaches lack integration of demographic, patient-reported, neuroimaging, and neurophysiological data to understand this variability. This study used explainable machine learning to analyze multimodal factors affecting QoL changes, measured by the Parkinson’s Disease Questionnaire (PDQ-39) in 63 patients, and quantified each variable’s contribution. Results showed that preoperative PDQ-39 scores and upper beta band activity (>20 Hz) in the left STN were key predictors of QoL changes. Lower initial QoL burden predicted worsening, while improvement was associated with higher beta activity. Additionally, electrode positions along the superior-inferior axis, especially relative to the z = −7 coordinate in standard space, influenced outcomes, with improved and worsened QoL above and below this marker. This study emphasizes a tailored, data-informed approach to optimize DBS treatment and improve patient QoL.
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来源期刊
CiteScore
25.10
自引率
3.30%
发文量
170
审稿时长
15 weeks
期刊介绍: npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.
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