Unsupervised Machine Learning Revealed that Repeat Transcranial Magnetic Stimulation is More Suitable for Stroke Patients with Statin.

IF 3.9 3区医学 Q1 CLINICAL NEUROLOGY

Neurology and Therapy Pub Date : 2024-06-01 Epub Date: 2024-04-30 DOI:10.1007/s40120-024-00615-8

Chaohua Cui, Changhong Li, Tonghua Long, Zhenxian Lao, Tianyu Xia

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引用次数: 0

Abstract

Introduction: Repeat transcranial magnetic stimulation (rTMS) demonstrates beneficial effects for stroke patients, though its efficacy varies due to the complexity of patient conditions and disease progression. Unsupervised machine learning could be the optimal solution for identifying target patients for transcranial magnetic stimulation treatment.

Methods: We collected data from ischaemic stroke patients treated with rTMS. Unsupervised machine learning methods, including K-means and Hierarchical Clustering, were used to explore the clinical characteristics of patients suitable for rTMS. We then utilized a prospective observational cohort to validate the effect of selected characteristics. For the validated cohort, outcomes included the presence of motor evoked potentials (MEP), favorable functional outcomes (FFO), and changes in the Fugl-Meyer Assessment (FMA) at 3 and 6 months.

Results: Hierarchical clustering methods revealed that patients in the better prognosis group were more likely to take statins. The validated cohort was grouped based on statin intake. Patients taking statins exhibited a higher rate of MEP (p = 0.006), a higher rate of FFO at 3 months (p = 0.003) and 6 months (p = 0.021), and a more significant change in FMA (p < 0.001) at both 3 and 6 months. Statin intake was associated with FFO and changes in FMA at 3 and 6 months. This relationship persisted across all subgroups for FMA changes and some FFO subgroups.

Conclusion: Stroke patients undergoing rTMS treatment taking statins exhibited greater MEP, FFO, and changes in FMA. Statin intake was associated with a better prognosis in these patients.

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无监督机器学习发现重复经颅磁刺激更适合服用他汀类药物的中风患者

简介：重复经颅磁刺激（rTMS）对脑卒中患者有益，但由于患者病情和疾病进展的复杂性，其疗效也不尽相同。无监督机器学习可能是识别经颅磁刺激治疗目标患者的最佳解决方案：方法：我们收集了接受经颅磁刺激治疗的缺血性脑卒中患者的数据。方法：我们收集了接受经颅磁刺激治疗的缺血性脑卒中患者的数据，并使用无监督机器学习方法（包括 K-means 和层次聚类）来探索适合经颅磁刺激治疗的患者的临床特征。然后，我们利用前瞻性观察队列验证了所选特征的效果。验证队列的结果包括出现运动诱发电位（MEP）、良好的功能结果（FFO）以及 3 个月和 6 个月时 Fugl-Meyer 评估（FMA）的变化：层次聚类法显示，预后较好组的患者更有可能服用他汀类药物。根据他汀类药物的摄入量对验证队列进行了分组。服用他汀类药物的患者表现出更高的MEP率（p = 0.006）、3个月时更高的FFO率（p = 0.003）和6个月时更高的FFO率（p = 0.021），以及更显著的FMA变化（p 结论：接受经颅磁刺激治疗并服用他汀类药物的脑卒中患者表现出更大的MEP、FFO和FMA变化。他汀类药物的摄入与这些患者较好的预后有关。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Neurology and Therapy CLINICAL NEUROLOGY-

CiteScore

5.40

自引率

8.10%

发文量

103

审稿时长

6 weeks

期刊介绍： Aims and Scope Neurology and Therapy aims to provide reliable and inclusive, rapid publication for all therapy related research for neurological indications, supporting the timely dissemination of research with a global reach, to help advance scientific discovery and support clinical practice. Neurology and Therapy is an international, open access, peer reviewed, rapid publication journal dedicated to the publication of high-quality clinical (all phases), observational, real-world and health outcomes research around the discovery, development, and use of neurological and psychiatric therapies, (also covering surgery and devices). Studies relating to diagnosis, pharmacoeconomics, public health, quality of life, and patient care, management, and education are also welcomed. The journal is of interest to a broad audience of healthcare professionals and publishes original research, reviews, case reports, trial designs, communications and letters. 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