Abstract
Classify patients with Parkinson’s disease (PD) tremor based on the heterogeneity of
clinical features and electrophysiological characteristics of tremor. Methods: Clinical data (including motor
symptoms, non-motor symptoms, progression rate, disease stage) and electrophysiological characteristics of 220
patients with PD tremor were collected. Based on these clinical features and electrophysiological parameters,
these patients were classified by K-means cluster analysis. We used the silhouette coefficients corresponding to K
ranging from 2 to 10 to determine the optimal number of clusters. Results: Based on the above methods, PD
patients with tremor were clustered into two subtypes. (1) Subtype 1 (85 cases): rapid progression of tremor,
good response to levodopa, and electromyographic analysis showing predominantly 4~6 Hz resting tremor; (2)
Subtype 2 (135 cases): slow progression of tremor, poor response to levodopa, and electromyographic analysis
revealing irregular jerky movements. Significant differences were observed between the two subtypes in disease
duration, motor symptom scores, rigidity scores, tremor scores, axial symptom scores, levodopa-equivalent
doses, rigidity/tremor score ratios, progression rates of tremor, responsiveness of motor symptoms and tremor to
levodopa, frequency distribution of upper limb resting, postural, intentional, and postural action tremors, as well
as patterns of muscle contraction (all P<0.05). Conclusion: There is heterogeneity in both clinical features and
electrophysiological characteristics of PD patients with tremor. Based on this heterogeneity, PD patients with
tremor can be classified into two subtypes.
Key words
Parkinson’s disease /
tremor /
heterogeneity /
cluster analysis /
subtypes
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A Cluster Analysis Study on Clinical Features and Electrophysiological Heterogeneity in
Parkinson’s Disease Patients with Tremor[J]. Neural Injury and Functional Reconstruction. 0
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