The diagnostic value of tremor analysis for defining the Parkinson's disease subtype

Abstract

Objective: To find more objective evidence and support for clinical classification of Parkinson's disease by means of tremor analysis in patients with early confirmed Parkinson's disease. Methods: A cross-sectional study was conducted to collect 65 patients with early Parkinson's disease treated in the Third Hospital of Peking University from January 2015 to December 2016. Unified Parkinson's Disease Rating Scale (UPDRS), Hoehn-Yahr scale (H-Y scale), Mini-mental state examination (MMSE), Hamilton depression scale (HAMD) were recorded in all patients. According to the ratio of UPDRS rigidity score to tremor score, the patients were divided into tremor dominant (TD), postural instability/gait difficulty (PIGD) and mixed types. All patients were examined by tremor analysis and the results were analyzed and compared. Results: Among the 65 patients, the mean age of onset was (63±10) years, the course of disease was (14±8) months. Twenty-one patients were classified to TD group, 28 patients were classified to PIGD type, and 16 patients with mixed type. There was no significant difference in frequency and amplitude of tremor between the three groups (P>0.05), but the proportion of alternating contraction and harmonic resonance of active and antagonistic muscles in TD group was significantly higher (P<0.05). Twenty patients (71.4%) in TD group showed typical Parkinson's disease manifestations in tremor analysis. Only four patients (14.3%) in PIGD group showed the typical manifestations. More patients in PIGD group showed no clear main peak of tremor at rest. Some patients showed 6-8 Hz/sec peak frequency in posture position and simultaneous contraction of the active and antagonist muscles. These two manifestations occured simultaneously in mixed type patients, including 10 cases (62.5%) with typical Parkinson's disease manifestations. Conclusion: As an objective electrophysiological method to evaluate tremor type, tremor analysis can be used as an important assistant method for clinical classification of Parkinson's disease. It can provide information of the pathway of pathological loss in different types and give important hints in prognosis and treatment.