Dataset Information

Motor and Non-motor Features: Differences between Patients with Isolated Essential Tremor and Patients with Both Essential Tremor and Parkinson's Disease.

ABSTRACT: BACKGROUND: Patients with essential tremor (ET) who develop Parkinson's disease (PD) (i.e., ET→PD) may differ with respect to motor features (MFs) and non-motor features (NMFs) from patients with isolated ET. Few studies have assessed this issue. METHODS: In this retrospective chart review, we analyzed data on MFs and NMFs of 175 patients, including 54 ET→PD and 121 ET, actively followed in the Athens University 1st Neurology Department. RESULTS: Significantly more ET→PD than ET patients reported asymmetric tremor at ET onset (68.5% vs. 14.9%, p<0.001). Significantly more ET than ET→PD patients had head tremor (43.5% vs. 13.2%, p<0.001) and cerebellar signs (41.3% vs. 9.3%, p<0.001). More ET than ET→PD patients reported hearing impairment (65.3% vs. 28.3%, p<0.001) and restless legs syndrome (34.8% vs. 3.7%, p<0.001). Conversely, a larger proportion of ET→PD than ET patients reported rapid eye movement behavior disorder (51.9% vs. 10.0%, p<0.001), constipation (67.9% vs. 36.4%, p<0.001), and olfactory dysfunction (83.3% vs. 36.4%, p<0.001). DISCUSSION: The subset of ET→PD patients may have distinct MFs and NMFs that should be assessed further for the possible predictive value for the emergence of PD.

SUBMITTER: Ghika A

PROVIDER: S-EPMC4548968 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Publications

Motor and Non-motor Features: Differences between Patients with Isolated Essential Tremor and Patients with Both Essential Tremor and Parkinson's Disease.

Ghika Apostolia A Kyrozis Andreas A Potagas Constantinos C Louis Elan D ED

Tremor and other hyperkinetic movements (New York, N.Y.) 20150814

<h4>Background</h4>Patients with essential tremor (ET) who develop Parkinson's disease (PD) (i.e., ET→PD) may differ with respect to motor features (MFs) and non-motor features (NMFs) from patients with isolated ET. Few studies have assessed this issue.<h4>Methods</h4>In this retrospective chart review, we analyzed data on MFs and NMFs of 175 patients, including 54 ET→PD and 121 ET, actively followed in the Athens University 1st Neurology Department.<h4>Results</h4>Significantly more ET→PD than ...[more]

PMID: 26336614

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Project description:Introduction: Parkinson's disease (PD) is a progressive movement disorder characterized by heterogenous motor dysfunction with fluctuations in severity. Objective, short-timescale characterization of this dysfunction is necessary as therapies become increasingly adaptive. Objectives: This study aims to characterize a novel, naturalistic, and goal-directed tablet-based task and complementary analysis protocol designed to characterize the motor features of PD. Methods: A total of 26 patients with PD and without deep brain stimulation (DBS), 20 control subjects, and eight patients with PD and with DBS completed the task. Eight metrics, each designed to capture an aspect of motor dysfunction in PD, were calculated from 1-second, non-overlapping epochs of the raw positional and pressure data captured during task completion. These metrics were used to generate a classifier using a support vector machine (SVM) model to produce a unifying, scalar "motor error score" (MES). The data generated from these patients with PD were compared to same-day standard clinical assessments. Additionally, these data were compared to analogous data generated from a separate group of 12 patients with essential tremor (ET) to assess the task's specificity for different movement disorders. Finally, an SVM model was generated for each of the eight patients with PD and with DBS to differentiate between their motor dysfunction in the "DBS On" and "DBS Off" stimulation states. Results: The eight metrics calculated from the raw positional and force data captured during task completion were non-redundant. MES generated by the SVM analysis protocol showed a strong correlation with MDS-UPDRS-III scores assigned by movement disorder specialists. Analysis of the relative contributions of each of the eight metrics showed a significant difference between the motor dysfunction of PD and ET. Much of this difference was attributable to the homogenous, tremor-dominant phenotype of ET motor dysfunction. Finally, in individual patients with PD with DBS, task performance and subsequent SVM classification effectively differentiated between the "DBS On" and "DBS Off" stimulation states. Conclusion: This tablet-based task and analysis protocol correlated strongly with expert clinical assessments of PD motor dysfunction. Additionally, the task showed specificity for PD when compared to ET, another common movement disorder. This specificity was driven by the relative heterogeneity of motor dysfunction of PD compared to ET. Finally, the task was able to distinguish between the "DBS On" and "DBS Off" states within single patients with PD. This task provides temporally-precise and specific information about motor dysfunction in at least two movement disorders that could feasibly correlate to neural activity.

Dataset Information

Motor and Non-motor Features: Differences between Patients with Isolated Essential Tremor and Patients with Both Essential Tremor and Parkinson's Disease.

Publications

Motor and Non-motor Features: Differences between Patients with Isolated Essential Tremor and Patients with Both Essential Tremor and Parkinson's Disease.

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