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A new neurophysiological tool for differential diagnosis in tremor syndromes: The Tremor Stability Index

L. di Biase, J.-S. Brittain, S.A. Shah, D.J. Pedrosa, H. Cagnan, A. Mathy, C.C. Chen, L. Timmerman, P. Schwingenschuh, K. Bhatia, V. Di Lazzaro, P. Brown (Oxford, United Kingdom)

Meeting: 2017 International Congress

Abstract Number: 748

Keywords: Essential tremor(ET), Neurophysiology, Resting tremors

Session Information

Date: Tuesday, June 6, 2017

Session Title: Tremor

Session Time: 1:45pm-3:15pm

Location: Exhibit Hall C

Objective: We present a robust new neurophysiological measure, the Tremor Stability Index (TSI), which can discriminate Parkinson’s disease tremor (PD) and Essential tremor (ET) with high diagnostic accuracy.

Background: Misdiagnosis among tremor syndromes is common, and can impact on both clinical care and research. To date no validated neurophysiological technique is available that has proven to have good classification performance, and the diagnostic gold standard is the clinical evaluation made by a movement disorders expert.

Methods: The TSI is derived from kinematic measurements of tremulous activity. It was assessed in a test cohort comprising 16 rest tremor recordings in tremor-dominant PD and 20 postural tremor recordings in ET, and validated on a second, independent cohort comprising a further 50 tremulous PD and ET recordings. Clinical diagnosis was used as gold standard. 100 seconds of tremor recording were selected for analysis in each patient. The classification accuracy of the new index was assessed by binary logistic regression, and by receiver operating characteristic (ROC) analysis. The diagnostic performance was examined by calculating the sensitivity, specificity, accuracy, likelihood ratio positive, likelihood ratio negative, area under the ROC curve, and by cross-validation.

Results: TSI with a cutoff of 1·05 gave good classification performance for PD tremor and ET, in both test and validation datasets. TSI sensitivity, specificity and accuracy ranged between 88-95%, 88-95% and 90-92%, respectively. ROC analysis showed an AUC of 0·916 (95% C.I. 0·797 – 1·000) for the Test dataset and a value of 0·905 (95% C.I. 0·812 – 0·998) for the Validation dataset. Classification accuracy proved independent of recording device and posture.

Conclusions: In conclusion, the TSI can aid in the differential diagnosis of the two most common tremor types, presents a high diagnostic accuracy, can be derived from short, cheap, widely available and non-invasive tremor recordings, and is independent of operator or postural context in its interpretation.

To cite this abstract in AMA style:

L. di Biase, J.-S. Brittain, S.A. Shah, D.J. Pedrosa, H. Cagnan, A. Mathy, C.C. Chen, L. Timmerman, P. Schwingenschuh, K. Bhatia, V. Di Lazzaro, P. Brown. A new neurophysiological tool for differential diagnosis in tremor syndromes: The Tremor Stability Index [abstract]. Mov Disord. 2017; 32 (suppl 2). https://www.mdsabstracts.org/abstract/a-new-neurophysiological-tool-for-differential-diagnosis-in-tremor-syndromes-the-tremor-stability-index/. Accessed May 21, 2025.
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