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Tremor stability index: a new tool for differential diagnosis in tremor syndromes
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 dis...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5493195/ https://www.ncbi.nlm.nih.gov/pubmed/28459950 http://dx.doi.org/10.1093/brain/awx104 |
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author | di Biase, Lazzaro Brittain, John-Stuart Shah, Syed Ahmar Pedrosa, David J. Cagnan, Hayriye Mathy, Alexandre Chen, Chiung Chu Martín-Rodríguez, Juan Francisco Mir, Pablo Timmerman, Lars Schwingenschuh, Petra Bhatia, Kailash Di Lazzaro, Vincenzo Brown, Peter |
author_facet | di Biase, Lazzaro Brittain, John-Stuart Shah, Syed Ahmar Pedrosa, David J. Cagnan, Hayriye Mathy, Alexandre Chen, Chiung Chu Martín-Rodríguez, Juan Francisco Mir, Pablo Timmerman, Lars Schwingenschuh, Petra Bhatia, Kailash Di Lazzaro, Vincenzo Brown, Peter |
author_sort | di Biase, Lazzaro |
collection | PubMed |
description | 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. We present a robust new neurophysiological measure, the tremor stability index, which can discriminate Parkinson’s disease tremor and essential tremor with high diagnostic accuracy. The tremor stability index is derived from kinematic measurements of tremulous activity. It was assessed in a test cohort comprising 16 rest tremor recordings in tremor-dominant Parkinson’s disease and 20 postural tremor recordings in essential tremor, and validated on a second, independent cohort comprising a further 50 tremulous Parkinson’s disease and essential tremor recordings. Clinical diagnosis was used as gold standard. One hundred 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 analysis. The diagnostic performance was examined by calculating the sensitivity, specificity, accuracy, likelihood ratio positive, likelihood ratio negative, area under the receiver operating characteristic curve, and by cross-validation. Tremor stability index with a cut-off of 1.05 gave good classification performance for Parkinson’s disease tremor and essential tremor, in both test and validation datasets. Tremor stability index maximum sensitivity, specificity and accuracy were 95%, 95% and 92%, respectively. Receiver operating characteristic analysis showed an area under the curve of 0.916 (95% confidence interval 0.797–1.000) for the test dataset and a value of 0.855 (95% confidence interval 0.754–0.957) for the validation dataset. Classification accuracy proved independent of recording device and posture. The tremor stability index can aid in the differential diagnosis of the two most common tremor types. It has 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. |
format | Online Article Text |
id | pubmed-5493195 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
record_format | MEDLINE/PubMed |
spelling | pubmed-54931952017-07-01 Tremor stability index: a new tool for differential diagnosis in tremor syndromes di Biase, Lazzaro Brittain, John-Stuart Shah, Syed Ahmar Pedrosa, David J. Cagnan, Hayriye Mathy, Alexandre Chen, Chiung Chu Martín-Rodríguez, Juan Francisco Mir, Pablo Timmerman, Lars Schwingenschuh, Petra Bhatia, Kailash Di Lazzaro, Vincenzo Brown, Peter Brain Article 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. We present a robust new neurophysiological measure, the tremor stability index, which can discriminate Parkinson’s disease tremor and essential tremor with high diagnostic accuracy. The tremor stability index is derived from kinematic measurements of tremulous activity. It was assessed in a test cohort comprising 16 rest tremor recordings in tremor-dominant Parkinson’s disease and 20 postural tremor recordings in essential tremor, and validated on a second, independent cohort comprising a further 50 tremulous Parkinson’s disease and essential tremor recordings. Clinical diagnosis was used as gold standard. One hundred 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 analysis. The diagnostic performance was examined by calculating the sensitivity, specificity, accuracy, likelihood ratio positive, likelihood ratio negative, area under the receiver operating characteristic curve, and by cross-validation. Tremor stability index with a cut-off of 1.05 gave good classification performance for Parkinson’s disease tremor and essential tremor, in both test and validation datasets. Tremor stability index maximum sensitivity, specificity and accuracy were 95%, 95% and 92%, respectively. Receiver operating characteristic analysis showed an area under the curve of 0.916 (95% confidence interval 0.797–1.000) for the test dataset and a value of 0.855 (95% confidence interval 0.754–0.957) for the validation dataset. Classification accuracy proved independent of recording device and posture. The tremor stability index can aid in the differential diagnosis of the two most common tremor types. It has 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. 2017-07-01 /pmc/articles/PMC5493195/ /pubmed/28459950 http://dx.doi.org/10.1093/brain/awx104 Text en http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article di Biase, Lazzaro Brittain, John-Stuart Shah, Syed Ahmar Pedrosa, David J. Cagnan, Hayriye Mathy, Alexandre Chen, Chiung Chu Martín-Rodríguez, Juan Francisco Mir, Pablo Timmerman, Lars Schwingenschuh, Petra Bhatia, Kailash Di Lazzaro, Vincenzo Brown, Peter Tremor stability index: a new tool for differential diagnosis in tremor syndromes |
title | Tremor stability index: a new tool for differential diagnosis in tremor syndromes |
title_full | Tremor stability index: a new tool for differential diagnosis in tremor syndromes |
title_fullStr | Tremor stability index: a new tool for differential diagnosis in tremor syndromes |
title_full_unstemmed | Tremor stability index: a new tool for differential diagnosis in tremor syndromes |
title_short | Tremor stability index: a new tool for differential diagnosis in tremor syndromes |
title_sort | tremor stability index: a new tool for differential diagnosis in tremor syndromes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5493195/ https://www.ncbi.nlm.nih.gov/pubmed/28459950 http://dx.doi.org/10.1093/brain/awx104 |
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