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...

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Autores: Di Biase, Lazzaro, Brittain, John-Stuart, Shah, Syed Ahmar, Pedrosa, David J., Cagnan, Hayriye, Mathy, Alexandre, Chen, Chiung Chu, Martín Rodríguez, Juan Francisco, Mir Rivera, Pablo, Timmerman, Lars, Schwingenschuh, Petra, Bhatia, Kailash, Di Lazzaro, Vincenzo, Brown, Peter
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:España
Recursos:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/154752
Acesso em linha:https://hdl.handle.net/11441/154752
https://doi.org/10.1093/brain/awx104
Access Level:acceso abierto
Palavra-chave:Tremor
Parkinson’s disease
Clinical neurophysiology
Movement disorders
Neurophysiology
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spelling Tremor stability index: a new tool for differential diagnosis in tremor syndromesDi Biase, LazzaroBrittain, John-StuartShah, Syed AhmarPedrosa, David J.Cagnan, HayriyeMathy, AlexandreChen, Chiung ChuMartín Rodríguez, Juan FranciscoMir Rivera, PabloTimmerman, LarsSchwingenschuh, PetraBhatia, KailashDi Lazzaro, VincenzoBrown, PeterTremorParkinson’s diseaseClinical neurophysiologyMovement disordersNeurophysiologyMisdiagnosis 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 55 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.Rosetrees TrustNational Institute of Health Research Oxford Biomedical Research CentreDeutsche Forschungsgemeinschaft PE2291/1-1Medical Research Council MR/M014762/1Medical Research Council MC_UU_12024/1Medical Research Council MR/N003446/1Oxford University PressInstituto de Biomedicina de Sevilla (IBIS)MedicinaMedical Research CouncilRosetrees TrustNational Institute of Health Research Oxford Biomedical Research CentreDeutsche Forschungsgemeinschaft / German Research Foundation (DFG)Medical Research2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/154752https://doi.org/10.1093/brain/awx104reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésBrain, 140 (7), 1977-1986.PE2291/1-1MR/M014762/1MR/N003446/1MC_UU_12024/1https://doi.org/10.1093/brain/awx104info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1547522026-06-17T12:51:07Z
dc.title.none.fl_str_mv 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
spellingShingle Tremor stability index: a new tool for differential diagnosis in tremor syndromes
Di Biase, Lazzaro
Tremor
Parkinson’s disease
Clinical neurophysiology
Movement disorders
Neurophysiology
title_short 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_sort Tremor stability index: a new tool for differential diagnosis in tremor syndromes
dc.creator.none.fl_str_mv Di Biase, Lazzaro
Brittain, John-Stuart
Shah, Syed Ahmar
Pedrosa, David J.
Cagnan, Hayriye
Mathy, Alexandre
Chen, Chiung Chu
Martín Rodríguez, Juan Francisco
Mir Rivera, Pablo
Timmerman, Lars
Schwingenschuh, Petra
Bhatia, Kailash
Di Lazzaro, Vincenzo
Brown, Peter
author Di Biase, Lazzaro
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 Rivera, Pablo
Timmerman, Lars
Schwingenschuh, Petra
Bhatia, Kailash
Di Lazzaro, Vincenzo
Brown, Peter
author_role author
author2 Brittain, John-Stuart
Shah, Syed Ahmar
Pedrosa, David J.
Cagnan, Hayriye
Mathy, Alexandre
Chen, Chiung Chu
Martín Rodríguez, Juan Francisco
Mir Rivera, Pablo
Timmerman, Lars
Schwingenschuh, Petra
Bhatia, Kailash
Di Lazzaro, Vincenzo
Brown, Peter
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Instituto de Biomedicina de Sevilla (IBIS)
Medicina
Medical Research Council
Rosetrees Trust
National Institute of Health Research Oxford Biomedical Research Centre
Deutsche Forschungsgemeinschaft / German Research Foundation (DFG)
Medical Research
dc.subject.none.fl_str_mv Tremor
Parkinson’s disease
Clinical neurophysiology
Movement disorders
Neurophysiology
topic Tremor
Parkinson’s disease
Clinical neurophysiology
Movement disorders
Neurophysiology
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 55 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.
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/154752
https://doi.org/10.1093/brain/awx104
url https://hdl.handle.net/11441/154752
https://doi.org/10.1093/brain/awx104
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Brain, 140 (7), 1977-1986.
PE2291/1-1
MR/M014762/1
MR/N003446/1
MC_UU_12024/1
https://doi.org/10.1093/brain/awx104
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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