TY - JOUR
T1 - Tremor stability index
T2 - A new tool for differential diagnosis in tremor syndromes
AU - Di Biase, Lazzaro
AU - Brittain, John Stuart
AU - Shah, Syed Ahmar
AU - Pedrosa, David J.
AU - Cagnan, Hayriye
AU - Mathy, Alexandre
AU - Chen, Chiung Chu
AU - Martín-Rodríguez, Juan Francisco
AU - Mir, Pablo
AU - Timmerman, Lars
AU - Schwingenschuh, Petra
AU - Bhatia, Kailash
AU - Di Lazzaro, Vincenzo
AU - Brown, Peter
N1 - Publisher Copyright:
© The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - 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.
AB - 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.
KW - Parkinson's disease
KW - clinical neurophysiology
KW - movement disorders
KW - neurophysiology
KW - tremor
UR - http://www.scopus.com/inward/record.url?scp=85020942656&partnerID=8YFLogxK
U2 - 10.1093/brain/awx104
DO - 10.1093/brain/awx104
M3 - 文章
C2 - 28459950
AN - SCOPUS:85020942656
SN - 0006-8950
VL - 140
SP - 1977
EP - 1986
JO - Brain
JF - Brain
IS - 7
ER -