Literature DB >> 20544934

Monitoring disease progression using high-density motor unit number estimation in amyotrophic lateral sclerosis.

Johannes P van Dijk1, Helenius J Schelhaas, Ivo N Van Schaik, Henny M H A Janssen, Dick F Stegeman, Machiel J Zwarts.   

Abstract

In amyotrophic lateral sclerosis (ALS), progressive motor neuron loss causes severe weakness. Functional measurements tend to underestimate the underlying pathology because of collateral reinnervation. A more direct marker of lower motor neuron loss is of significant importance. We evaluated high-density motor unit number estimation (MUNE), as compared with the ALS Functional Rating Scale (ALSFRS) and maximal compound muscle action potential (CMAP) amplitude, for monitoring and classifying disease progression. MUNE showed good reproducibility (intraclass correlation coefficient = 0.86). MUNE showed a significantly greater decrease than the ALSFRS, the Medical Research Council (MRC) scale, and CMAP amplitude. Patients could be stratified into groups with rapidly or slowly progressive disease based on a decrement in MUNE at 4 months from baseline; ALSFRS score at 8 months was significantly lower in the rapidly progressive group. MUNE was sensitive to motor neuron loss early in the disease course when compared to other clinical measures. Stratification of patients based on a decrease in MUNE seems feasible.

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Year:  2010        PMID: 20544934     DOI: 10.1002/mus.21680

Source DB:  PubMed          Journal:  Muscle Nerve        ISSN: 0148-639X            Impact factor:   3.217


  8 in total

1.  Motor unit number estimation based on high-density surface electromyography decomposition.

Authors:  Yun Peng; Jinbao He; Bo Yao; Sheng Li; Ping Zhou; Yingchun Zhang
Journal:  Clin Neurophysiol       Date:  2016-06-25       Impact factor: 3.708

Review 2.  Neuromuscular Junction Dysfunction in Amyotrophic Lateral Sclerosis.

Authors:  Sagar Verma; Shiffali Khurana; Abhishek Vats; Bandana Sahu; Nirmal Kumar Ganguly; Pradip Chakraborti; Mandaville Gourie-Devi; Vibha Taneja
Journal:  Mol Neurobiol       Date:  2022-01-08       Impact factor: 5.590

3.  Differences in Dysfunction of Thenar and Hypothenar Motoneurons in Amyotrophic Lateral Sclerosis.

Authors:  Jia Fang; Liying Cui; Mingsheng Liu; Yuzhou Guan; Xiaoguang Li; Dawei Li; Bo Cui; Dongchao Shen; Qingyun Ding
Journal:  Front Hum Neurosci       Date:  2016-03-07       Impact factor: 3.169

4.  Tracking motor units longitudinally across experimental sessions with high-density surface electromyography.

Authors:  E Martinez-Valdes; F Negro; C M Laine; D Falla; F Mayer; D Farina
Journal:  J Physiol       Date:  2017-03-01       Impact factor: 5.182

5.  SPiQE: An automated analytical tool for detecting and characterising fasciculations in amyotrophic lateral sclerosis.

Authors:  J Bashford; A Wickham; R Iniesta; E Drakakis; M Boutelle; K Mills; C Shaw
Journal:  Clin Neurophysiol       Date:  2019-04-19       Impact factor: 3.708

Review 6.  Biomarkers in Motor Neuron Disease: A State of the Art Review.

Authors:  Nick S Verber; Stephanie R Shepheard; Matilde Sassani; Harry E McDonough; Sophie A Moore; James J P Alix; Iain D Wilkinson; Tom M Jenkins; Pamela J Shaw
Journal:  Front Neurol       Date:  2019-04-03       Impact factor: 4.003

7.  The rise and fall of fasciculations in amyotrophic lateral sclerosis.

Authors:  James A Bashford; Aidan Wickham; Raquel Iniesta; Emmanuel M Drakakis; Martyn G Boutelle; Kerry R Mills; Chris E Shaw
Journal:  Brain Commun       Date:  2020-02-20

8.  The evolving role of surface electromyography in amyotrophic lateral sclerosis: A systematic review.

Authors:  J Bashford; K Mills; C Shaw
Journal:  Clin Neurophysiol       Date:  2019-12-27       Impact factor: 3.708

  8 in total

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