A model incorporating ultrasound to predict the probability of fast disease progression in amyotrophic lateral sclerosis

Toh TH 1 , Abdul-Aziz NA 1 , Yahya MA 1 , Goh KJ 1 , Loh EC 2 , Capelle DP 2 Show all authors , Shahrizaila N 3

Affiliations 

  • 1 Neurology Unit, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
  • 2 Palliative Care Unit, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
  • 3 Neurology Unit, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. Electronic address: nortina@um.edu.my
Clin Neurophysiol, 2021 10;132(10):2722-2728.
PMID: 34312065 DOI: 10.1016/j.clinph.2021.05.034

Abstract

OBJECTIVE: We aimed to develop a model to predict amyotrophic lateral sclerosis (ALS) disease progression based on clinical and neuromuscular ultrasound (NMUS) parameters.

METHODS: ALS patients were prospectively recruited. Muscle fasciculation (≥2 over 30-seconds, examined in biceps brachii-brachialis (BB), brachioradialis, tibialis anterior and vastus medialis) and nerve cross-sectional area (CSA) (median, ulnar, tibial, fibular nerve) were evaluated through NMUS. Ultrasound parameters were correlated with clinical data, including revised ALS Functional Rating Scale (ALSFRS-R) progression at one year. A predictive model was constructed to differentiate fast progressors (ALSFRS-R decline ≥ 1/month) from non-fast progressors.

RESULTS: 40 ALS patients were recruited. Three parameters emerged as strong predictors of fast progressors: (i) ALSFRS-R slope at time of NMUS (p = 0.041), (ii) BB fasciculation count (p = 0.027) and (iii) proximal to distal median nerve CSA ratio 

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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