A model incorporating ultrasound to predict the probability of fast disease progression in amyotrophic lateral sclerosis
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 ( 1.22 (p = 0.026). A predictive model (scores 0-5) was...
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| Main Authors: | , , , , , , |
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| Format: | Article |
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Elsevier
2021
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/28573/ |
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| Summary: | 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 ( 1.22 (p = 0.026). A predictive model (scores 0-5) was built with excellent discrimination (area under curve: 0.915). Using a score of 3, the model demonstrated good sensitivity (81.3%) and specificity (91.0%) in differentiating fast from non-fast progressors. Conclusion: The current model is simple and can predict the probability of fast disease progression. Significance: This model has potential as a surrogate biomarker of ALS disease progression. (c) 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved. |
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