Journal
LIFE-BASEL
Volume 12, Issue 10, Pages -Publisher
MDPI
DOI: 10.3390/life12101506
Keywords
motor neuron diseases; differential diagnosis; multimodal characterization; amyotrophic lateral sclerosis
Categories
Funding
- Italian Ministry of Health [NET-2018-12366666]
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A multimodal characterization approach embedding clinical, cognitive/behavioral, genetic, and neurophysiological data can improve the differentiation of pUMN and pLMN from ALS at the time of diagnosis. Detailed clinical and neurophysiological examinations can significantly improve the differentiation of motor neuron diseases.
Pure/predominant upper motor neuron (pUMN) and lower motor neuron (pLMN) diseases have significantly better prognosis compared to amyotrophic lateral sclerosis (ALS), but their early differentiation is often challenging. We therefore tested whether a multimodal characterization approach embedding clinical, cognitive/behavioral, genetic, and neurophysiological data may improve the differentiation of pUMN and pLMN from ALS already by the time of diagnosis. Dunn's and chi-squared tests were used to compare data from 41 ALS, 34 pLMN, and 19 pUMN cases with diagnoses confirmed throughout a 2-year observation period. Area under the curve (AUC) analyses were implemented to identify the finest tools for phenotypes discrimination. Relative to ALS, pLMN showed greater lower limbs weakness, lower UMN burden, and progression rate (p < 0.001-0.04). PUMN showed a greater frequency of lower limbs onset, higher UMN burden, lower ALSFRS-r and MRC progression rates (p < 0.001-0.03), and greater ulnar compound muscle action potential (CMAP) amplitude and tibial central motor conduction time (CMCT) (p = 0.05-0.03). The UMN progression rate was the finest measure to identify pLMN cases (AUC = 90%), while the MRC progression rate was the finest tool to identify pUMN (AUC = 82%). Detailed clinical and neurophysiological examinations may significantly improve MNDs differentiation, facilitating prognosis estimation and ameliorating stratification strategies for clinical trials enrollment.
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