Spoken Language Alterations can Predict Phenoconversion in Isolated Rapid Eye Movement Sleep Behavior Disorder:
Martin Šubert1, Michal Novotný1, Tereza Tykalová1
1Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Annals of Neurology
|November 24, 2023
Summary
Speech and language impairments predict neurodegenerative disease development in individuals with idiopathic REM sleep behavior disorder. Automated analysis of language patterns can identify patients at higher risk for synucleinopathy subtypes.
Area of Science:
- Neurology
- Linguistics
- Sleep Medicine
Background:
- Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage for synucleinopathies.
- Identifying early markers for phenoconversion is crucial for timely intervention.
- Speech and language changes may indicate underlying neurodegeneration.
Purpose of the Study:
- To investigate the association between speech and language impairments and the risk of developing parkinsonism or dementia in patients with iRBD.
- To assess the utility of automated language analysis in predicting phenoconversion.
Main Methods:
- A multicenter cohort of 180 iRBD patients underwent baseline speech assessment.
- Automated speech recognition and natural language processing analyzed linguistic and acoustic features of narrative speech.
- Cox proportional hazard models evaluated the predictive value of language patterns for phenoconversion over 5 years.
Main Results:
- Of 156 patients with follow-up, 42 (26.9%) converted to neurodegenerative disease.
- Higher severity of linguistic and acoustic abnormalities predicted conversion (HR=2.35 and HR=1.92, respectively).
- Converters showed reduced content richness, slower articulation, and prolonged pauses.
Conclusions:
- Automated language analysis can predict phenoconversion from iRBD to synucleinopathy subtypes.
- Language deterioration patterns may serve as early biomarkers for neurodegeneration.
- This approach can aid in stratifying patients for clinical trials.
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