About half of all patients with Lewy body dementias (LBD), including Parkinson’s disease dementia (PDD), have co-occurring Alzheimer’s disease (AD), which is associated with worse prognosis. Natural speech analysis can be an inexpensive and non-invasive screening tool for co-pathology, according to a recent study at the University of Pennsylvania and Ohio State University (Shellikeri S, et al., Parkinsonism Relat Disord. 2022 Sep;102:94-100. doi: 10.1016/j.parkreldis.2022.07.023).
This study analyzed lexical-semantic and acoustic features of picture descriptions using automated methods in 22 SYN + AD and 38 SYN-AD patients stratified using AD CSF biomarkers or autopsy diagnosis. Speech markers of AD co-pathology were identified using best subset regression, and their diagnostic discrimination was tested using receiver operating characteristic. ANCOVAs compared measures between groups covarying for demographic differences and cognitive disease severity. Tested were relations with CSF tau levels, and compared speech measures between PDD and DLB clinical disorders in the same cohort.
Age of acquisition of nouns (p = 0.034, |d| = 0.77) and lexical density (p = 0.0064, |d| = 0.72) were reduced in SYN + AD, and together showed excellent discrimination for SYN + AD vs. SYN-AD (95% sensitivity, 66% specificity; AUC = 0.82). Lower lexical density was related to higher CSF t-Tau levels (R = -0.41, p = 0.0021). Clinically-diagnosed PDD vs. DLB did not differ on any speech features.
It is clear, then, that AD co-pathology may result in a deviant natural speech profile in LBD characterized by specific lexical-semantic impairments, not detectable by clinical disorder diagnosis. This study demonstrates the potential of automated digital speech analytics as a screening tool for underlying AD co-pathology in LBD.
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