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[P1–494]: COGNITIVE FRAILTY: A CONCEPTUAL REVIEW
Author(s) -
Facal David,
Pereiro Arturo X.,
Maseda Ana,
GandoyCrego Manuel,
JuncosRabadán Onésimo
Publication year - 2017
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2017.06.510
Subject(s) - psycinfo , dementia , cognition , medline , clinical psychology , psychology , cognitive decline , conceptualization , gerontology , cognitive reserve , medicine , cognitive impairment , psychiatry , disease , pathology , artificial intelligence , political science , computer science , law
Background:Novel approaches for the identification of “preclinical” or “pre-symptomatic” Alzheimer’s disease and other dementia are a key issue in the field, also in view of early biomarkers discovery. Recent studies showed that discourse alterations may be one of the earliest signs of the pathology, frequently measurable years before other cognitive deficits become apparent. Traditional neuropsychological tests fail to identify these changes. In contrast, the analysis of spoken language productions by Natural language processing (NLP) techniques can ecologically pinpoint language modifications in potential patients. This interdisciplinary study aimed at using NLP to identify early linguistic signs of cognitive decline in the elderly.Methods:We enrolled 96 subjects (age range 50-75): 48 healthy controls and 48 impaired subjects: 16 subjects with single domain amnestic Mild Cognitive Impairment (a-MCI), 16 with multiple domain MCI (md-MCI) and 16 with early Dementia (eD). Each subject underwent a brief neuropsychological screening composed by MMSE, MoCA, GPCog, CDT and verbal fluency (phonemic and semantic). The spontaneous speech during three tasks (complex picture; a typical working day; the last remembered dream) was then recorded, transcribed and annotated at various linguistic levels. A multidimensional parameter computation was performed by a quantitative analysis of spoken texts, computing 67 rhythmic, acoustic, lexical, morpho-syntactic and syntactic features. Results:Neuropsychological tests showed significant differences between controls and md-MCI, and between controls and eD subjects (p<0,01); MoCA, phonemic fluency and GPCog discriminated between controls and a-MCI (p<0,05) while MMSE, CDT and semantic fluency didn’t differentiate between the two groups (p>0,05). In the linguistic experiments, a number of features regarding lexical, acoustic and syntactic aspects were significant (p<0.05 using the Kolmogorov-Smirnov test) in differentiating between all the considered subject groups. Conclusions: Linguistic features of spontaneous discourse transcribed and analyzed by NLP techniques show significant differences between controls and pathological states, and seems to be a promising approach for the identification of preclinical stages of dementia. Long duration follow up studies are needed to confirm this assumption. Supported by OPLON, MIUR (L.C.).