Open AccessNEUROPSYCHOLOGICAL TESTS AS PREDICTORS OF CONVERSION TO ALZHEIMER’S DISEASE IN BETA-AMYLOID POSITIVE INDIVIDUALS
Author(s) -
Brenda Gonçalves,
Isadora Ribeiro,
Thamires Naela Cardoso Magalhães,
Christian Luiz Baptista Gerbelli,
Luciana Pimentel- Silva,
Helena Passarelli Giroud Joaquim,
Leda Leme Talib,
Orestes Vicente Forlenza,
Marcio Balthazar
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5327/1980-5764.rpda007
Subject(s) - neuropsychology , clinical dementia rating , dementia , audiology , alzheimer's disease , psychology , neuropsychological test , amyloid beta , correlation , medicine , disease , cognition , clinical psychology , neuroscience , geometry , mathematics
Background: amnestic Mild Cognitive Impairment (aMCI) refers to a possibletransitional stage between healthy aging and dementia and has an increased chance of converting to Alzheimer’s disease (AD). Objectives: to assess whether neuropsychological tests can predict the conversion to AD in patients with aMCI and altered CSF amyloid peptide (βA+). Methods: 48 individuals underwent neuropsychological assessment (time 0 and time 1), being 18 healthy controls and 30 aMCI βA+, who performed a single CSF collection (time 0). All subjects with aMCI scored 0.5 in the Memory category of the Clinical Dementia Rating (CDR) test, and we considered the conversion to AD if the overall score changed from 0.5 to 1. We performed different additional univariate analyses with MANOVAs to differentiate between groups. Results : 8 subjects converted to AD (converters), and 22 remained stable (non-converters). The converters performed worse in the sub-item test Recognition of Rey Auditory Verbal Learning Test (RAVLT) compared to controls and non-converters (F = 14,58, p <0,001). Conclusions: the Recognition task of the RAVLT was able to differentiate aMCI βA+ individuals who converted to AD in our sample, which was not observed in the other investigated tests. We suggest additional studies with larger sample sizes and validation cohorts to contribute to our findings.