One hundred and seven elderly subjects with cognitive impairment (91 memory clinic patients with mild cognitive impairment [MCI] and 16 with dementia of AD type) and 55 cognitively healthy volunteers were included in this study.
In a follow-up analysis using an independent data set, we demonstrate a protective effect of this variant against risk of conversion to MCI or AD (p = 0.038) and against cognitive decline in individuals who develop dementia (p = 3.41 × 10<sup>-15</sup> ).
Fine-Gray subdistribution modeling was used to examine the risk of progression from CN to MCI/dementia due to Aβ+, APOEɛ4 carriage, and their interaction in the Australian Imaging, Biomarkers and Lifestyle (AIBL) flagship study of aging CN cohort (n = 599) over 8 years.
It is expected that future versions of cognitive screening tests, modified using a PBA, will highlight the benefits of attending to qualitative features of test performance when trying to identify subtle features suggestive of MCI and/or dementia.
We analyzed 94 patients with MCI-AD followed until conversion to dementia and 39 patients with MCI who had brain amyloidosis (AMY+ MCI), all with available baseline <sup>18</sup>F-fluorodeoxyglucose positron emission tomography (FDG-PET) results.
<b>Conclusions:</b> Linguistic features of spontaneous speech transcribed and analyzed by NLP techniques show significant differences between controls and pathological states (not only eD but also MCI) and seems to be a promising approach for the identification of preclinical stages of dementia.
Prevalence of amyloid positivity in the Olmsted County population without dementia and risk of progression from no cognitive impairment (ie, normal cognition for age) to incident amnestic MCI (aMCI) and from MCI or aMCI to incident AD dementia.
Seventy-seven individuals with pre-MCI and 180 CN elders were recruited from the pool of individuals registered at the National Research Center for Dementia in Gwangju, Korea.
The cross-sectional cohort included control subjects without dementia and patients with AD, and the longitudinal cohort included patients with MCI and patients with AD followed over a 2-year period.
A multivariate model based on the Disease State Index classifier incorporated the available baseline tests to predict progression to MCI or dementia over time.
Simultaneous multi-category classification analyses showed that the volume under the ROC surface (VUS) was 0.57 and that the derived optimal cut-off points were 2 and 8 for controls, MCI, and dementia.
Cognitive decline (defined as the incidence of either Parkinson's disease mild cognitive impairment [PD-MCI] or dementia [PDD], diagnosed according to published criteria and blinded to genotype) was studied as the primary outcome.
Age (hazard ratio (HR) 1.05 per year, 95% CI: 1.01-1.08, p = 0.007), presence of MCI status (HR 3.40, 95% CI: 1.97-6.92, p < 0.001), MTA (HR 1.71 per point, 95% CI: 1.26-2.32, p = 0.001), and SVD score (HR 1.23 per point, 95% CI: 1.20-1.48, p = 0.030) at baseline were independent predictors for dementia conversion in these patients.
The primary outcome was cognitive status, classified as normal, mild cognitive impairment [MCI], and dementia on the basis of standardized cognitive tests (delayed word recall, word fluency, and digit symbol substitution).
Further analysis of the diagnostic subgroups suggested different variables were more strongly associated with IADL from group to group (apathy and depression for normal participants, apathy for MCI participants and for participants with dementia due to AD, but not for those with non-AD dementia).