OBJECTIVES: @entity73 ( @entity73 ) case-finding criteria have low specificity in general population studies. This study retrospectively identifies cases of @entity73 and determines baseline criteria giving the highest discriminability. The ability of these criteria to increase current case detection specificity is estimated. DESIGN: A population-based cohort was recruited from electoral rolls from three French cities. Clinical and environmental characteristics were evaluated at baseline and at 2- and 4-year follow-up. The clinical characteristics of incident cases of @entity303 were examined retrospectively. @entity1 : Eight thousand nine hundred nineteen @entity1 aged 65 years and older without @entity303 (60.8% @entity1 ) were included in this study. The mean age (SD) of the @entity1 was 74.2 (5.6) years for @entity1 and 74.4 (5.6) years for @entity1 . RESULTS: Three hundred twenty @entity1 (3.6%) were retrospectively classified as @entity73 at baseline. This @entity73 group had poorer performance on all cognitive tests compared with the rest of the cohort, and a subsample undergoing MRI were found to have more @entity62 . The group were also characterized by the presence of an @entity2204 genotype (odds ratio [OR]: 2.17, confidence interval [CI]: 1.44-3.29 for @entity1 ; OR: 2.27, CI: 1.59-3.24 for @entity1 ) and instrumental activities of daily living loss (OR: 1.72, CI: 1.01-3.0 for @entity1 ; OR: 1.49; CI: 0.97-2.3 for @entity1 ). @entity1 with @entity73 also had high depressive symptomatology (OR: 1.96; CI: 1.34-2.87), anticholinergic drug use (OR: 1.59; CI: 1.05-2.28), and low body mass index (OR: 1.54, CI: 1.05-2.28) and for @entity1 a history of @entity64 (OR: 2.17, CI: 1.16-4.05) and glycemia (OR: 1.72, CI: 1.13-2.71). Addition of these characteristics to @entity73 increases their specificity. CONCLUSIONS: This general population study using a retrospective method for classifying @entity1 with @entity73 identified gender-specific noncognitive clinical variables that may increase specificity.

Retrospective identification and characterization of mild XXXX from a prospective population cohort.

@entity1 :: ('9606', 'Species') :: ['participants', 'women', 'Women', 'PARTICIPANTS', 'persons', 'men'] @entity64 :: ('MESH:D020521', 'Disease') :: ['stroke'] @entity2204 :: ('348', 'Gene') :: ['ApoE   4'] @entity303 :: ('MESH:D003704', 'Disease') :: ['dementia'] @entity73 :: ('MESH:D003072', 'Disease') :: ['Mild cognitive impairment', 'conventional MCI definitions', 'MCI'] @entity62 :: ('MESH:D056784', 'Disease') :: ['white matter hyperintensities']
@entity73 :: (MESH:D003072,Disease) :: ['cognitive impairment']
