OBJECTIVES: Mild cognitive impairment (MCI) case-finding criteria have low specificity in general population studies. This study retrospectively identifies cases of MCI 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 dementia were examined retrospectively. PARTICIPANTS: Eight thousand nine hundred nineteen persons aged 65 years and older without dementia (60.8% women) were included in this study. The mean age (SD) of the participants was 74.2 (5.6) years for men and 74.4 (5.6) years for women. RESULTS: Three hundred twenty persons (3.6%) were retrospectively classified as MCI at baseline. This MCI 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 white matter hyperintensities. The group were also characterized by the presence of an ApoE ε4 genotype (odds ratio [OR]: 2.17, confidence interval [CI]: 1.44-3.29 for men; OR: 2.27, CI: 1.59-3.24 for women) and instrumental activities of daily living loss (OR: 1.72, CI: 1.01-3.0 for men; OR: 1.49; CI: 0.97-2.3 for women). Women with MCI 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 men a history of stroke (OR: 2.17, CI: 1.16-4.05) and glycemia (OR: 1.72, CI: 1.13-2.71). Addition of these characteristics to conventional MCI definitions increases their specificity. CONCLUSIONS: This general population study using a retrospective method for classifying persons with MCI identified gender-specific noncognitive clinical variables that may increase specificity.
OBJECTIVES: Mild cognitive impairment (MCI) case-finding criteria have low specificity in general population studies. This study retrospectively identifies cases of MCI 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 dementia were examined retrospectively. PARTICIPANTS: Eight thousand nine hundred nineteen persons aged 65 years and older without dementia (60.8% women) were included in this study. The mean age (SD) of the participants was 74.2 (5.6) years for men and 74.4 (5.6) years for women. RESULTS: Three hundred twenty persons (3.6%) were retrospectively classified as MCI at baseline. This MCI 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 white matter hyperintensities. The group were also characterized by the presence of an ApoE ε4 genotype (odds ratio [OR]: 2.17, confidence interval [CI]: 1.44-3.29 for men; OR: 2.27, CI: 1.59-3.24 for women) and instrumental activities of daily living loss (OR: 1.72, CI: 1.01-3.0 for men; OR: 1.49; CI: 0.97-2.3 for women). Women with MCI 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 men a history of stroke (OR: 2.17, CI: 1.16-4.05) and glycemia (OR: 1.72, CI: 1.13-2.71). Addition of these characteristics to conventional MCI definitions increases their specificity. CONCLUSIONS: This general population study using a retrospective method for classifying persons with MCI identified gender-specific noncognitive clinical variables that may increase specificity.
Authors: M E Gurol; M C Irizarry; E E Smith; S Raju; R Diaz-Arrastia; T Bottiglieri; J Rosand; J H Growdon; S M Greenberg Journal: Neurology Date: 2006-01-10 Impact factor: 9.910
Authors: B Winblad; K Palmer; M Kivipelto; V Jelic; L Fratiglioni; L-O Wahlund; A Nordberg; L Bäckman; M Albert; O Almkvist; H Arai; H Basun; K Blennow; M de Leon; C DeCarli; T Erkinjuntti; E Giacobini; C Graff; J Hardy; C Jack; A Jorm; K Ritchie; C van Duijn; P Visser; R C Petersen Journal: J Intern Med Date: 2004-09 Impact factor: 8.989
Authors: Oscar L Lopez; William J Jagust; Corinne Dulberg; James T Becker; Steven T DeKosky; Annette Fitzpatrick; John Breitner; Constantine Lyketsos; Beverly Jones; Claudia Kawas; Michelle Carlson; Lewis H Kuller Journal: Arch Neurol Date: 2003-10
Authors: Richard A McClure; Chad W Chumbley; Michelle L Reyzer; Kevin Wilson; Richard M Caprioli; John C Gore; Wellington Pham Journal: Neuroimage Clin Date: 2013-04-30 Impact factor: 4.881