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OBJECTIVE: The Evans Index (EI) is used for recognition of individuals with normal pressure hydrocephalus. However, recent studies suggest that the EI is not a reliable marker of this condition. Rather, the EI may be inversely correlated with cognitive performance, but information on this correlation is lacking. We aimed to assess the relationship between the EI and cognitive performance in community-dwelling older adults. PATIENTS AND METHODS: The study included 314 non-disabled, stroke-free, individuals aged ≥60 years enrolled in the Atahualpa Project undergoing brain MRI and MoCA testing. Using generalized linear models, adjusted for demographics, cardiovascular risk factors edentulism, depression, global cortical atrophy and white matter hyperintensities of vascular origin, we assessed the relationship between the EI and cognitive performance. Predictive margins of the MoCA score according to percentiles of the EI were also evaluated, after adjusting for variables reaching significance in univariate models. RESULTS: The mean EI was 0.248 ±â€¯0.022 and the mean MoCA score was 19.7 ±â€¯4.8 points. A fully-adjusted generalized linear model showed a significant inverse relationship between the EI and the MoCA score. Predictive models showed a decrease in the MoCA score according to increased levels of the EI (ß: -3.28; 95% C.I.: -6.09 to -0.47; p = 0.022). CONCLUSION: The independent effect of the EI on the MoCA score provides evidence of the utility of the EI to evaluate cognitive performance.

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AIMS: Frailty is a geriatric state of physical vulnerability that might be associated with cognitive decline in the absence of a concurrent neurodegenerative disorder. This assumes that neuroimaging studies are normal, but such examinations have rarely been considered for a frailty work-up. The present study identifies neuroimaging signatures in older adults interviewed with the Edmonton Frail Scale (EFS). METHODS: Community-dwellers aged ≥60 years enrolled in the Atahualpa Project were invited to undergo brain magnetic resonance imaging. Using generalized regression models, we evaluated the association between frailty and diffuse cortical and subcortical brain damage, after adjusting for relevant confounders. Multivariate models estimated the interaction of age in the association between frailty and these neuroimaging signatures. RESULTS: Out of 298 participants (mean age 70 ± 8 years, 57% women), 151 (51%) had moderate-to-severe cortical atrophy and 74 (25%) had moderate-to-severe white matter hyperintensities of presumed vascular origin. Mean EFS scores were 5 ± 3 points, with 140 (47%) individuals classified as robust, 65 (22%) as pre-frail and 93 (31%) as frail. Multivariate models showed a significant association between cortical atrophy with the continuous (P = 0.002) and the categorized (P = 0.008) EFS score. The relationship between white matter hyperintensities and the EFS was marginal. According to interaction models, prefrail or frail individuals aged ≥67 years presented more prominent neuroimaging signatures of diffuse cortical or subcortical damage than their robust counterparts. CONCLUSIONS: Neuroimaging signatures of frailty are mainly related to age. This reinforces the importance of early frailty detection to reduce its catastrophic consequences. Geriatr Gerontol Int 2017; 17: 270-276.

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PURPOSE: To assess the effect of age in the association between poor sleep quality and frailty status. DESIGN AND SETTING: Population-based, cross-sectional study conducted in Atahualpa, a rural village located in coastal Ecuador. METHODS: Out of 351 Atahualpa residents aged ≥ 60 years, 311 (89%) were interviewed with the Pittsburgh Sleep Quality Index (PSQI) and the Edmonton Frail Scale (EFS). The independent association between PSQI and EFS scores was evaluated by the use of a generalized linear model adjusted for relevant confounders. A contour plot with Shepard interpolation was constructed to assess the effect of age in this association. RESULTS: Mean score in the PSQI was 5 ± 2 points, with 34% individuals classified as poor sleepers. Mean score in the EFS was 5 ± 3 points, with 46% individuals classified as robust, 23% as prefrail, and 31% as frail. In the fully adjusted model, higher scores in the PSQI were significantly associated with higher scores in the EFS (ß 0.23; 95% CI 0.11-0.35; P < .0001). Several clusters depicted the strong effect of age in the association between PSQI and EFS scores. Older individuals were more likely to have high scores in the EFS and the PSQI, and younger individuals had low EFS scores and were good sleepers. Clusters of younger individuals who were poor sleepers and had high EFS scores accounted for the independent association between PSQI and EFS scores. CONCLUSIONS: This study shows the strong effect of age in the association between poor sleep quality and frailty status.

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