Study of an integrated model for the identification of patients with Alzheimer's type dementia
Abstract
Introduction. Alzheimer's disease dementia represents a progressive cognitive impairment resulting from a brain pathology that impacts autonomy and functionality. Therefore, this study aimed to develop a model integrating cerebral, autonomic, and cognitive indicators to contribute to the detection of Alzheimer's cases. Methodology. This observational study consisted of 14 older adults (controls) and 14 individuals diagnosed with dementia (Alzheimer's disease), selected and examined intentionally. They were assessed using the Montreal Cognitive Assessment, magnetic resonance imaging (fractal dimension of axial and coronal slices), and cardiac reactivity to an orthostatic tolerance test. Results. Differences were identified in cognitive, cerebral, and autonomic indicators between the two groups (t-test). A binomial logistic regression analysis revealed that the Montreal Cognitive Assessment and the minimum heart rate constituted a model that explained the diagnosis in 75.55% of cases (adjusted R²). The fractal dimension of the brain in axial (r =-0.38, p = 0.046) and coronal (r = -0.42, p = 0.026) slices correlated significantly with the Montreal Cognitive Assessment. Discussion. These results were compared with studies addressing the potential of integrating cognitive and autonomic measures in the diagnosis of dementia. Additionally, the usefulness of the fractal dimension of the brain as an indicator derived from magnetic resonance imaging was discussed. Conclusions. The integration of indicators (cognitive and autonomic) explained the diagnosis to a greater extent than the isolated variables. Furthermore, the potential use of the fractal dimension of the brain was demonstrated, as it revealed an association with cognitive functioning as represented by the Montreal Cognitive Assessment.
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