805 research outputs found
Determinants of cerebral white matter lesions: A longitudinal population based MRI study
W hite matter lesions are frequently found on cerebral magnetic resonance
imaging scans of elderly non-demented and demented people.
l-4 The pathogenesis of white matter lesions is largely unknown. However
age and high diastolic and systolic blood pressure levels and indicators
of atherosclerosis have consistently been reported as risk factors for
white matter lesions, regardless of their location.2-s Many other, especially
vascular, risk factors have been associated with white matter lesions, but
these relations were mostly not consistent throughout studies.
There is growing evidence that white matter lesions play an important
role in the development of cognitive decline and dementia.4 .6 -8 The
white matter can be distinguished into two separate anatomical regions,
namely the peri ventricular white matter (a strip of white matter adjacent
to the lateral ventricles) and the subcortical white matter (the white mattcr
just underneath the gray matter). Only a few studies have distinguished
between these two locations and have reported on their determinants
separately.9,10 Yet it may be that different risk factors underlie white
matter lesions at different locations, or that lesions in different locations
may have different cognitive consequences
White Matter Microstructural Damage on Diffusion Tensor Imaging in Cerebral Small Vessel Disease
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Apathy, but not depression, predicts all-cause dementia in cerebral small vessel disease
Objective: To determine whether apathy or depression predicts all-cause dementia in small vessel disease (SVD) patients. Methods: Analyses used two prospective cohort studies of SVD: St. George’s Cognition and Neuroimaging in Stroke (SCANS; n=121) and Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC; n=352). Multivariate Cox regressions were used to predict dementia using baseline apathy and depression scores in both datasets. Change in apathy and depression was used to predict dementia in a subset of 104 participants with longitudinal data from SCANS. All models were controlled for age, education and cognitive function. Results: Baseline apathy scores predicted dementia in SCANS (HR 1.49, 95% CI 1.05 to 2.11, p=0.024) and RUN DMC (HR 1.05, 95% CI 1.01 to 1.09, p=0.007). Increasing apathy was associated with dementia in SCANS (HR 1.53, 95% CI 1.08 to 2.17, p=0.017). In contrast, baseline depression and change in depression did not predict dementia in either dataset. Including apathy in predictive models of dementia improved model fit. Conclusions: Apathy, but not depression, may be a prodromal symptom of dementia in SVD, and may be useful in identifying at-risk individuals
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