13 research outputs found

    Interactions between Neuropsychiatric Symptoms and Alzheimer’s Disease Neuroimaging Biomarkers in Predicting Longitudinal Cognitive Decline

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    OBJECTIVE: To examine interactions between Neuropsychiatric symptoms (NPS) with Pittsburgh Compound B (PiB) and fluorodeoxyglucose positron emission tomography (FDG-PET) in predicting cognitive trajectories. METHODS: We conducted a longitudinal study in the setting of the population-based Mayo Clinic Study of Aging in Olmsted County, MN, involving 1581 cognitively unimpaired (CU) persons aged ≥50 years (median age 71.83 years, 54.0% males, 27.5% APOE ɛ4 carriers). NPS at baseline were assessed using the Neuropsychiatric Inventory Questionnaire (NPI-Q). Brain glucose hypometabolism was defined as a SUVR ≤ 1.47 (measured by FDG-PET) in regions typically affected in Alzheimer\u27s disease. Abnormal cortical amyloid deposition was measured using PiB-PET (SUVR ≥ 1.48). Neuropsychological testing was done approximately every 15 months, and we calculated global and domain-specific (memory, language, attention, and visuospatial skills) cognitive z-scores. We ran linear mixed-effect models to examine the associations and interactions between NPS at baseline and z-scored PiB- and FDG-PET SUVRs in predicting cognitive z-scores adjusted for age, sex, education, and previous cognitive testing. RESULTS: Individuals at the average PiB and without NPS at baseline declined over time on cognitive z-scores. Those with increased PiB at baseline declined faster (two-way interaction), and those with increased PiB and NPS declined even faster (three-way interaction). We observed interactions between time, increased PiB and anxiety or irritability indicating accelerated decline on global z-scores, and between time, increased PiB and several NPS (e.g., agitation) showing faster domain-specific decline, especially on the attention domain. CONCLUSIONS: NPS and increased brain amyloid deposition synergistically interact in accelerating global and domain-specific cognitive decline among CU persons at baseline

    Impact of e-ASPECTS software on the performance of physicians compared to a consensus ground truth: a multi-reader, multi-case study

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    BackgroundThe Alberta Stroke Program Early CT Score (ASPECTS) is used to quantify the extent of injury to the brain following acute ischemic stroke (AIS) and to inform treatment decisions. The e-ASPECTS software uses artificial intelligence methods to automatically process non-contrast CT (NCCT) brain scans from patients with AIS affecting the middle cerebral artery (MCA) territory and generate an ASPECTS. This study aimed to evaluate the impact of e-ASPECTS (Brainomix, Oxford, UK) on the performance of US physicians compared to a consensus ground truth.MethodsThe study used a multi-reader, multi-case design. A total of 10 US board-certified physicians (neurologists and neuroradiologists) scored 54 NCCT brain scans of patients with AIS affecting the MCA territory. Each reader scored each scan on two occasions: once with and once without reference to the e-ASPECTS software, in random order. Agreement with a reference standard (expert consensus read with reference to follow-up imaging) was evaluated with and without software support.ResultsA comparison of the area under the curve (AUC) for each reader showed a significant improvement from 0.81 to 0.83 (p = 0.028) with the support of the e-ASPECTS tool. The agreement of reader ASPECTS scoring with the reference standard was improved with e-ASPECTS compared to unassisted reading of scans: Cohen's kappa improved from 0.60 to 0.65, and the case-based weighted Kappa improved from 0.70 to 0.81.ConclusionDecision support with the e-ASPECTS software significantly improves the accuracy of ASPECTS scoring, even by expert US neurologists and neuroradiologists

    Mid- and Late-Life Physical Activity and Neuropsychiatric Symptoms in Dementia-Free Older Adults: Mayo Clinic Study of Aging

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    OBJECTIVE: This study examined associations between physical activity (PA) and neuropsychiatric symptoms (NPS) in older adults free of dementia. METHODS: This cross-sectional study included 3,222 individuals ≥70 years of age (1,655 men; mean±SD age=79.2±5.6; cognitively unimpaired, N=2,723; mild cognitive impairment, N=499) from the population-based Mayo Clinic Study of Aging. PA (taken as a presumed predictor) in midlife (i.e., when participants were 50-65 years of age) and late life (i.e., the year prior to assessment) was assessed with a self-reported, validated questionnaire; PA intensity and frequency were used to calculate composite scores. NPS (taken as presumed outcomes) were assessed with the Neuropsychiatric Inventory Questionnaire, Beck Depression Inventory (BDI-II), and Beck Anxiety Inventory (BAI). Regression analyses included midlife and late-life PA in each model, which were adjusted for age, sex, education, apolipoprotein E ɛ4 status, and medical comorbidity. RESULTS: Higher late-life PA was associated with lower odds of having apathy (OR=0.89, 95% CI=0.84-0.93), appetite changes (OR=0.92, 95% CI=0.87-0.98), nighttime disturbances (OR=0.95, 95% CI=0.91-0.99), depression (OR=0.94, 95% CI=0.90-0.97), irritability (OR=0.93, 95% CI=0.89-0.97), clinical depression (OR=0.92, 95% CI=0.88-0.97), and clinical anxiety (OR=0.90, 95% CI=0.86-0.94), as well as lower BDI-II (β estimate=-0.042, 95% CI=-0.051 to -0.033) and BAI (β estimate=-0.030, 95% CI=-0.040 to -0.021) scores. Higher midlife PA was associated only with higher BDI-II scores (β estimate=0.011, 95% CI=0.004 to 0.019). Sex modified the associations between PA and NPS. CONCLUSIONS: Late-life PA was associated with a lower likelihood of clinical depression or anxiety and subclinical NPS. These findings need to be confirmed in a cohort study
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