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Background: The objective of this study was to establish a prospective population-based cohort to investigate the prevalence, incidence and risk factors for mild cognitive impairment (MCI) and dementia. Methods: The Olmsted County, Minn., population, aged 70–89 years on October 1, 2004, was enumerated using the Rochester Epidemiology Project. Eligible subjects were randomly selected and invited to participate. Participants underwent a comprehensive in-person evaluation including the Clinical Dementia Rating Scale, a neurological evaluation and neuropsychological testing. A consensus diagnosis of normal cognition, MCI or dementia was made by a panel using previously published criteria. A subsample of subjects was studied via telephone interview. Results: Four hundred and two subjects with dementia were identified from a detailed review of their medical records but were not contacted. At baseline, we successfully evaluated 703 women aged 70–79 years, 769 women aged 80–89 years, 730 men aged 70–79 years and 517 men aged 80–89 years (total n = 2,719). Among the participants, 2,050 subjects were evaluated in person and 669 via telephone. Conclusions: Strengths of the study are that the subjects were randomly selected from a defined population, the majority of the subjects were examined in person, and MCI was defined using published criteria. Here, we report the design and sampling, participation, baseline measures and sample characteristics.

INTRODUCTION Our goal was to develop cut-points for amyloid PET, tau PET, FDG PET, and MRI cortical thickness. METHODS We examined five methods for determining cut-points. RESULTS The reliable worsening method produced a cut-point only for amyloid PET. The specificity, sensitivity, and accuracy of clinically impaired versus young clinically normal (CN) methods labeled the most people positive and all gave similar cut-points for tau PET, FDG PET and cortical thickness. Cut-points defined using the accuracy of clinically impaired versus age-matched CN method labeled fewer people positive. DISCUSSION In the future, we will employ a single cut-point for amyloid PET (SUVR 1.42, centiloid 19) based on the reliable worsening cut-point method. We will base lenient cut-points for tau PET, FDG PET and cortical thickness on the accuracy of clinically impaired vs young CN method and base conservative cut-points on the accuracy of clinically impaired vs age-matched CN method.

Objective:We investigated the prevalence of mild cognitive impairment (MCI) in Olmsted County, MN, using in-person evaluations and published criteria. Methods:We evaluated an age-and sex-stratified random sample of Olmsted County residents who were 70-89 years old on October 1, 2004, using the Clinical Dementia Rating Scale, a neurologic evaluation, and neuropsychological testing to assess 4 cognitive domains: memory, executive function, language, and visuospatial skills. Information for each participant was reviewed by an adjudication panel and a diagnosis of normal cognition, MCI, or dementia was made using published criteria.Results: Among 1,969 subjects without dementia, 329 subjects had MCI, with a prevalence of 16.0% (95% confidence interval [CI] 14.4-17.5) for any MCI, 11.1% (95% CI 9.8-12.3) for amnestic MCI, and 4.9% (95% CI 4.0-5.8) for nonamnestic MCI. The prevalence of MCI increased with age and was higher in men. The prevalence odds ratio (OR) in men was 1.54 (95% CI 1.21-1.96; adjusted for age, education, and nonparticipation). The prevalence was also higher in subjects who never married and in subjects with an APOE ⑀3⑀4 or ⑀4⑀4 genotype. MCI prevalence decreased with increasing number of years of education (p for linear trend Ͻ0.0001). Conclusions:Our study suggests that approximately 16% of elderly subjects free of dementia are affected by MCI, and amnestic MCI is the most common type. The higher prevalence of MCI in men may suggest that women transition from normal cognition directly to dementia at a later age but more abruptly. Neurology The field of aging and dementia is moving toward an earlier identification of clinical impairment, and the construct of mild cognitive impairment (MCI) has played a pivotal role.1,2 MCI is considered an intermediate state between the cognitive changes of aging and the earliest clinical features of dementia, particularly Alzheimer disease (AD).3 In recent years, the construct has been broadened to include other aspects of cognitive function beyond memory impairment. 4,5 There have been several recent epidemiologic studies on MCI, but most investigators retrofitted the criteria for MCI to previously collected clinical information, used a variety of detection procedures, and implemented the MCI diagnostic criteria using different algorithms.6,7 By contrast, we evaluated in person a population-based sample specifically to detect MCI and its subtypes using published diagnostic criteria.

Objective A workgroup commissioned by the Alzheimer’s Association (AA) and the National Institute on Aging (NIA) recently published research criteria for preclinical Alzheimer’s disease (AD). We performed a preliminary assessment of these guidelines. Methods We employed Pittsburgh compound B positron emission tomography (PET) imaging as our biomarker of cerebral amyloidosis and 18fluorodeoxyglucose PET imaging and hippocampal volume as biomarkers of neurodegeneration. A group of 42 clinically diagnosed AD subjects was used to create imaging biomarker cut-points. A group of 450 cognitively normal (CN) subjects from a population based sample was used to develop cognitive cut-points and to assess population frequencies of the different preclinical AD stages using different cut-point criteria. Results The new criteria subdivide the preclinical phase of AD into stages 1–3. To classify our CN subjects, two additional categories were needed. Stage 0 denotes subjects with normal AD biomarkers and no evidence of subtle cognitive impairment. Suspected Non-AD Pathophysiology (SNAP) denotes subjects with normal amyloid PET imaging, but abnormal neurodegeneration biomarker studies. At fixed cut-points corresponding to 90% sensitivity for diagnosing AD and the 10th percentile of CN cognitive scores, 43% of our sample was classified as stage 0; 16% stage 1; 12 % stage 2; 3% stage 3; and 23% SNAP. Interpretation This cross-sectional evaluation of the NIA-AA criteria for preclinical AD indicates that the 1–3 staging criteria coupled with stage 0 and SNAP categories classify 97% of CN subjects from a population-based sample, leaving just 3% unclassified. Future longitudinal validation of the criteria will be important.