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A Summary Risk Score for the Prediction of Alzheimer Disease in Elderly Persons
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OBJECTIVE: To develop a simple summary risk score for the prediction of Alzheimer disease in elderly persons based on their vascular risk profiles. DESIGN: A longitudinal, community-based study. SETTING: New York, New York. Patients One thousand fifty-one Medicare recipients aged 65 years or older and residing in New York who were free of dementia or cognitive impairment at baseline. MAIN OUTCOME MEASURES: We separately explored the associations of several vascular risk factors with late-onset Alzheimer disease (LOAD) using Cox proportional hazards models to identify factors that would contribute to the risk score. Then we estimated the score values of each factor based on their beta coefficients and created the LOAD vascular risk score by summing these individual scores. RESULTS: Risk factors contributing to the risk score were age, sex, education, ethnicity, APOE epsilon4 genotype, history of diabetes, hypertension or smoking, high-density lipoprotein levels, and waist to hip ratio. The resulting risk score predicted dementia well. According to the vascular risk score quintiles, the risk to develop probable LOAD was 1.0 for persons with a score of 0 to 14 and increased 3.7-fold for persons with a score of 15 to 18, 3.6-fold for persons with a score of 19 to 22, 12.6-fold for persons with a score of 23 to 28, and 20.5-fold for persons with a score higher than 28. CONCLUSIONS: While additional studies in other populations are needed to validate and further develop the score, our study suggests that this vascular risk score could be a valuable tool to identify elderly individuals who might be at risk of LOAD. This risk score could be used to identify persons at risk of LOAD, but can also be used to adjust for confounders in epidemiologic studies.
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“Accordingly, high lipid levels could be one of the risk factors for AD (Reitz et al., 2010).”
From Effect of Probiotic Supplementation on Cognitive Function and Metabolic Status in Alzheimer's Disease: A Randomized, Double-Blind and Controlled Trial (2016) · cites this paper as Reitz et al., 2010
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Metadata
- Authors
- Reitz, C., Tang, M.-X., Schupf, N., Manly, J. J., Mayeux, R., & Luchsinger, J. A.
- Affiliations
- Columbia University (US)
- Mayo Clinic (US)
- Venue
- Archives of Neurology
- Publisher
- American Medical Association (AMA)
- Published
- 2010-07-01
- Volume
- 67
- Issue
- 7
- Pages
- 835-41
- ISSN
- 0003-9942 (ISSN-L)
- PMC
- PMC3068839
- OpenAlex
- W2142160461
- Cited by
- 199
- References
- 73
- Citations by year
- 2026: 8 · 2025: 6 · 2024: 10 · 2023: 13 · 2022: 10 · 2021: 21 · 2020: 15 · 2019: 13 · 2018: 12 · 2017: 9 · 2016: 15 · 2015: 9 · 2014: 11 · 2013: 17 · 2012: 13
- FWCI
- 10.03
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Archives of Neurology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (R01AG037212, P01AG007232, K23AG034550, AG 07702, AG 07232, R01AG041797, P50AG008702, U24AG056270)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neurological Disease Mechanisms and Treatments
- Keywords
- Alzheimer's disease, late-onset Alzheimer's disease, vascular risk factors, risk score, dementia prediction, older adults, APOE ε4, diabetes mellitus, hypertension, smoking, HDL cholesterol, waist-to-hip ratio, ethnicity, sex differences, risk stratification
- MeSH terms
- Age Factors, Aged, Aged, 80 and over, Alzheimer Disease, Diabetes Mellitus, Female, Humans, Hypertension, Longitudinal Studies, Male, Neuropsychological Tests, New York City, Predictive Value of Tests, Psychiatric Status Rating Scales, Residence Characteristics, Risk Factors, Geriatric Assessment, Proportional Hazards Models, Apolipoprotein E4
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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