Jinlei Li1, Matthew Ogrodnik2, Sherral Devine3, Sanford Auerbach4, Philip A Wolf2, Rhoda Au5. 1. Department of Epidemiology, Peking Union Medical College, Beijing, China; Department of Graduate Medical Sciences, Boston University School of Medicine, Boston, MA, USA. 2. Department of Graduate Medical Sciences, Boston University School of Medicine, Boston, MA, USA. 3. Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA; Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA. 4. Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA. 5. Department of Graduate Medical Sciences, Boston University School of Medicine, Boston, MA, USA; Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA. Electronic address: rhodaau@bu.edu.
Abstract
INTRODUCTION: With a rapidly aging population, general practitioners are confronting the challenge of how to determine those who are at greatest risk for dementia and potentially need more specialized follow-up to mitigate symptoms early in its course. We created a practical dementia risk score and provided individualized estimates of future dementia risk. METHODS: Using the Framingham Heart Study data, we built our prediction model using Cox proportional hazard models and developed a point system for the risk score and risk estimates. RESULTS: The score system used total points ranging from -1 to 31 and stratifies individuals into different levels of risk. We estimated 5-, 10-, and 20-year dementia risk prediction and incorporated these into the points system. DISCUSSION: This risk score system provides a practical tool because all included predictors are easy to assess by practitioners. It can be used to estimate future probabilities of dementia for individuals.
INTRODUCTION: With a rapidly aging population, general practitioners are confronting the challenge of how to determine those who are at greatest risk for dementia and potentially need more specialized follow-up to mitigate symptoms early in its course. We created a practical dementia risk score and provided individualized estimates of future dementia risk. METHODS: Using the Framingham Heart Study data, we built our prediction model using Cox proportional hazard models and developed a point system for the risk score and risk estimates. RESULTS: The score system used total points ranging from -1 to 31 and stratifies individuals into different levels of risk. We estimated 5-, 10-, and 20-year dementia risk prediction and incorporated these into the points system. DISCUSSION: This risk score system provides a practical tool because all included predictors are easy to assess by practitioners. It can be used to estimate future probabilities of dementia for individuals.
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