Classification Models for Early Identification of Persons at Risk for Dementia in Primary Care: An Evaluation in a Sample Aged 80 Years and Older

Abstract

Aim: To evaluate previously developed classification models to make implementation in primary care possible and aid early identification of persons at risk for dementia. Methods: Data were drawn from the OCTO-Twin study. At baseline, 521 persons ≧80 years of age were nondemented, and for 387 a blood sample was available. Predictors of dementia were collected and analyzed in initially nondemented persons using generalized estimating equations and Cox survival analyses. Results: In the basic model using predictors already known or easily obtained (basic set), the mean 2-year predictive value increased from 6.9 to 28.8% in persons with memory complaints and an MMSE score ≤25. In the extended model, using both the basic set and an extended set of predictors requiring further assessment, the 8-year predictive value increased from 15.0 to 45.8% in persons with low cholesterol and an MMSE score ≤24. Conclusion: Both models can contribute to an improved early identification of persons at risk for dementia in primary care.