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Updated: Jun 10, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Free and cued selective reminding identifies very mild dementia in primary care
Ellen Grober1, Amy E Sanders, Charles Hall
1Department of Neurology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, New York 10462, USA.
Abstract:
The Free and Cued Selective Reminding Test (FCSRT) is used widely to identify very mild dementia; 3 alternative scoring procedures have been proposed based on free recall, total recall, and cue efficiency. We compared the predictive validity of these scoring procedures for the identification of very mild prevalent dementia (CDR=0.5), of incident dementia, and for distinguishing Alzheimer Disease (AD) and nonAD dementias. We tested 244 elderly African American and White primary care patients at 18 month intervals using a screening neuropsychologic battery that included the FCSRT and a comprehensive diagnostic neuropsychologic battery. Median follow-up was 2.6 years. Dementia diagnoses were assigned using standard criteria without access to the results of the screening battery. There were 50 prevalent and 28 incident dementia cases. At scores selected to provide specificities of 90%, free recall was more sensitive to incident and prevalent dementia than the other 2 measures. Patients with impaired free recall were 15 times more likely to have a prevalent dementia and their risk of future dementia was 4 times higher than patients with intact free recall. Neither race nor education affected prediction although older patients were at increased risk of future dementia. Total recall was more impaired in AD dementia than in nonAD dementias. The results indicate that using the FCSRT, free recall is the best measure for detecting prevalent dementia and predicting future dementia. Total recall impairment supports the diagnosis of AD rather than nonAD dementia.
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