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Updated: Mar 22, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Specific Features of Subjective Cognitive Decline Predict Faster Conversion to Mild Cognitive Impairment
Miguel A Fernández-Blázquez1, Marina Ávila-Villanueva1, Fernando Maestú2,3
1Alzheimer Disease Research Unit, CIEN Foundation, Carlos III Institute of Health, Alzheimer Center Queen Sophia Foundation, Madrid, Spain.
Background:
Alzheimer's disease (AD) is a silent disorder that needs the earliest possible intervention in order to reduce its high economic and social impact. It has been recently suggested that subjective cognitive decline (SCD) appears at preclinical stages many years before the onset of AD. Therefore, SCD could become an ideal target for early therapeutic intervention.
Objective:
The goal of this study was to evaluate the clinical significance of SCD on the conversion from a cognitively healthy stage to a mild cognitive impairment (MCI) in one-year follow-up.
Methods:
A total of 608 cognitively intact individuals from the Vallecas Project's cohort, a community-based prospective study to identify early markers of AD, were enrolled in this study. Participants were classified in three groups: i) No Complaints (NCg), ii) Subjects with complaints in one or more cognitive domains (SCDg), and iii) Subjects who, besides complaints, fulfilled the features of SCD Plus proposed by the International Working Group of SCD (SCD-Pg).
Results:
Individuals were followed up for a mean of 13.1 months (range 10.7-22.4). During this time, 41 volunteers developed MCI (6.7% of total sample). The conversion rate for SCD-Pg (18.9%) was significantly higher than SCDg (5.6%) and NCg (4.9%).
Conclusion:
Specific features associated with SCD may help to identify individuals at high risk of fast conversion to MCI. These results highlight the importance of a close follow-up of subjects with SCD-P and include them in early intervention programs because of their increased risk for the development of MCI.
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