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Updated: Oct 28, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A systematic review and network meta-analysis of interventions for subjective cognitive decline
Mandy Roheger1, Xenia-Serena Hennersdorf1, Steffen Riemann1
1Department of Neurology University Medicine Greifswald Greifswald Germany.
Background:
Subjective cognitive decline (SCD) is considered a risk factor for Alzheimer's disease (AD), highlighting the need for identifying and ranking effective interventions. This was addressed in a systematic review and network meta-analysis (NMA) of pharmacological and non-pharmacological interventions for SCD.
Methods:
MEDLINE, Web of Science Core Collection, CENTRAL, and PsycINFO were searched for randomized controlled trials (RCTs) investigating effects on memory, global cognition, and quality of life. Random-effect model NMAs were conducted. The Cochrane Risk-of-Bias-2 tool assessed methodological quality. Prospero-Registration: CRD42020180457.
Results:
The systematic review included 56 RCTs. Education programs were most effective for improving memory, second most effective for improving global cognition. Quality of life and adverse events could not be included due to insufficient data. Overall methodological quality of studies was low.
Conclusion:
Education programs were most effective for improving memory and cognition, warranting further research into effective elements of this intervention. There is urgent need to address identified methodological shortcomings in SCD intervention research.
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