Cognitive-Communicative Predictors of Mild Cognitive Impairment: A Systematic Review and Meta-Analysis
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Mild cognitive impairment (MCI) is the preclinical stage and sign of dementia. It is also important for guidance in the prevention and intervention of neurological disease. The purpose of this study was to review literatures on cognitive/communicative and other predictors of MCI patients systematically, and to propose the evidence-based data including effect sizes of them using a meta-analysis method. Fifty-seven researches published since 2010, meeting the inclusion and exclusion criteria, were entered into the analysis. They were analyzed in a methodological and content level, and the effect sizes were calculated by 3 predictors. Predictive values were pooled from cognitive (10 domains), communicative (9 domains), and other (3 domains). The main findings were as follows. Firstly, the general target population for studies was older adults over the age of 55, and most studies included at least 2 types of predictors. Secondly, average effect sizes of 3 predictors in MCI were all significant. Thirdly, cognitive predictors like memory and general cognition had significant and high-level effect sizes. Fourthly, communicative predictors including comprehension and word fluency had moderate-level effect sizes significantly. Lastly, all demographic and neuropsychological (age, education, depression) predictors had significant and moderate-level effect sizes. Our results provide the evidence-based information to predict MCI. Especially, specific cognitive and communicative predictors may contribute to increase the diagnostic and prognostic accuracy in MCI. This study is also expected to present clinically available data and increase the effect in intervention for MCI.
Abstract
Mild cognitive impairment (MCI) is the preclinical stage and sign of dementia. It is also important for guidance in the prevention and intervention of neurological disease. The purpose of this study was to review literatures on cognitive/communicative and other predictors of MCI patients systematically, and to propose the evidence-based data including effect sizes of them using a meta-analysis method. Fifty-seven researches published since 2010, meeting the inclusion and exclusion criteria, were entered into the analysis. They were analyzed in a methodological and content level, and the effect sizes were calculated by 3 predictors. Predictive values were pooled from cognitive (10 domains), communicative (9 domains), and other (3 domains). The main findings were as follows. Firstly, the general target population for studies was older adults over the age of 55, and most studies included at least 2 types of predictors. Secondly, average effect sizes of 3 predictors in MCI were all significant. Thirdly, cognitive predictors like memory and general cognition had significant and high-level effect sizes. Fourthly, communicative predictors including comprehension and word fluency had moderate-level effect sizes significantly. Lastly, all demographic and neuropsychological (age, education, depression) predictors had significant and moderate-level effect sizes. Our results provide the evidence-based information to predict MCI. Especially, specific cognitive and communicative predictors may contribute to increase the diagnostic and prognostic accuracy in MCI. This study is also expected to present clinically available data and increase the effect in intervention for MCI.
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