Abstract summary 

The Mini-Cog is a rapid screening tool that can be administered to older adults to detect cognitive impairment (CI); however, the accuracy of the Mini-Cog to detect CI for older patients in various healthcare settings is unclear.To evaluate the diagnostic accuracy of the Mini-Cog to screen for cognitive impairment in older patients across different healthcare settings.We searched nine electronic databases (including MEDLINE, Embase) from inception to January 2023. We included studies with patients ≥60 years old undergoing screening for cognitive impairment using the Mini-Cog across all healthcare settings. A cut-off of ≤ 2/5 was used to classify dementia, mild cognitive impairment (MCI), and cognitive impairment (defined as either MCI or dementia) across various settings. The diagnostic accuracy of the Mini-Cog was assessed against gold standard references such as the Diagnostic and Statistical Manual of Mental Disorders (DSM). A bivariate random-effects model was used to estimate accuracy and diagnostic ability. The risk of bias was assessed using QUADAS-2 criteria.The systematic search resulted in 4,265 articles and 14 studies were included for analysis. To detect dementia (six studies, n = 4772), the Mini-Cog showed 76% sensitivity and 83% specificity. To detect MCI (two studies, n = 270), it showed 84% sensitivity and 79% specificity. To detect CI (eight studies, n = 2152), it had 67% sensitivity and 83% specificity. In the primary care setting, to detect either MCI, dementia, or CI (eight studies, n = 5620), the Mini-Cog demonstrated 73% sensitivity and 84% specificity. Within the secondary care setting (seven studies, n = 1499), the Mini-Cog to detect MCI, dementia or CI demonstrated 73% sensitivity and 76% specificity. A high or unclear risk of bias persisted in the patient selection and timing domain.The Mini-Cog is a quick and freely available screening tool and has high sensitivity and specificity to screen for CI in older adults across various healthcare settings. It is a practical screening tool for use in time-sensitive and resource-limited healthcare settings.

Authors & Co-authors:  Abayomi Sritharan Yan Saripella Alhamdah Englesakis Tartaglia He Chung

Study Outcome 

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