Evidence map›Paper›PMID 38483857›Full record

SynthesisPloS one2024

The diagnostic accuracy of the Mini-Cog screening tool for the detection of cognitive impairment-A systematic review and meta-analysis.

Simisola Naomi Abayomi, Praveen Sritharan, Ellene Yan, Aparna Saripella, Yasmin Alhamdah, Marina Englesakis, Maria Carmela Tartaglia, David He, Frances Chung

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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  10. Bedside cognitive screening to detect dementia and predict poor outcomes in hospitals.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Simisola Naomi AbayomiDepartment of Medicine, University of Ottawa, Ottawa, Ontario, Canada.
Praveen SritharanMichael G DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada.ORCID 0000-0002-2870-5550
Ellene YanTemerty Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.
Aparna SaripellaDepartment of Anesthesia and Pain Management, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada.
Yasmin AlhamdahTemerty Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.
Marina EnglesakisLibrary & Information Services, University Health Network, Toronto, Ontario, Canada.ORCID 0000-0002-2199-1056
Maria Carmela TartagliaTemerty Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.
David HeDepartment of Anesthesiology and Pain Medicine, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada.
Frances ChungTemerty Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0001-9576-3606

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

objectivesTo evaluate the diagnostic accuracy of the Mini-Cog to screen for cognitive impairment in older patients across different healthcare settings. METHODS/

designWe 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.

resultsThe 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.

conclusionsThe 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.

Indexed as

Cognitive DysfunctionDementiaAgedAged, 80 and overHumansMass ScreeningMiddle AgedSensitivity and Specificity

Identifiers

PMID38483857
PMCPMC10939258

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.