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Updated: May 23, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Screening for mild cognitive impairment in patients with heart failure: Montreal cognitive assessment versus mini
Jan Cameron1, Linda Worrall-Carter, Karen Page
1Cardiovascular Research Centre, Australian Catholic University, Melbourne, Australia. jan.cameron@acu.edu.au
Background:
Cognitive impairments occur frequently in patients with chronic heart failure (CHF), resulting in worse health outcomes than expected. These impairments can remain undetected unless specifically screened. There are limited sensitive screening measures available in nursing practice to identify mild cognitive impairment (MCI).
Aim:
To compare the Montreal Cognitive Assessment (MoCA) with the Mini Mental State Exam (MMSE) in screening for MCI in CHF patients.
Methods:
The MMSE and MoCA were administered to 93 hospitalized CHF patients (70±11 years), without a history of neurocognitive problems. Patients with low MoCA scores (<26) were compared to those with low MMSE scores (<27). Two different parameters were examined between the MoCA and the MMSE: level of MCI agreement (Kappa coefficient) and task errors on assessed cognitive domains (χ2 test).
Results:
Statistically more patients had low MoCA scores compared with low MMSE scores (66 vs. 30, p=0.02). The MoCA classified 38 (41%) patients as cognitively impaired that were not classified by the MMSE. A significantly low level of agreement was found (κ=0.25, p=0.001) between the MMSE and MoCA in identifying patients with scores suggestive of MCI. More task errors were observed on the MoCA cognitive domains compared with the MMSE cognitive domains. In 68% of patients with low cognitive scores, visuospatial task errors were observed on tasks from the MoCA compared with 22% on a similar task of the MMSE.
Conclusion:
The MoCA, a screening tool for MCI, identified subtle but potentially clinically relevant cognitive dysfunctions with greater frequency than MMSE.
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