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Updated: Jul 19, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Role of comprehensive geriatric assessment in screening for mild cognitive disorders
Jie Yu1, Shou-Rong Lu1, Zhuo Wang1
1Department of Geriatrics, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi 214023, Jiangsu Province, China.
Background:
The role of comprehensive geriatric assessment (CGA) in screening for mild cognitive disorders was not known.
Aim:
To evaluate the role of CGA in screening for mild cognitive disorders.
Methods:
A total of 100 elderly people who underwent health examinations in our hospital and community between January 2020 and December 2021 were included for analysis. Using Petersen as the diagnostic gold standard, healthy individuals were included in the control group and patients with mild cognitive impairment were assigned to the study group. The correlation between the cognitive function of the patients and their baseline clinical profiles was analyzed. Patients' Montreal Cognitive Assessment (MoCA) and CGA screening results were compared, and the sensitivity and specificity were calculated to assess the screening role of CGA.
Results:
CGA assessment yielded higher diagnostic accuracy than MoCA. The results of the multivariate regression analysis showed no correlation of gender, age, body mass index and literacy with cognitive function. Patients with mild cognitive impairment obtained significantly lower MoCA scores than healthy individuals (P < 0.05). In the CGA scale, patients with mild cognitive impairment showed significantly lower Mini-mental State Examination, Miniature Nutritional Assessment and Berg Balance Scale scores, and higher Activity of Daily Living, Instrumental Activities of Daily Living Scale and Frailty Screening Inventory scores than healthy individuals (P < 0.05), whereas the other assessment scales showed no significant differences (P > 0.05). The CGA provides higher diagnostic sensitivity and specificity than the MoCA (P < 0.05).
Conclusion:
CGA allows accurate identification of mild cognitive impairment with high sensitivity and specificity, facilitating timely and effective intervention, and is thus recommended for clinical use.
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