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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Association between the Geriatric Nutritional Risk Index and mild cognitive impairment in elderly patients with type
Shuyun Li1, Ying Yang1, Gang Tian1
1The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Abstract:
BackgroundDiabetes increases the risk of mild cognitive impairment (MCI). The Geriatric Nutritional Risk Index (GNRI) is an objective indicator for assessing malnutrition risk, and aging and malnutrition are closely associated with MCI. However, the relationship between GNRI and MCI in older type 2 diabetes mellitus (T2DM) remains unclear.ObjectiveTo investigate the correlation between GNRI and MCI in elderly patients with T2DM.MethodsIn this cross-sectional study, 366 T2DM patients aged ≥ 60 years were divided into MCI and normal cognitive function (NCF) group according to the Montreal Cognitive Assessment (MoCA). Nutritional status was evaluated by calculating GNRI levels. GNRI levels and MoCA scores were compared between two groups, and correlation and regression analysis were performed to explore the association between GNRI and MCI.ResultsThe GNRI level in the MCI group was significantly lower than that in the NCF group (p < 0.05) and positively correlated with MoCA scores (r = 0.783, p < 0.001). MCI prevalence increased progressively with decreasing GNRI levels. After adjusting for confounders, the odds of MCI were significantly higher in the 92 ≤ GNRI ≤ 98 and GNR < 92 groups compared to GNRI < 98 (p < 0.05). Binary logistic regression identified that after adjusting for age, education level, body mass index, HbA1c, HOMA-IR, 25(OH)D and DR, GNRI as an independent protective factor for T2DM with MCI (OR = 0.783, 95%CI 0.648-0.874, p < 0.001).ConclusionsLower GNRI levels are associated with increased risk of MCI in elderly T2DM patients; GNRI is a potential predictor of MCI. Assessing nutritional status of elderly with T2DM facilitates the early clinical recognition of MCI.
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