Determining the optimal value of the Geriatric Nutritional Risk Index to screen older patients with malnutrition risk: A study at a university hospital in Japan.

Abstract:

AIM:The Geriatric Nutritional Risk Index (GNRI) can predict nutritional risk. However, just a few studies have validated the optimal cut-off value of GNRI for nutrition screening in older patients. Hence, this study aimed to determine the optimal value of GNRI to screen the risk of malnutrition among older patients. METHODS:This retrospective cross-sectional study was carried out with 5867 consecutive older adult patients who were admitted to an academic hospital in Japan. Receiver operating characteristic curve analyses were carried out to obtain the optimal cut-off value of GNRI, and the results were compared against the Mini Nutritional Assessment - Short Form and Malnutrition Universal Screening Tool. The validation of the obtained cut-off value was examined on the concordance rate of malnutrition diagnosis based on the European Society of Clinical Nutrition and Metabolism criteria. RESULTS:The mean age of the patients was 76.0 ± 7.0 years. The optimal cut-off value of GNRI for Mini Nutritional Assessment - Short Form ≤11 points was 95.92 (area under the curve 0.827 [0.817-0.838], P < 0.001), and that for Malnutrition Universal Screening Tool ≥1 point was 95.95 (area under the curve 0.788 [0.776-0.799], P < 0.001). By adapting GNRI <96 points as an initial screening cut-off in the European Society of Clinical Nutrition and Metabolism-defined malnutrition process, the concordance rates of comparisons were 98.5% and 98.5% for Mini Nutritional Assessment - Short Form-based and MUST-based diagnosis, respectively. CONCLUSIONS:The study showed GNRI <96 points as the optimal cut-off value for nutritional screening. GNRI might be one of the easy-to-use tools for nutritional screening and for diagnosing malnutrition in older adults. Geriatr Gerontol Int 2020; 20: 811-816.

journal_name

Geriatr Gerontol Int

authors

Ishida Y,Maeda K,Nonogaki T,Shimizu A,Yamanaka Y,Matsuyama R,Kato R,Ueshima J,Mori N

doi

10.1111/ggi.13976

subject

Has Abstract

pub_date

2020-09-01 00:00:00

pages

811-816

issue

9

eissn

1444-1586

issn

1447-0594

journal_volume

20

pub_type

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