Frontiers in Nutrition (Feb 2024)
Validity and applicability of the global leadership initiative on malnutrition criteria in non-dialysis patients with chronic kidney disease
Abstract
IntroductionThere are no standardized assessment criteria for selecting nutritional risk screening tools or indicators to assess reduced muscle mass (RMM) in the Global Leadership Initiative on Malnutrition (GLIM) criteria. We aimed to compare the consistency of different GLIM criteria with Subjective Global Assessment (SGA) and protein-energy wasting (PEW).MethodsIn this study, nutritional risk screening 2002 first four questions (NRS-2002-4Q), Nutritional Risk Screening 2002 (NRS-2002), Malnutrition Universal Screening Tool (MUST), and Mini-Nutritional Assessment Short-Form (MNA-SF) tools were used as the first step of nutritional risk screening for the GLIM. The RMM is expressed using different metrics. The SGA and PEW were used to diagnose patients and classify them as malnourished and non-malnourished. Kappa (κ) tests were used to compare the concordance between the SGA, PEW, and GLIM of each combination of screening tools.ResultsA total of 157 patients were included. Patients with Chronic kidney disease (CKD) stage 1–3 accounted for a large proportion (79.0%). The prevalence rates of malnutrition diagnosed using the SGA and PEW were 18.5% and 19.7%, respectively. The prevalence of GLIM-diagnosed malnutrition ranges from 5.1% to 37.6%, depending on the different screening methods for nutritional risk and the different indicators denoting RMM. The SGA was moderately consistent with the PEW (κ = 0.423, p < 0.001). The consistency among the GLIM, SGA, and PEW was generally low. Using the NRS-2002-4Q to screen for nutritional risk, GLIM had the best agreement with SGA and PEW when skeletal muscle index (SMI), fat-free mass index (FFMI), and hand grip strength (HGS) indicated a reduction in muscle mass (SGA: κ = 0.464, 95% CI 0.28–0.65; PEW: κ = 0.306, 95% CI 0.12–0.49).ConclusionThe concordance between the GLIM criteria and the SGA and PEW depended on the screening tool used in the GLIM process. The inclusion of RMM in the GLIM framework is important. The addition of HGS could further improve the performance of the GLIM standard compared to the use of body composition measurements.
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