Diagnostic Agreement of GLIM Criteria with SGA for Malnutrition in Non-Dialysis Chronic Kidney Disease

Shuai Chen,1,* Jing Xue,1,* Kaidi Zhang,1 Yicun Xu,2 Lina Yuan,3 Caixia Liu,2 Baoli Zhao,2 Lihua Zhao41Second Department of Nephrology, First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China; 2Department of Rehabilitation, First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China; 3Third Department of Intensive Care Medicine, First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China; 4Department of Nutrition, First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lihua Zhao, Department of Nutrition, First Hospital of Hebei Medical University, No. 89 Donggang Road, Shijiazhuang, Hebei, 050000, People’s Republic of China, Tel +86-13832104091, Email lhzhaozz@163.com Baoli Zhao, Department of Rehabilitation, First Hospital of Hebei Medical University, No. 89 Donggang Road, Shijiazhuang, Hebei, 050000, People’s Republic of China, Email hvdg22@163.comBackground and Objective: Malnutrition significantly contributes to the adverse prognosis of patients with chronic kidney disease (CKD). The Global Leadership Initiative on Malnutrition (GLIM) criteria were introduced to standardize malnutrition diagnosis globally. This study evaluates the diagnostic performance and agreement of the GLIM criteria compared with the Subjective Global Assessment (SGA) in non-dialysis CKD patients.Methods: In this cross-sectional study, 248 non-dialysis CKD patients (stages G1-G5) were screened using the Nutritional Risk Screening 2002 (NRS-2002). Patients with a score < 3 were classified as well-nourished. Those with a score ≥ 3 underwent GLIM assessment incorporating phenotypic and etiologic parameters. CKD was operationalized as fulfilling the GLIM disease-burden/inflammation etiologic criterion; therefore, GLIM-based prevalence was interpreted in light of this assumption. Concurrently, all patients were assessed using SGA (the reference standard). Diagnostic agreement was evaluated using Cohen’s Kappa, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Multivariable logistic regression identified factors independently associated with GLIM-diagnosed malnutrition.Results: The prevalence of malnutrition was 46.8% by SGA and 49.2% by GLIM. The GLIM framework demonstrated substantial agreement with SGA (Kappa = 0.812, P < 0.001). The GLIM criteria exhibited a sensitivity of 87.9%, a specificity of 84.8%, and an AUC of 0.864 (95% CI: 0.818– 0.910). Malnutrition prevalence increased progressively with advanced CKD stages (P < 0.001). Multivariable analysis revealed that advanced CKD stage, older age, and lower serum albumin were factors independently associated with GLIM-diagnosed malnutrition.Conclusion: The GLIM criteria demonstrate good diagnostic agreement with the SGA in assessing malnutrition among non-dialysis CKD patients. While GLIM provides a standardized and structured framework, longitudinal studies are required to validate its predictive value for clinical outcomes.Keywords: global leadership initiative on malnutrition, subjective global assessment, nutritional risk screening 2002, chronic kidney disease, malnutrition, diagnostic performance