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September 10, 2025Open Access

Optimizing Nutritional Assessment in Gastrointestinal Oncosurgery: A Comparative Analysis of GLIM and PG-SGA

LZLi ZhuFujian Medical University ZLZhihui LuFudan University SWShurui WangCapital University

Key Points

Malnutrition prevalence was notably high at 74.5% using GLIM and 87.5% using PG-SGA in the study population undergoing elective gastrointestinal surgery.
Significant correlations were found between malnutrition severity and clinical biomarkers, including albumin and hemoglobin levels, as well as 6-month quality of life scores.
Multivariate regression analysis identified several risk factors for malnutrition, including advanced age and cardiovascular metabolic diseases, highlighting patient-specific considerations.
The negligible inter-method agreement (κ = 0.07) suggests variability between GLIM and PG-SGA, necessitating tailored nutritional assessment strategies based on clinical objectives.

Abstract

Abstract Objective This prospective cohort study evaluates the diagnostic efficacy of the Global Leadership Initiative on Malnutrition (GLIM) criteria and the Patient-Generated Subjective Global Assessment (PG-SGA) in identifying malnutrition among patients undergoing elective gastrointestinal tumor resection. It further examines associations between malnutrition, clinical biomarkers, body composition, and postoperative quality of life (QoL). Methods Nutritional risk screening (NRS2002) and subsequent malnutrition diagnosis (GLIM/PG-SGA) were performed in 216 patients from a tertiary care center. Correlations between malnutrition severity, biochemical indices, and QoL were analyzed. Multivariate regression identified risk factors for malnutrition. Results Malnutrition prevalence was 74.5% (GLIM) and 87.5% (PG-SGA). Both tools inversely correlated with albumin, prealbumin, hemoglobin, and 6-month QoL scores. GLIM-associated risk factors included advanced age (β: 0.181, p = 0.013), combined with cardiovascular and metabolic diseases (CVMD; β: -0.253, pβ: -0.234, pβ: 0.181, p = 0.007) and TNM stage > II (β: 0.212, p = 0.002). Inter-method agreement was negligible (κ = 0.07). Conclusions Selection of nutritional assessment tools could align with clinical objectives: GLIM prioritizes current physiological metrics and tumor-specific factors (e.g., sarcopenia and gastric cancer), while PG-SGA to some extent reflects tumor burden (e.g., TNM staging and NLR).

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