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Comparison of three objective nutritional screening tools for identifying GLIM-defined malnutrition in patients with gastric cancer.
Zuo, Junbo; Huang, Yan; Huang, Zhenhua; Zhang, Jingxin; Hou, Wenji; Wang, Chen; Wang, Xiuhua; Bu, Xuefeng.
Afiliación
  • Zuo J; Department of General Surgery, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
  • Huang Y; Department of Nutrition, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
  • Huang Z; Department of Nutrition, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
  • Zhang J; Department of Cardiovascular Medicine, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
  • Hou W; Department of General Surgery, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
  • Wang C; Department of General Surgery, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
  • Wang X; Department of General Surgery, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
  • Bu X; Department of General Surgery, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
Eur J Clin Nutr ; 2024 Sep 29.
Article en En | MEDLINE | ID: mdl-39343804
ABSTRACT

OBJECTIVE:

This study aimed to compare three objective nutritional screening tools for identifying GLIM-defined malnutrition in patients with gastric cancer (GC).

METHOD:

Objective nutritional screening tools including geriatric nutritional risk index (GNRI), prognostic nutritional index (PNI), and controlling nutritional status (CONUT) score, were evaluated in patients with GC at our institution. Malnutrition was diagnosed according to the GLIM criteria. The diagnostic value of GNRI, PNI, and COUNT scores in identifying GLIM-defined malnutrition was assessed by conducting Receiver Operating Characteristic (ROC) curves and calculating the area under the curve (AUC). Additionally, sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were determined. The Kappa coefficient (k) was used to assess agreement between three objective nutritional screening tools and GLIM criteria.

RESULTS:

A total of 316 patients were enrolled in this study, and malnutrition was diagnosed in 151 (47.8%) patients based on the GLIM criteria. The GNRI demonstrated good diagnostic accuracy (AUC = 0.805, 95% CI 0.758-0.852) for detecting GLIM-defined malnutrition, while the PNI and COUNT score showed poor diagnostic accuracy with AUCs of 0.699 (95% CI 0.641-0.757) and 0.665 (95% CI 0.605-0.725) respectively. Among these objective nutritional screening tools, the GNRI-based malnutrition risk assessment demonstrated the highest specificity (80.0%), accuracy (72.8%), PPV (74.8%), NPV (71.4%), and consistency (k = 0.452) with GLIM-defined malnutrition.

CONCLUSIONS:

Compared to PNI and COUNT scores, GNRI demonstrated superior performance as an objective nutritional screening tool for identifying GLIM-defined malnutrition in GC patients.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Eur J Clin Nutr Asunto de la revista: CIENCIAS DA NUTRICAO Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Eur J Clin Nutr Asunto de la revista: CIENCIAS DA NUTRICAO Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido