Work

Association between objective nutritional indices and malnutrition inflammation score in peritoneal dialysis patients

Year: 2026

Type: article

Abstract: Objective: This study aimed to investigate the associations between objective nutritional indices and the Malnutrition-Inflammation Score (MIS) in patients undergoing peritoneal dialysis (PD).. Methods: = 85) malnutrition-inflammation risk groups based on MIS. The objective nutritional indices, such as C-reactive protein-to-albumin ratio (CAR), advanced lung cancer inflammation index (ALI), prognostic nutritional index (PNI), geriatric nutritional risk index (GNRI), and controlling nutritional status (CONUT) score, were calculated. Clinical characteristics, laboratory parameters, and objective indices were compared between the groups. Correlation analyses and multivariable linear regression were used to assess the relationship between MIS and each objective index. The predictive performance of each index for identifying malnutrition risk was evaluated using receiver operating characteristic (ROC) curve analysis. Results: < 0.001). These associations remained significant after multivariate adjustment. The ROC analysis indicated that all indices had significant predictive value for an MIS of >5. GNRI showed the highest predictive performance (area under the curve (AUC) = 0.75, 95% CI: 0.67-0.83), with an optimal cutoff value of 92.5 (sensitivity 90.3%, specificity 56.5%), followed by ALI (AUC = 0.72) and PNI (AUC = 0.70). Conclusion: Objective nutritional indices, particularly GNRI, ALI, and PNI, are significantly associated with MIS and effectively identify PD patients at high risk of malnutrition. These readily available objective tools could serve as practical alternatives to MIS for rapid nutritional assessment and large-scale screening in clinical practice. However, future multicenter, large-scale studies are warranted to validate our findings and determine the optimal index.

Source: Frontiers in Nutrition

DOI: 10.3389/fnut.2025.1713482

Authors: Xinqi Teng, Xiangyu Yang, Leiyun Wang, Lulu Li

Institution: Wuhan No.1 Hospital

Language: English

Topic: Dialysis and Renal Disease Management

Subfield: Nephrology

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Zero hunger

Open Access status: gold

Estimated APC paid: $3,801