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

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 This cross-sectional study enrolled 147 maintenance PD patients. Participants were stratified into low (MIS ≤ 5, n = 62) and high (MIS 5, n = 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 Patients with an MIS of 5 had significantly lower body mass index (BMI), albumin, lymphocyte percentage, ALI, PNI, and GNRI, as well as significantly higher dialysis vintage, CRP, neutrophil-to-lymphocyte ratio (NLR), CAR, and CONUT scores (all p 0.05). All objective indices showed significant correlations with MIS, with GNRI demonstrating the strongest correlation ( r = −0.558, p 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.