Santos Ketsia Meneses Souza, Boulhosa Ramona Souza da Silva Baqueiro, Garcêz Laís Spindola, Lyra André Castro, Bueno Allain Amador, de Jesus Rosangela Passos, Oliveira Lucivalda Pereira Magalhães
Food, Nutrition and Health Post-Graduation Program, Federal University of Bahia, Salvador, Bahia, Brazil.
Department of Health, Salvador City Council, Brazil.
Nutrition. 2025 Feb;130:112612. doi: 10.1016/j.nut.2024.112612. Epub 2024 Oct 24.
Early clinical prognosis and mortality reduction remains a challenge in chronic liver disease (CLD). The full potential of the Nutritional Prognostic Index (NPI) for nutritional assessment and management in CLD patients remains unexplored. The aim of this study was to establish an NPI cutoff point for the identification of nutritional risk in advanced CLD (ACLD) patients, as well as to assess the NPI's ability to predict ACLD-associated mortality.
This ethically approved prospective cohort study investigated malnutrition risk using both the NPI and the Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) in patients hospitalized for ACLD. NPI reference values were determined using a receiver operating characteristic curve. Associations between nutritional risk identified by the RFH-NPT and the NPI were assessed using Fisher's exact test, and agreement between tools was assessed using the Kappa index. The association between NPI-defined nutritional risk and 12-mo mortality was examined using Pearson Chi-square test.
The sample population consisted of 120 adults, comprising 84 (70%) male and 57 (50.9%) of alcoholic etiology and presenting as Child-Pugh A, B, or C at admission. The identified cutoff point for NPI was <41, identifying nutritional risk in 82.5% of patients. The NPI presented a statistically significant association with the RFH-NPT, with a substantial agreement coefficient of 0.34. An association between NPI <41 cutoff and mortality were observed, with 82.1% of the sample below cutoff experiencing mortality within 12 mo.
The NPI is a valuable nutritional marker for the identification of nutritional risk in ACLD and is a simple and effective assessment tool that can aid in early CLD prognosis assessment. Validation, however, remains necessary in other CLD populations of different etiologies.
