The value of perioperative nutritional risk stratification in the prevention of surgical site infection: precision application from GLIM/PG-SGA to PNI, CONUT, and GNRI.

Surgical site infection (SSI) remains a major postoperative complication despite advances in perioperative prophylaxis and standardized care. Increasing evidence suggests that perioperative malnutrition is a host-related condition linking systemic inflammation, impaired immune recovery, low muscle mass, delayed wound healing, and increased susceptibility to infection. This narrative review summarizes the biological relationship between perioperative malnutrition and SSI, critically compares the roles of GLIM, PG-SGA, PNI, CONUT, and GNRI, and distinguishes SSI-specific findings from evidence based on broader postoperative outcomes. GLIM and PG-SGA are most useful for defining clinically meaningful malnutrition phenotypes, whereas PNI, CONUT, and GNRI support rapid and objective risk quantification. Because these tools capture different dimensions of nutritional vulnerability, we propose a complementary, stepwise pathway integrating early screening, phenotype-based diagnosis, secondary risk stratification, targeted intervention, and postoperative reassessment. This framework should be regarded as a hypothesis-generating clinical model that requires prospective validation before it can be adopted as a standardized SSI-prevention algorithm.