Application of bioelectrical impedance analysis in the nutritional assessment of patients with gynecologic malignancies

Abstract Objective: To analyze body composition measurements and explore their correlation with the nutritional risk screening score and neutrophil-to-lymphocyte ratio (NLR; an index of inflammation) to provide a basis for the perioperative and nutritional management of patients with gynecologic malignancy. Methods: This study included 77 patients with gynecologic malignancies confirmed by surgical pathology between December 2021 and January 2023. Preoperative body composition data were obtained using bioelectrical impedance analysis. Nutritional risk screening and assessment were performed. Differences in body composition by age, nutritional status, International Federation of Gynecology and Obstetrics (FIGO) stage, systemic inflammatory response, and type of gynecologic malignancy were compared. Results: The extracellular water ratio was significantly higher in patients with a high FIGO stage than in those with a low FIGO stage ( t =4.047, P <0.001). Other body composition parameters were lower in patients with a high FIGO stage than in those with a low FIGO stage ( P <0.05). Regarding the NLR, the extracellular water ratio was significantly higher in patients with a high NLR than in those with a low NLR ( t =2.929, P =0.005). As the nutritional condition worsened, the extracellular water ratio increased ( H =12.291, P =0.002), with no significant difference in other body composition parameters between patients with different nutritional conditions ( H =5.118, P =0.077). Other body composition parameters decreased with the nutritional condition, which was statistically significant ( P <0.05). Conclusions: Bioelectrical impedance analysis is an easy-to-perform, noninvasive, and reproducible measurement technique that can assess changes in body composition. Body composition analysis can effectively determine an individual’s nutritional and metabolic status, providing a reference for the management of patients with gynecologic malignancy, and potentially providing predictive biomarkers to stratify these patients.