Neutrophil percentage to albumin ratio and advanced cardiovascular-kidney-metabolic syndrome in diabetes: a machine learning approach.

BACKGROUND: Diabetes mellitus (DM) has become an increasingly significant global health challenge, with rising complications and mortality rates. Patients with DM are at a higher risk for advanced Cardiovascular-kidney-metabolic (CKM) syndrome, underscoring the importance of early detection and precise prevention strategies. The neutrophil percentage to albumin ratio (NPAR), a composite biomarker, may be indicative of inflammatory dysregulation and nutritional status in patients with advanced CKM and DM. This study aims to explore the association between NPAR and advanced CKM in patients with diabetes. METHODS: Data were derived from six National Health and Nutrition Examination Survey (NHANES) cycles (1999-2020), including 9375 adults. Multivariable logistic regression analyses were conducted to assess the association of NPAR with advanced CKM in diabetes, and restricted cubic spline (RCS) regression was further applied to explore potential nonlinear relationships. Subgroup analyses were performed to explore differences across various population factors. Feature selection was carried out using the Boruta algorithm, and predictive performance was evaluated through receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA). RESULTS: This study found a positive association between NPAR and risk of advanced CKM in diabetes. The RCS analysis revealed that this positive correlation was linear. Subgroup analysis showed no significant interactions across groups. Feature selection identified 22 relevant variables, and the machine learning model demonstrated excellent predictive accuracy (Area under curve: 0.873 and 0.872 for training and validation sets). The calibration curves and DCA affirmed the model's clinical relevance. CONCLUSIONS: This study suggests that an elevated NPAR may serve as a potential marker for advanced CKM in patients with diabetes. It holds potential as an adjunct tool for detection and management of advanced CKM in patients with DM, offering valuable insights for clinical practice.