Impact of the triglyceride–glucose–neutrophil-to-lymphocyte ratio (TyG-NLR) and the C-reactive protein–TyG index (CTI) on cardio-renal disease in patients with type 2 diabetes

Ying Guo¹Hongjian Jia²Yan Wang²Mengyan Li³Tong Chen²Zhendong Diao²Xicheng Li²Jietao Zhang^2*

• ¹Affiliated Hospital of Jining Medical University, Jining, China
• ²The Affiliated Hospital of Qingdao University, Qingdao, China
• ³Shandong Second Medical University, Weifang, China

Background: We compared the triglyceride–glucose– neutrophil-to-lymphocyte ratio and a C-reactive protein–TyG–based index to examine their associations with severity outcomes in hospitalized adults with type 2 diabetes. Methods:We conducted a retrospective study of hospitalized adults with type 2 diabetes at the Affiliated Hospital of Qingdao University, classifying cardiorenal disease into four severity levels. Using ordinal logistic regression, we evaluated the independent associations of the C-reactive protein–TyG–based index and the triglyceride–glucose– neutrophil-to-lymphocyte ratio with severity, performed trend testing, and explored potential nonlinearity with restricted cubic splines . For robustness, we additionally fitted a partial proportional odds model and a multinomial logistic model. Relative to a base covariate model, we assessed the incremental value of these indices in terms of overall model performance , discrimination, calibration , and clinical net benefit via decision-curve analysis. Results:A total of 2,885 patients were included. In multivariable ordinal logistic regression analysis, both higher quartiles of CTI and TyG-NLR were significantly associated with increased disease severity. The Brant test indicated partial violation of the proportional odds assumption; sensitivity analysis using a VGAM-based partial proportional odds model yielded consistent results across thresholds. Trend tests revealed a significant linear increase in disease severity across quartiles for both indices .Restricted cubic spline analysis showed a nonlinear relationship between TyG-NLR and disease severity , with the risk plateauing beyond a TyG-NLR value of approximately 16.64; in contrast, CTI exhibited an approximately linear association.Regarding model performance, the TyG-NLR model achieved the best overall fit, while CTI yielded moderate improvement. In terms of discrimination, the TyG-NLR model attained the highest AUC of 0.680 and the lowest Brier score of 0.476. Calibration curves demonstrated good agreement at all thresholds, with the TyG-NLR model showing the closest alignment with the ideal line.Decision curve analysis indicated that TyG-NLR provided the greatest net clinical benefit across a wide range of threshold probabilities (0.05–0.35), followed by CTI. Both VGAM and multinomial logistic models yielded consistent directions of association, supporting the robustness of these findings. Conclusions:In adults with type 2 diabetes, both CTI and TyG-NLR were independently associated with cardiorenal disease severity.