Clinical Report: Assessment of TyG Index and SII for Identifying DKD

Overview

This study evaluates the combined utility of the triglyceride-glucose index (TyG) and systemic immune-inflammation index (SII) in identifying diabetic kidney disease (DKD) among hospitalized patients with type 2 diabetes mellitus (T2DM). The findings suggest that this combination offers a promising screening tool with high sensitivity and specificity for DKD detection.

Background

Diabetic kidney disease (DKD) is a significant complication of type 2 diabetes mellitus (T2DM) and a leading cause of end-stage renal disease (ESRD). Early detection of DKD is crucial for timely intervention, as late-stage diagnosis often leads to irreversible damage. Current screening methods, primarily urinary albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR), have limitations that necessitate the exploration of additional biomarkers for improved diagnostic accuracy.

Data Highlights

Key Findings

• TyG and lgSII were significantly elevated in the DKD group compared to the non-DKD group (P<0.001).
• The final prediction model achieved an AUC of 0.850, indicating good discriminative ability.
• Optimal cut-off values were identified as TyG >10.03 and lgSII >2.76.
• The model demonstrated a sensitivity of 74.3% and specificity of 85.0% for DKD identification.
• Bootstrap validation yielded a mean AUC of 0.855, confirming model stability.
• The high-risk group (both indicators above cut-offs) had a DKD prevalence of 96.8%.

Clinical Implications

The combination of TyG and SII may serve as a low-cost and readily available tool for rapid risk stratification of DKD in hospitalized T2DM patients. Clinicians should consider integrating these indices into routine assessments to enhance early detection and management of DKD.

Conclusion

The findings support the use of TyG and SII as effective screening tools for DKD in hospitalized patients with T2DM. Further external validation is necessary before clinical implementation.

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