ABSTRACT
Objective: The activation of platelets in individuals with type 2 diabetes mellitus (T2DM) triggers inflammation and hemodynamic abnormalities, contributing to the development of diabetic kidney disease (DKD). Despite this, research into the relationship between plateletcrit (PCT) levels and DKD is sparse, with inconsistent conclusions drawn regarding the connection between various platelet parameters and DKD. This highlights the necessity for comprehensive, large-scale population studies. Therefore, our objective is to explore the association between PCT levels and various platelet parameters in relation to DKD. Methods: In this cross-sectional study, hematological parameter data were collected from a cohort of 4,302 hospitalized Chinese patients. We analyzed the relationships between PCT, platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), platelet large cell ratio (P-LCR), and DKD, along with the urinary albumin-to-creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR). Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic potential of these parameters. Results: DKD patients exhibited significantly higher PCT levels compared to those without DKD. Multivariate regression analysis identified elevated PCT and PLT levels as potential independent risk factors for both DKD and UACR, while lower MPV levels might serve as independent protective factors for eGFR. The areas under the ROC curve for PCT in relation to DKD and UACR (≥30 mg/g) were 0.523 and 0.526, respectively. The area under the ROC curve for PLT in relation to UACR (≥30 mg/g) was 0.523. Conclusion: PCT demonstrates a weak diagnostic value for T2DM patients at risk of developing DKD and experiencing proteinuria, and PLT shows a similarly modest diagnostic utility for detecting proteinuria. These insights contribute to a deeper understanding of the complex dynamics involved in DKD. Additionally, incorporating these markers into routine clinical assessments could enhance risk stratification, facilitating early interventions and personalized management strategies.
