Frontiers in Endocrinology (Jan 2024)

Association of systemic immune-inflammation index with diabetic kidney disease in patients with type 2 diabetes: a cross-sectional study in Chinese population

  • Pijun Yan,
  • Pijun Yan,
  • Pijun Yan,
  • Pijun Yan,
  • Pijun Yan,
  • Yuxia Yang,
  • Yuxia Yang,
  • Yuxia Yang,
  • Yuxia Yang,
  • Yuxia Yang,
  • Xing Zhang,
  • Xing Zhang,
  • Xing Zhang,
  • Xing Zhang,
  • Xing Zhang,
  • Yi Zhang,
  • Yi Zhang,
  • Yi Zhang,
  • Yi Zhang,
  • Yi Zhang,
  • Jia Li,
  • Jia Li,
  • Jia Li,
  • Jia Li,
  • Jia Li,
  • Zujiao Wu,
  • Xiaofang Dan,
  • Xiaofang Dan,
  • Xiaofang Dan,
  • Xiaofang Dan,
  • Xiaofang Dan,
  • Xian Wu,
  • Xian Wu,
  • Xian Wu,
  • Xian Wu,
  • Xian Wu,
  • Xiping Chen,
  • Shengxi Li,
  • Yong Xu,
  • Yong Xu,
  • Yong Xu,
  • Yong Xu,
  • Yong Xu,
  • Qin Wan,
  • Qin Wan,
  • Qin Wan,
  • Qin Wan,
  • Qin Wan

DOI
https://doi.org/10.3389/fendo.2023.1307692
Journal volume & issue
Vol. 14

Abstract

Read online

ObjectiveSystemic immune-inflammation index (SII), a novel inflammatory marker, has been reported to be associated with diabetic kidney disease (DKD) in the U.S., however, such a close relationship with DKD in other countries, including China, has not been never determined. We aimed to explore the association between SII and DKD in Chinese population.MethodsA total of 1922 hospitalized patients with type 2 diabetes mellitus (T2DM) included in this cross-sectional study were divided into three groups based on estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (ACR): non-DKD group, DKD stages 1–2 Alb group, and DKD-non-Alb+DKD stage 3 Alb group. The possible association of SII with DKD was investigated by correlation and multivariate logistic regression analysis, and receiver-operating characteristic (ROC) curves analysis.ResultsMoving from the non-DKD group to the DKD-non-Alb+DKD stage 3 Alb group, SII level was gradually increased (P for trend <0.01). Partial correlation analysis revealed that SII was positively associated with urinary ACR and prevalence of DKD, and negatively with eGFR (all P<0.01). Multivariate logistic regression analysis showed that SII remained independently significantly associated with the presence of DKD after adjustment for all confounding factors [(odds ratio (OR), 2.735; 95% confidence interval (CI), 1.840-4.063; P < 0.01)]. Moreover, compared with subjects in the lowest quartile of SII (Q1), the fully adjusted OR for presence of DKD was 1.060 (95% CI 0.773-1.455) in Q2, 1.167 (95% CI 0.995-1.368) in Q3, 1.266 (95% CI 1.129-1.420) in the highest quartile (Q4) (P for trend <0.01). Similar results were observed in presence of DKD stages 1–2 Alb or presence of DKD-non- Alb+DKD stage 3 Alb among SII quartiles. Last, the analysis of ROC curves revealed that the best cutoff values for SII to predict DKD, Alb DKD stages 1- 2, and DKD-non-Alb+ DKD stage 3 Alb were 609.85 (sensitivity: 48.3%; specificity: 72.8%), 601.71 (sensitivity: 43.9%; specificity: 72.3%), and 589.27 (sensitivity: 61.1%; specificity: 71.1%), respectively.ConclusionHigher SII is independently associated with an increased risk of the presence and severity of DKD, and SII might be a promising biomarker for DKD and its distinct phenotypes in Chinese population.

Keywords