PeerJ · 2024
Systemic immune-inflammation index as an independent risk factor for diabetic nephropathy: a retrospective, single-center study.
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Zhang Xiaohong, Fang Yuan, Weng Mengjie, Chen Caiming, Xu Yanfang, Wan Jianxin
Аннотация
PURPOSE: Systemic immune-inflammation index (SII) was an indicator which could reflect immune response and systemic inflammation. We aim to explore the relationship between SII and diabetic nephropathy (DN).
METHODS: SII was calculated as neutrophil count × platelet count/lymphocyte count. The receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnosis power of SII. Univariate and multivariate logistic analysis were conducted to assess SII as the risk factor for DN. A restricted cubic spline model was carried out to show the nonlinear association between SII and DN.
RESULTS: Two hundred participants were enrolled, with an average age of 56.6 ± 13.4 years; 54% participants were categorized as DN. Spearman association analysis showed SII was positive associated with increased urinary albumin to creatinine ratio and serum creatinine, while negative associated with eGFR and serum albumin. The ROC curve revealed that the maximum area under the curve (AUC) was 0.761 (95% CI, 0.694-0.828, P < 0.001). After univariate and multivariate logistic analysis, SII (OR=1.004, P = 0.002) and serum creatinine (OR=1.146, P < 0.001) were risk factors for the occurrence of DN, while age (OR=0.920, P = 0.011) and serum albumin (OR=0.708, P < 0.001) were protective factors for the occurrence of DN. The restricted cubic spline model showed that there was a significant nonlinear association between DN incidence and continuous SII value when it exceeded 624*10 ˆ 9/L.
CONCLUSION: SII is a novel diagnostic biomarker which is independently associated with DN. Further large-scale prospective studies are needed to validate our findings before SII can be considered a reliable diagnostic or prognostic tool for DN.
METHODS: SII was calculated as neutrophil count × platelet count/lymphocyte count. The receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnosis power of SII. Univariate and multivariate logistic analysis were conducted to assess SII as the risk factor for DN. A restricted cubic spline model was carried out to show the nonlinear association between SII and DN.
RESULTS: Two hundred participants were enrolled, with an average age of 56.6 ± 13.4 years; 54% participants were categorized as DN. Spearman association analysis showed SII was positive associated with increased urinary albumin to creatinine ratio and serum creatinine, while negative associated with eGFR and serum albumin. The ROC curve revealed that the maximum area under the curve (AUC) was 0.761 (95% CI, 0.694-0.828, P < 0.001). After univariate and multivariate logistic analysis, SII (OR=1.004, P = 0.002) and serum creatinine (OR=1.146, P < 0.001) were risk factors for the occurrence of DN, while age (OR=0.920, P = 0.011) and serum albumin (OR=0.708, P < 0.001) were protective factors for the occurrence of DN. The restricted cubic spline model showed that there was a significant nonlinear association between DN incidence and continuous SII value when it exceeded 624*10 ˆ 9/L.
CONCLUSION: SII is a novel diagnostic biomarker which is independently associated with DN. Further large-scale prospective studies are needed to validate our findings before SII can be considered a reliable diagnostic or prognostic tool for DN.