Predictive value of SII and sd-LDL for contrast-induced acute kidney injury in STEMI patients undergoing percutaneous coronary intervention

Aim: To investigate the relationship between the incidence of contrast-induced acute kidney injury (CI-AKI) and the level of small dense low-density lipoprotein (sd-LDL) and systemic immune-inflammation index (SII) in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing emergency percutaneous coronary intervention (PCI), and to further compare the predictive values of SII, sd-LDL and their combination for CI-AKI.
Methods: A total of 674 patients were assigned to a training and a validation cohort according to their chronological sequence. The baseline characteristics of the 450 patients in the training cohort were considered as candidate univariate predictors of CI-AKI. Multivariate logistic regression was then used to identify predictors of CI-AKI and develop a prediction model. The predictive values of SII, sd-LDL and their combination for CI-AKI were also evaluated.
Results: Multivariate logistic regression analysis showed that age, left ventricular ejection fraction (LVEF), sd-LDL, uric acid, estimated glomerular filtration rate (eGFR) and SII were predictors of CI-AKI. The area under the curve (AUC) of the prediction model based on the above factors was 0.846 [95% confidence interval (CI) 0.808–0.884], and the Hosmer-Lemeshow test (P = 0.587, χ2 = 6.543) proved the goodness of fit of the model. The AUC combining SII with sd-LDL to predict CI-AKI was 0.785 (95% CI 0.735–0.836), with a sensitivity of 72.8% and a specificity of 79.8%, and was statistically significant when compared with SII and sd-LDL, respectively. The predictive efficiency of combining SII with sd-LDL and SII were evaluated by improved net reclassification improvement (NRI, 0.325, P < 0.001) and integrated discrimination improvement (IDI, 0.07, P < 0.001).
Conclusions: Both SII and sd-LDL can be used as predictors of CI-AKI in STEMI patients undergoing emergency PCI, and their combination can provide more useful value for early assessment of CI-AKI.