The Systemic Inflammation Response Index as an Independent Predictor of Acute Kidney Injury in Critically Ill Patients With Acute Myocardial Infarction: Insights From a Large-Scale Cohort Study.

BACKGROUND

Acute kidney injury (AKI) is a critical risk factor for adverse outcomes in acute myocardial infarction (AMI) patients admitted to the intensive care unit (ICU). Early identification of high-risk patients is essential for personalized treatment. The systemic inflammation response index (SIRI), a marker of systemic inflammation, has not been fully explored for its predictive role in AKI.

METHODS

This study included 6936 critically ill AMI patients from the MIMIC-III and MIMIC-IV databases Lasso regression, multivariate logistic regression, restricted cubic spline (RCS) models, and subgroup analyses were employed to explore the association between SIRI and AKI risk. Then, we constructed a predictive model based on these findings internally validated using bootstrapping (1000 repetitions). Discrimination was assessed by the optimism-corrected area under the receiver operating characteristic (ROC) curve (areas under the curve [AUC]), and calibration was evaluated by the calibration curve and the Hosmer-Lemeshow test. The optimal cutoff value for SIRI was determined using the Youden index and propensity score matching (PSM; 1:1) was performed. Conditional logistic regression was used to validate the robustness of this association. Additionally, Cox regression and Kaplan-Meier survival analyses were conducted to assess the relationship between SIRI and in-hospital mortality in the overall cohort.

RESULTS

Elevated SIRI levels independently predicted AKI, showing a nonlinear relationship. Subgroup and propensity-matched analyses confirmed this association. Furthermore, the predictive performance of the model was robust upon internal validation. The optimism-corrected AUC was 0.767 (95% CI: 0.755-0.781) and the calibration curve showed excellent agreement, the Hosmer-Lemeshow test indicated good fit (p=0.539). Kaplan-Meier curves revealed higher in-hospital mortality in higher SIRI quartiles (log-rank p  < 0.001). Multivariate Cox regression further supported SIRI as a significant predictor of in-hospital mortality.

CONCLUSION

SIRI is an independent risk factor for AKI and in-hospital mortality in critically ill AMI patients, offering valuable clinical utility for early AKI prediction and risk stratification.