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The Systemic Inflammation Response Index as an Independent Predictor of Acute Kidney Injury in Critically Ill
Xudong Li1,2, Liang Ruan1,2, Shuyuan Zhang1,2
1Department of Cardiology, Zhongda Hospital, Southeast University, Nanjing, Jiangsu, China.
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.
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