Abstract
PURPOSE: The predictive value of the Systemic Immune-Inflammation Index (SII) on mortality in patients with sepsis-associated acute kidney injury (S-AKI) remains unclear. This study aims to investigate the predictive value of SII levels at the Intensive Care Unit (ICU) on the 28-day mortality of S-AKI patients. PATIENTS AND METHODS: S-AKI patients admitted to the ICU of Henan Provincial People's Hospital from January 1, 2023, to December 31, 2023. Patients who were diagnosed with S-AKI were divided into survival and death groups based on their 28-day outcome after ICU admission. Using receiver operating characteristic (ROC) curves to determine the best cut-off values and prognostic abilities of various parameters. Kaplan-Meier survival curves describe the 28-day survival of patients after ICU admission. Cox regression analysis identified the main risk factors associated with mortality in S-AKI patients, constructing a predictive nomogram. The concordance index (C-index) and decision curve analysis were used to validate the predictive ability of this model. RESULTS: A total of 216 patients with S-AKI were included. ROC analysis showed that SII had the highest predictive value for mortality risk in S-AKI patients after ICU admission. Compared with the low-SII group, the high-SII group had higher 28-day (86.7% vs 32.4%, respectively, P <0.001) mortality rate. Based on Cox regression analysis, a nomogram predictive model was constructed, including age, respiratory failure, SII levels, number of organ dysfunctions at ICU admission, sequential organ failure assessment (SOFA), and acute physiology and chronic health evaluation II (APACHEII). The C-index for predicting the 28-day survival rate was 0.682. Decision curve analysis indicated a high level of clinical predictive efficacy. CONCLUSION: SII serves as a potential biomarker for predicting the prognosis of S-AKI patients. The constructed nomogram prognostic model can aid in assessing the prognosis of S-AKI patients.