The Value of SII in Predicting the Mortality of Patients with Heart Failure

BACKGROUND: The main purpose of this study was to explore the predictive value of the systemic immune inflammation index (SII), a novel clinical marker, in heart failure (HF) patients. METHODS: Critically ill patients with HF were identified from the Medical Information Mart for Intensive Care III (MIMIC III) database. Patients were divided into three groups according to tertiles of SII (group 1, group 2, group 3). We used Kaplan-Meier curves and Cox proportional hazards regression models to evaluate the association between the SII and all-cause mortality in HF. Subgroup analysis was used to verify the predictive effect of the SII on mortality. RESULTS: This study included 9107 patients with a diagnosis of HF from the MIMIC III database. After 30, 60, 180, and 365 days of follow-up, 25.60%, 32.10%, 41.30%, and 47.50% of the patients in group 3 had died. Using the Kaplan-Meier curve, we observed that patients with higher SII values had a shorter survival time (log rank p < 0.001). The Cox proportional hazards regression model adjusted for all possible confounders and indicated that the higher SII group had a higher mortality (30-day: HR = 1.304, 95%CI = 1.161 − 1.465, 60-day: HR = 1.266, 95% CI = 1.120 − 1.418, 180-day: HR = 1.274, 95%CI = 1.163 − 1.395, and 365-day: HR = 1.255, 95%CI = 1.155 − 1.364). CONCLUSIONS: SII values could be used as a predictor of prognosis in critically ill patients with HF.