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Introduction: Cardiovascular events (CVE) remain the leading cause of mortality in hemodialysis (HD) patients. The ability to assess the risk of short-term CVE is of great importance. Soluble suppression of tumorogenicity-2 (sST2) is a novel biomarker that better stratifies risk of CVE than troponins in patients with heart failure. Few studies have investigated the role of sST2 in the HD population. The aim of this single-center study was to assess the predictive ability of sST2 on CVE in comparison to high-sensitive cardiac troponin I (hs-cTnI) and B-type natriuretic peptide (BNP) in HD patients., Methods: This study used a prospective, observational cohort design. We enrolled 40 chronic HD patients asymptomatic for chest pain and without recent history of acute coronary syndrome. We tested sST2 pre-/post-HD, hs-cTnI, and BNP. Demographic/dialytic/echocardiographic data were evaluated. We recorded the number of CVE for 12 months. The patients were classified into 2 groups: those who developed CVE and those who did not., Results: Ten of the 40 patients (25%) developed CVE during a 12-month follow-up. Increased sST2 levels (p < 0.0001) as well as hs-cTnI and BNP are predictive of CVE. When analyzing biomarkers as binary variables for values above or below the normal range, the correlation remained significant only for sST2 (p = 0.001). A small variation in sST2 levels before and after HD sessions was found (-2.1 ng/mL). sST2 was correlated with left ventricular (LV) echocardiographic data: LV mass index (p = 0.0001), LV ejection fraction (p = 0.01), and diastolic bulging of septum (p = 0.015). BNP and sST2 combination increased the prediction of CVE in a statistical model., Conclusion: Our study confirms that sST2 is useful for stratifying CV risk in the HD population. sST2 can be evaluated simply as a dichotomous value higher or lower than the normal range, making it easily interpretable. Dialysis and residual diuresis did not affect significantly sST2. A multimarker approach that incorporates sST2 and BNP may improve the prediction of CVE., (© 2021 S. Karger AG, Basel.)