Testosterone and soluble ST2 as mortality predictive biomarkers in male patients with sepsis-induced cardiomyopathy

FRONTIERS IN MEDICINE(2024)

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摘要
Sepsis-induced cardiomyopathy (SIC) is characterized by high mortality and poor outcomes. This study aimed to explore the relationship between testosterone and soluble ST2 (sST2) and all-cause mortality in patients with SIC. Clinical data from SIC patients at Renmin Hospital of Wuhan University from January 2021 and March 2023 were reviewed. Serum testosterone and sST2 were measured at admission. Kaplan-Meier analysis and receiver operative characteristic curve (ROC) were used to estimate the predictive values of testosterone and sST2 on 28 days and 90 days mortality of SIC. A total of 327 male subjects with SIC were enrolled in this study. During the 28 days and 90 days follow-up, 87 (26.6%) and 103 deaths (31.5%) occurred, respectively. Kaplan-Meier analysis showed significantly higher 28 days and 90 days survival in patients with higher testosterone and decreased sST2 levels (p < 0.001). Testosterone, sST2, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were significantly associated with 28 days and 90 days mortality (p < 0.05). Partial correlation analysis showed strong positive correlation between testosterone and left ventricular ejection fraction (LVEF) (p < 0.001), and negative correlation between testosterone and sST2 (p < 0.001), high-sensitivity troponin I (hs-TnI) levels (p < 0.001) and smoke history (p < 0.01). The concentrations of sST2 were positively related with E/e ' ratio (p < 0.001), and negatively correlated with TAPSE (p < 0.001). The combination of testosterone and sST2 enhanced the prediction of both 28 days [area under the ROC curve (AUC), 0.805] and 90 days mortality (AUC, 0.833). Early serum testosterone and sST2 levels could predict mortality of SIC independently and jointly. Further research is needed to determine the utility of biochemical markers in identifying high-risk patients with SIC.
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关键词
sepsis-induced cardiomyopathy,male,testosterone,sST2,mortality prediction,biomarkers
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