Plasma neutrophil extracellular traps in patients with sepsis-induced acute kidney injury serve as a new biomarker to predict 28-day survival outcomes of disease - He, Jian; Zheng, Feng; Qiu, Lihua; Wang, Yilan; Zhang, Jing; Ye, Hongwei; Zhang, Qian (Frontiers in Medicine, 2024)
Background: There is no accurate and readily available, validated biomarker for assessing disease severity and survival outcome in sepsis-induced acute kidney injury (SAKI), which is a limitation to conduct therapeutic interventions. The neutrophil extracellular traps (NETs) may be involving in the pathophysiology of SAKI. The present study investigated the predictive value of plasma NETs for survival outcome of patients with SAKI. Method: This observational study included 136 SAKI patients, who obtained a 28-day follow-up. According to the records of follow-up, SAKI patients were divided into two groups: non-survive group (60 subjects) and survive group (76 subjects). Blood samples were collected after the diagnosis of AKI for measurement of three NETs markers and 12 inflammatory indices. Correlation analysis, logistic regression analysis, receiver operating characteristic curve analysis, and survival analysis were performed. Results: Compared with survivors in SAKI patients, three plasma NETs markers showed significantly increased levels in non-survivors (all p < 0.001). Meanwhile, in SAKI patients, plasma levels of NETs markers were significantly associated with serum levels of inflammatory indices, and serum interleukin (IL) -2, IL-8, IL-10, and tumour necrosis factor alpha showed an interactive effect with plasma NETs markers on the survival of SAKI patients. Furthermore, the combination of three plasma NETs markers could identify SAKI patients with a poor 28-day survival with a better accuracy (area under the curve = 0.857). Finally, plasma NETs markers could independently predict the 28-day survival in SAKI patients. Conclusion: Plasma NETs markers were increased levels in SAKI patients with a poor outcome, and served as biomarkers to predict 28-day survival in SAKI patients.