Diagnostic and prognostic value of new bioscore in critically ill septic patients

G-rich sequence factor 1 serves as a prognostic biomarker in septic patients

Background

Sepsis is a condition of organ dysfunction caused by infection, and is unavoidably related to costs and mortality; however, no biomarker has yet been identified to clearly predict the prognosis of septic patients. In this study, we aimed to explore the role of guanine-rich sequence factor 1 (GRSF1) in evaluating the severity and prognosis of sepsis.

Methods

The expression of GRSF1 in peripheral blood was measured and analyzed in 42 septic participants and 32 healthy controls respectively by using quantitative reverse transcription polymerase chain reaction (RT-qPCR). Clinical data were assessed by correlation analysis. In addition, GRSF1 expression was investigated in cecal ligation and puncture (CLP) induced mice septic models by RT-qPCR and western blot (WB).

Results

The expression of GRSF1 expression in septic patients in the first day of electronic intensive care unit (eICU) administration was significantly lower in comparison with HC. Further analysis showed GRSF1 expression was strongly related to the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) score and Sequential Organ Failure Assessment (SOFA) score. Low expression of GRSF1 predicted high mortality within 24 hours in septic patients and in CLP-induced mice.

Conclusions

Decreased expression of GRSF1 was significantly correlated with high mortality in septic patients, and also in experimental septic mice. The GRSF1 protein may be a potential prognostic biomarker in sepsis.

Current Evidence and Limitation of Biomarkers for Detecting Sepsis and Systemic Infection

Sepsis was recently redefined as a life-threatening disease involving organ dysfunction caused by a dysregulated host response to infection. Biomarkers play an important role in early detection, diagnosis, and prognostication. We reviewed six promising biomarkers for detecting sepsis and systemic infection, including C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), CD64, presepsin, and sTREM-1. Among the recent studies, we found the following risks of bias: only a few studies adopted the random or consecutive sampling strategy; extensive case-control analysis, which worsened the over-estimated performance; most of the studies used post hoc cutoff values; and heterogeneity with respect to the inclusion criteria, small sample sizes, and different quantitative synthesis methods applied in meta-analyses. We recommend that CD64 and presepsin should be considered as the most promising biomarkers for diagnosing sepsis. Future studies should enroll a larger sample size with a cohort rather than a case-control study design. A random or consecutive study design with a pre-specified laboratory threshold, consistent sampling timing, and an updated definition of sepsis will also increase the reliability of the studies. Further investigations of appropriate specimens, testing assays, and cutoff levels for specific biomarkers are also warranted.