The Biomarker Prediction Model of Septic Risk in Infected Patients

Overview

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to an infection. Sepsis is associated with high mortality because of the complex mechanisms. In China, the mortality of sepsis in ICU was up to 35.5%. As a major and urgent global public health challenge，sepsis is hard to treat because of the complexion and highly heterogeneous in clinical manifestation. The early diagnosis and stratification of the infection is very important. If we can identify the patients who may developed into the sepsis, the therapeutic regimen was not only antibiotic, but also included stable the vascular endothelial cells，regulation of coagulation function and protection of organ functions. Biomarkers have an important place in sepsis because they are strictly related to the organ damage. Each organ has its own specific biomarkers, and these biomarkers will change according to the severity of the disease. So the investigators want to find the difference of biomarkers of each organ in patients from infection to spesis.

According to the definition, infection is the original source of sepsis. How can diagnose organ failure early is the most impotent thing which can prevention the sepsis. In 2021, the guidelines for management of septic and septic shock recommend Sequential Organ Failure Assessment (SOFA) and systemic inflammatory response syndrome (SIRS) to diagnose sepsis. The standards of SOFA were acquired from clinical manifestations，such as blood pressure, oxygenation index, platelet, etc. These indexes can abnormal at the end of organ failure. On the other hand, it is difficult to acquire these indexes in emergency. There is wide variation in diagnostic accuracy of these tools with most having poor predictive values. The number of publications related to sepsis biomarkers has increased over the years. The proportion of new biomarkers has decreased. Because of the complexity of the sepsis response, single biomarker might be fruitless. The investigators want to use the cytokines which have found and can represent the function of the organ in septic patients. The investigations can use these biomarkers of respiratory system, circulation, liver, renal system, coagulation and nervous system, to build up a prediction model of septic risk in infected patients. The participants will be divided into "training set" and "verification set" randomly. The proportion of training set: verification set is 3:2. In the training set, the investigators will compare the cytokines between infection and sepsis. In sepsis patients, the investigators will compare the data between "organ failure group" and "control group", and use these data to build up the prediction model of septic risk. These data will be verify the validity and accuracy of the model in the verification set.