S100B Protein as a Post-traumatic Biomarker for Prediction of Brain Death in Association With Patient Outcomes


1 Department of Neurosurgery, Tabriz University of Medical Sciences, Tabriz, IR Iran

2 Neurosciences Reserch Center, Tabriz University of Medical Sciences, Tabriz, IR Iran


S100B is a calcium-binding protein, belonging to the S100 family proteins which are characterized by their high solubility and, currently, comprises 21 members which are expressed in a cell-specific manner. If we can predict the possibility of definite brain death after brain injury, we will rescue some organs of body to transplant proposes.

In this regard our study focused on the S100B protein value in predicting brain death after head trauma. In this study, the use of serum level of protein S100, 24 hours after trauma has been considered as a reliable index for predicting brain death.

Patients and Methods
72 patients (50 male and 22 female) aged 5 - 80 years old (median 40 ± 17.72 years) with severe head traumas (GCS ≤ 8) were recruited in this cross-sectional study. Glasgow Coma Scale (GCS) and computed tomography (CT) scan findings were recorded for all patients, and then a single 5mL blood sample was obtained from each patient on admission, after 48 hours and a week later or after brain death to determine the level of S100B protein.

Primary and the last GCS of patients had a predictive value in determining brain death (P < 0.0005), also there was a significant correlation between GCS and level of S100B protein. There was a significant correlation between CT scan findings and S100B protein only after 48 hours of trauma.

Changes in S100B protein, especially the levels of this dimer 48 hours after trauma can be used as marker to predict brain death. Alongside other known prognostic factors such as age, GCS and diameters of the pupils, however, this factor individually can not conclusive predict the patient's clinical course and incidence of brain death. However, it is suitable to use GCS, CT scan, clinical symptoms and biomarkers together for a perfect prediction of brain death.