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A survey of concentrations of S100b and NSE in patients with acute cerebral infarction at the Intensive Care Unit of Hue Central Hospital was conducted. Objective: Blood concentrations of S100b and NSE in patients in the acute phase of cerebral infarction were surveyed. To understand the relationship between blood levels of S100b and NSE with some other risk factors such as age, sex, occupation, Glasgow Coma Scale score, and the volume of lesions on computerized tomography. Subjects and Methods: 44 hospitalized patients with acute cerebral infarction at the intensive care unit of Hue central hospital were included. Data was collected through the medical records of patients with acute cerebral infarction. The study method was crossectional and descriptive.. Data was analysed by medical statistics, and processed by the SPSS 16.0 software. Results: The age of the majority of patients was 61 to 80 years (45.5%), i.e patients who are retired and elderly. The mean value of S100b and NSE did not differ between the 2 groups of age and sex (p> 0.05). S100b? and NSE were associated with Glasgow coma scale, as S100b and NSE were elevated in patients with a Glasgow coma scale score of 3-9 points. The lower the GCS score, the more S100b and NSE increased, however the difference was not statistically significant (p> 0.05). The greater the volume of lesions is, the higher the concentration of S100b and NSE becomes. There is a positive correlation between S100b and NSE and lesion volume, the correlation equations were respectively: Y = 33.605X + 68.446 (n=44, r = 0.44, p< 0.01). Y = 2.425x + 30.106 (n=44, r= 0.45, p< 0.01). The cut-off value to predict the survival of S-100b and NSE in this study is respectively 0.45 mcg/l and 37.71ng/ml. The predictive value of survival (death) of S-100 is higher than NSE. Conclusion: The predictive value of survival (death) of S-100 is higher than NSE. The lower a patient’s GCS score, the more S100b and NSE increase. There is a positive correlation between NSE and S100 with lesion volume. NSE and S100b can be used to predict and monitor disease progression and the volume of brain lesions.

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