Automatic Culture-free Detection of Bacteria from Blood for Rapid Sepsis Diagnostics

Abstract

Approximately 50 million people suffer from sepsis yearly, and 13 million die from it. For every hour a patient with septic shock is untreated, their survival rate decreases by 8%. Therefore, rapid detection and antibiotic susceptibility profiling of bacterial agents in the blood of sepsis patients are crucial for determining appropriate treatment. The low bacteria concentrations and high abundance of blood cells currently necessitate culture-based diagnostic methods, which can take several days. Here, we introduce a method to isolate bacteria from whole blood with high separation efficiency through smart centrifugation, followed by microfluidic trapping and subsequent detection using deep learning applied to microscopy images.