series event

Real-time identification of sepsis-causing pathogens

Real-time identification of sepsis-causing pathogens using sensor-based metabolomics and machine learning

Abstract: Sepsis is a medical emergency demanding rapid diagnosis and tailored antimicrobial therapy. It represents the 10th leading cause of death in the US; killing more patients than prostate cancer, breast cancer and HIV/AIDS combined. It is responsible for 11% of ICU admissions, with a mortality rate estimated at 28% to 50%. Current clinical practice requires several steps starting with blood culture to detect presence of infection followed by a variety of species identification methods all of which combined can take up to several days until a definitive diagnosis is obtained. Specific Technologies has developed a novel, inexpensive, fully automated paradigm for the real-time detection and identification of sepsis-causing pathogens based on their emission of volatile metabolites produced during growth using a combination of sensor-based metabolomics and advanced data mining technologies.

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