Each year, ~2,000,000 people in the U.S. develop sepsis and over 250,000 of these people die. Clinicians need advanced support when they make rapid, high-stakes decisions about sepsis for individual patients. Personalized risk stratification can help save lives and reduce unnecessary and potentially harmful care.
Our lab, through a DoD funded study on post-operative sepsis, has developed blood biomarkers that can predict up to 3 days prior to diagnosis, with a 0.91 combined selectivity/sensitivity score. The current standard of care panel is 0.6 – 0.7.
We are also collaborating with the Hadlock lab, who are using machine learning on electronic health records, to develop a more accurate, trustworthy risk score for clinicians; and the Heath lab who will leverage their technology to better understand the immune response to Sepsis to identify new therapeutic targets.
Recent papers include:
A biological function based biomarker panel optimization process. Lee MY, Kim TK, Walters KA, Wang K. Sci Rep. 2019 May 14;9(1):7365. doi: 10.1038/s41598-019-43779-2. PMID: 31089177
Current Project Leads:
|Kai Wang||Simon Evans||Jennifer Hadlock||Leroy Hood|