Despite decades of research, sepsis remains a poorly understood condition with limited diagnostic tools and treatment. To tackle these obstacles, scientists Vincent Liu, Christopher Seymour, and Hallie Prescott have started using a “big data” approach, which relies on complex computer programs to sift through huge amounts of information. In this case, the computers analyze data such as demographic information, vital signs, and routine blood tests in the electronic health records of sepsis patients. The goal is to find patterns in the data that might help doctors understand, predict, and treat sepsis more effectively.
Health consequences of sepsis
Hallie Prescott, M.D., of the University of Michigan focuses on what happens to sepsis patients who survive initial hospitalization. She says that many people experience new physical illnesses or mental symptoms, and it’s common for patients to enter the hospital again within 3 months. Dr. Prescott wants to understand whether these negative consequences come directly from sepsis or from other illnesses the patient might already have. Doctors already know that certain pre-existing conditions such as autoimmune diseases make some patients more likely to develop sepsis in the first place.
Dr. Prescott recently co-chaired the international colloquium on understanding and enhancing sepsis survivorship. The group concluded that studies of sepsis usually focus on short-term survival, so there is little information on what happens to survivors in the months and years after sepsis. The group made several recommendations to advance research on sepsis survivorship. In the short term, it recommended that hospitals harmonize and share existing datasets to facilitate research. In the longer term, dedicated programs to study sepsis survivors are needed. This work will help doctors find and help patients who are more likely to have a worse prognosis after sepsis.
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