Issue link: https://beckershealthcare.uberflip.com/i/571945
43 Research Links Liver to Pneumonia, Sepsis Susceptibility By Shannon Barnet F or the first time, researchers have revealed a direct link between liv- er-produced molecules and pneumo- nia susceptibility during sepsis. The Boston University School of Medicine-led study was published in the journal Infection and Immu- nity. To model the common clinical scenario of sepsis followed by pneumonia, research- ers systemically treated models with a bac- terial product that would elicit a sepsis-like response, followed hours later by a live bacterial challenge in the lungs. One group of models had completely normal livers, and the other lacked a gene in their livers that prevented maximal liver activation. The study showed those in the group lacking a complete liver response exhibited a significantly compromised immune re- sponse in both the lungs and blood, where more bacteria survived, and were ultimately more likely to succumb to pneumonia. According to corresponding author Lee J. Quinton, PhD, associate professor of medicine and pathology at BUSM, "The re- sults of this study directly suggest that liver activation is required to maintain adequate immune responses in the lungs." The authors suggest that liver activity may serve as a previously unrealized win- dow into pneumonia defense and suscepti- bility. "A better understanding of how these distinct organs collaborate to mount im- mune responses has important clinical implications for patients with or at risk for pneumonia and sepsis," said Dr. Quinton. "The idea that non-lung tissue could be targeted for treatments of lung disease is compelling." n New Algorithm Can Help Detect Sepsis Faster By Heather Punke A computer algorithm developed by researchers from Johns Hopkins in Baltimore could correctly predict septic shock in 85 percent of cases without increasing the number of false positives, according to a study published in Science Translational Medicine. "e critical advance our study makes is to detect these patients early enough that clinicians have time to intervene," Suchi Saria, a Johns Hopkins assistant professor of computer science and health policy and the study's leader, told Hub. Researchers created an algorithm that determines a Targeted Real-time Early Warning Score based on 27 factors which measure a patient's risk of septic shock. To do so, researchers used electronic health records of 16,234 patients admitted to intensive care units at Boston-based Beth Israel Deaconess Medical Center from 2001 to 2007. "With a median lead time of over 24 hours, this scoring algorithm may allow clinicians enough time to intervene before the patients suffer the most damaging effects of sepsis," the study reads. Now the researchers are looking into how the algorithm and TREWScore can be used in a hospital or nursing home, according to the Hub report. n