BACKGROUND. In sepsis, there may be dysregulation in programed cell death pathways, typified by apoptosis and necroptosis. Programmed cell death pathways may contribute to variability in the immune response. TRAIL is a potent inducer of apoptosis. Receptor-interacting serine/threonine protein kinase-3 (RIPK3) is integral to the execution of necroptosis. We explored whether plasma TRAIL levels were associated with in-hospital mortality, organ dysfunction, and septic shock. We also explored the relationship between TRAIL and RIPK3. METHODS. We performed an observational study of critically ill adults admitted to intensive care units at 3 academic medical centers across 2 continents, using 1 as derivation and the other 2 as validation cohorts. Levels of TRAIL were measured in the plasma of 570 subjects by ELISA. RESULTS. In all cohorts, lower (<28.5 pg/ml) versus higher levels of TRAIL were associated with increased organ dysfunction (P ≤ 0.002) and septic shock (P ≤ 0.004). Lower TRAIL levels were associated with in-hospital mortality in 2 of 3 cohorts (Weill Cornell-Biobank of Critical Illness, P = 0.012; Brigham and Women’s Hospital Registry of Critical Illness, P = 0.011; Asan Medical Center, P = 0.369). Lower TRAIL was also associated with increased RIPK3 (P ≤ 0.001). CONCLUSION. Lower levels of TRAIL were associated with septic shock and organ dysfunction in 3 independent ICU cohorts. TRAIL was inversely associated with RIPK3 in all cohorts. FUNDING. NIH (R01-HL055330 and KL2-TR002385).
Edward J. Schenck, Kevin C. Ma, David R. Price, Thomas Nicholson, Clara Oromendia, Eliza Rose Gentzler, Elizabeth Sanchez, Rebecca M. Baron, Laura E. Fredenburgh, Jin-Won Huh, Ilias I. Siempos, Augustine M.K. Choi
Usage data is cumulative from May 2019 through October 2019.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.