Critical care clinics
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Critical care clinics · Jan 2020
ReviewLubricin as a Therapeutic and Potential Biomarker in Sepsis.
Proteoglycan 4 (or lubricin), a mucin-like glycoprotein, was originally classified as a lubricating substance within diarthrodial joints. More recently, lubricin has been found in other tissues and has been implicated in 2 inflammatory pathways within the cell, via the Toll-like receptors (TLRs) and CD44. Lubricin is an antagonist of TLR2 and TLR4, and appears to enter cells via the CD44 receptor. Because of lubricin's action on these receptors, downstream processes of inflammation are halted, thereby preventing release of cytokines (a hallmark of inflammation and sepsis) from the cell, indicating lubricin's role as a biomarker and possible therapeutic for sepsis.
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Critical care clinics · Jan 2020
ReviewSoluble Triggering Receptor Expressed on Myeloid Cells-1: Diagnosis or Prognosis?
The diagnosis of sepsis, and especially its differentiation from sterile inflammation, may be challenging. The triggering receptor expressed on myeloid cells-1 is an amplifier of the innate immune response. Its soluble form is detectable in various biological fluids and can be used as a surrogate marker of triggering receptor expressed on myeloid cells-1 activation. In this article, we review the abundant literature evaluating the usefulness of soluble triggering receptor expressed on myeloid cells-1 for the diagnosis and the prognosis evaluation of sepsis or localized infections.
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Procalcitonin is a biomarker that is generally elevated in bacterial infections. This review describes a conceptual framework for biomarkers using lessons from the history of troponin, applies this framework to procalcitonin with a review of observational studies and randomized trials in and out of the intensive care unit, and concludes with clinical recommendations and thoughts on how to test a test.
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The role of biomarkers for detection of sepsis has come a long way. Molecular biomarkers are taking front stage at present, but machine learning and other computational measures using bigdata sets are promising. ⋯ The final conclusion is expert opinion, which is not bad but not perfect. Perhaps machine learning will displace expert opinion as the final and most accurate definition for sepsis.