Title |
Development and validation of a novel molecular biomarker diagnostic test for the early detection of sepsis
|
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Published in |
Critical Care, June 2011
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DOI | 10.1186/cc10274 |
Pubmed ID | |
Authors |
Allison Sutherland, Mervyn Thomas, Roslyn A Brandon, Richard B Brandon, Jeffrey Lipman, Benjamin Tang, Anthony McLean, Ranald Pascoe, Gareth Price, Thu Nguyen, Glenn Stone, Deon Venter |
Abstract |
Sepsis is a complex immunological response to infection characterized by early hyper-inflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on Systemic Inflammatory Response Syndrome (SIRS) differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 2 | <1% |
Norway | 1 | <1% |
Australia | 1 | <1% |
Brazil | 1 | <1% |
United Kingdom | 1 | <1% |
Canada | 1 | <1% |
United States | 1 | <1% |
Unknown | 195 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 39 | 19% |
Student > Ph. D. Student | 31 | 15% |
Student > Master | 24 | 12% |
Other | 14 | 7% |
Professor | 13 | 6% |
Other | 40 | 20% |
Unknown | 42 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 71 | 35% |
Agricultural and Biological Sciences | 32 | 16% |
Biochemistry, Genetics and Molecular Biology | 10 | 5% |
Computer Science | 7 | 3% |
Immunology and Microbiology | 7 | 3% |
Other | 26 | 13% |
Unknown | 50 | 25% |