Universal changes in biomarkers of coagulation and inflammation occur in patients with severe sepsis, regardless of causative micro-organism [ISRCTN74215569]
Bibliographic record
Abstract
INTRODUCTION: PROWESS (Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis) was a phase III, randomized, double blind, placebo controlled, multicenter trial conducted in patients with severe sepsis from 164 medical centers. Here we report data collected at study entry for 1690 patients and over the following 7 days for the 840 patients who received placebo (in addition to usual standard of care). METHODS: Nineteen biomarkers of coagulation activation, anticoagulation, fibrinolysis, endothelial injury, and inflammation were analyzed to determine the relationships between baseline values and their change over time, with 28-day survival, and type of infecting causative micro-organism. RESULTS: Levels of 13 of the 19 biomarkers at baseline correlated with Acute Physiology and Chronic Health Evaluation II scores, and nearly all patients exhibited coagulopathy, endothelial injury, and inflammation at baseline. At study entry, elevated D-dimer, thrombin-antithrombin complexes, IL-6, and prolonged prothrombin time were present in 99.7%, 95.5%, 98.5%, and 93.4% of patients, respectively. Markers of endothelial injury (soluble thrombomodulin) and deficient protein C, protein S, and antithrombin were apparent in 72%, 87.6%, 77.8%, and 81.7%, respectively. Impaired fibrinolysis (elevated plasminogen activator inhibitor-1) was observed in 44% of patients. During the first 7 days, increased prothrombin time (which is readily measurable in most clinical settings) was highly evident among patients who were not alive at 28 days. CONCLUSION: Abnormalities in biomarkers of inflammation and coagulation were related to disease severity and mortality outcome in patients with severe sepsis. Coagulopathy and inflammation were universal host responses to infection in patients with severe sepsis, which were similar across causative micro-organism groups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".