Sepsis-Induced Coagulopathy Phenotype Induced by Oxidized High-Density Lipoprotein Associated with Increased Mortality in Septic-Shock Patients
Bibliographic record
Abstract
Sepsis syndrome is a highly lethal uncontrolled response to an infection, which is characterized by sepsis-induced coagulopathy (SIC). High-density lipoprotein (HDL) exhibits antithrombotic activity, regulating coagulation in vascular endothelial cells. Sepsis induces the release of several proinflammatory molecules, including reactive oxygen species, which lead to an increase in oxidative stress in blood vessels. Thus, circulating lipoproteins, such as HDL, are oxidized to oxHDL, which promotes hemostatic dysfunction, acquiring prothrombotic properties linked to the severity of organ failure in septic-shock patients (SSP). However, a rigorous and comprehensive investigation demonstrating that oxHDL is associated with a coagulopathy-associated deleterious outcome of SSP, has not been reported. Thus, we investigated the participation of plasma oxHDL in coagulopathy-associated sepsis pathogenesis and elucidated the underlying molecular mechanism. A prospective study was conducted on 42 patients admitted to intensive care units, (26 SSP and 16 non-SSP) and 39 healthy volunteers. We found that an increased plasma oxHDL level in SSP was associated with a prothrombotic phenotype, increased mortality and elevated risk of death, which predicts mortality in SSP. The underlying mechanism indicates that oxHDL triggers an endothelial protein expression reprogramming of coagulation factors and procoagulant adhesion proteins, to produce a prothrombotic environment, mainly mediated by the endothelial LOX-1 receptor. Our study demonstrates that an increased plasma oxHDL level is associated with coagulopathy in SSP through a mechanism involving the endothelial LOX-1 receptor and endothelial protein expression regulation. Therefore, the plasma oxHDL level plays a role in the molecular mechanism associated with increased mortality in SSP.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".