Endotoxin and Cytokine Removal in Sepsis
Bibliographic record
Abstract
Sepsis, the leading cause of mortality in intensive care units, is a complex series of interrelated effects caused by the overproduction of multiple mediators and their unrestrained biological activity. Both proinflammatory and antiinflammatory mediators participate in the high complexity of sepsis and explain the failure of specific therapies to improve survival. Continuous extracorporeal therapies have been proposed as therapeutic options and as tools for blood purification in sepsis. Along these lines and in order to achieve higher clearances and mass removal rates, we studied the effects of plasmafiltration coupled with adsorption and provided in vitro and in vivo evidence that adsoprtion of multiple cytokines, activated complement components, and lipid mediators such as the platelet-activating factor occurs. We also showed that such treatment may lead to improved survival in a rabbit model of sepsis and to improved hemodynamics, reduced norepinephrine dose, and restoration of near-to-normal responsiveness of blood leukocytes to endotoxin in humans. It is anticipated that treatment of plasma, as a modular device to conventional hemofiltration, may pave the way to innovative approaches in the extracorporeal treatment of septic patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".