Patients with severe sepsis vary markedly in their ability to generate activated protein C
Bibliographic record
Abstract
Activated protein C (APC) supplementation significantly reduces mortality in patients with severe sepsis, presumably by down-regulating coagulation, inflammation, and apoptosis. In vivo, endogenous APC is generated from protein C (PC) "on demand" in response to elevated thrombin levels. Thrombomodulin and endothelial cell protein C receptor are endothelial receptors required to generate APC endogenously. Since these receptors may be down-regulated in sepsis, we measured plasma markers of APC generation in 32 patients with severe sepsis to determine whether APC generation is impaired and whether markers of APC generation correlate with 28-day mortality. Relative to normals, all patients had elevated F1 + 2 and thrombin-antithrombin complex (TAT) levels (markers of thrombin generation and inhibition, respectively), and 28 of 32 patients had reduced PC levels. In 20 patients, APC levels paralleled elevated F1 + 2 levels, whereas 12 patients had low APC levels despite elevated F1 + 2 levels, suggesting that APC generation is impaired in the latter. No significant differences exist between survivors and nonsurvivors with respect to baseline PC levels, F1 + 2 levels, and APACHE II (acute physiology and chronic health evaluation) scores. Baseline APC levels were higher in survivors (P = .024), and baseline F1 + 2/APC ratios were lower in survivors (P = .047). Larger studies are warranted to establish whether APC generation profiles aid in managing sepsis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".