The tissue factor pathway in ischemic stroke
Bibliographic record
Abstract
To explore the role of the the tissue factor (TF) pathway in ischemic stroke. We measured blood concentrations of markers of the TF pathway [TF antigen, free tissue factor pathway inhibitor antigen (TFPIf) and activity (TFPIac), and activated factor VII (FVIIa)] within 7 days (acute phase) and after 3-6 months (convalescence) in 150 patients with first-ever ischemic stroke and 150 community controls. During the acute phase, TF antigen and TFPIf were not significantly altered but TFPIac was increased (mean 1.27 versus 1.13 U/ml, P = 0.04) and FVIIa was decreased in cases compared with controls (mean 43.3 versus 57.9 mU/ml, P = 0.0004). After adjusting for baseline differences between cases and controls, increasing quartiles of TFPIf were independently associated with reduced odds of stroke, and reducing quartiles of FVIIa and increasing quartiles of TFPIac with increased odds of stroke. During the convalescent phase, FVIIa and TFPIac returned to normal but TF antigen and TFPIf were significantly decreased compared with controls [median TF antigen, 110 (follow-up) versus 155 pg/ml (controls), P = 0.0008; median TFPIf, 15.5 (follow-up) versus 23.3 ng/ml (controls), P = 0.002]. Alterations of blood concentrations of TF pathway markers are common in patients with acute ischemic stroke. The mechanisms are unclear but may relate to enhanced formation of TF-FVIIa complexes and upregulation and release of TFPI during the acute phase, and ongoing consumption of TF antigen and TFPIf during the chronic phase as the atherosclerotic plaque heals.
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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 | 0.000 |
| 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) | 0.002 | 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".