Review: Laboratory markers quantifying prothrombin activation and actions of thrombin in venous and arterial thrombosis do not accurately assess disease severity or the effectiveness of treatment
Bibliographic record
Abstract
Thrombin is normally produced for hemostasis and physiological wound healing. Increased thrombin production in vivo, cell activation and inflammation mediated in part by thrombin are hallmarks of both arterial and venous thrombosis. Thrombin generates (pro) coagulant, mitogenic, inflammatory and anticoagulant responses by interacting with a variety of cells in vivo. Both direct and indirect thrombin inhibitors are effective drugs for preventing and treating the consequences of arterial and venous thrombosis. For these reasons, measurements of the production and activities of thrombin in vivo have the potential for gauging the extent of thromboembolism and the responses of patients to anticoagulant, antiplatelet and anti-inflammatory drugs. However, a critical review of published information suggests that measurement of thrombin production and activity in patients at risk for and in patients with significant thrombosis generally does not provide information useful for clinical decision-making. This lack of clinical utility of levels of thrombin production in vivo may arise from two causes: the inability of the measurement to differentiate between physiological (hemostatic) and disease-related (pathological) sources and/or causes of thrombin productio n in vivo, and the inability of antithrombotic treatment modalities to permanently eliminate the stimuli that cause increased thrombin production evident in venous and arterial thrombosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.009 |
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".