Endogenous fibrinolysis—Relevance to clinical thrombosis risk assessment
Bibliographic record
Abstract
The development of an obstructive luminal thrombus is pathological and considered a failure of endogenous fibrinolysis. The consequences may be fatal, or result in lasting downstream organ damage. Therefore, assessment of endogenous fibrinolytic status in an individual may identify those at risk of occlusive thrombus formation and provide prognostic information. Arterial thrombi are more platelet rich and more resistant to fibrinolysis than venous thrombi. Several recent studies using global tests of fibrinolysis in patients with acute coronary syndromes (ACS) have shown that despite dual antiplatelet therapy, patients with impaired fibrinolytic status have an increased risk of adverse cardiovascular events, compared with those with effective fibrinolytic function. Such data add significantly to the predictive value of established cardiovascular risk factors and conventional biomarkers. Most data reported have been obtained with the Global Thrombosis Test and the turbidimetric plasma clot lysis assay. A few small studies in patients with ischaemic stroke suggest a similar predictive role of fibrinolytic status assessment in these patients. Studies reporting an association between impaired fibrinolysis and future venous thrombotic events are limited, and in the form of case-control studies. Viscoelastic assays may have a role in the prediction of venous thromboembolic risk. Assays of fibrinolytic function should be used to obtain a more accurate risk of future thrombotic events, particularly in the setting of ACS. The availability of point-of-care tests helps facilitate this and should encourage future studies to assess personalised antithrombotic treatment combinations to optimise fibrinolytic status and reduce thrombosis risk.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".