Exploring the Impact of Clinical Anticoagulants on Venous Thrombosis Stability Using a Novel Intravital Murine Model
Bibliographic record
Abstract
Abstract Abstract 1246 Background: Thrombus stability influences the progression of deep vein thrombosis to a potentially fatal pulmonary embolism (PE) event. Anticoagulants are clinically administered to treat venous thrombosis. However, the effect of anticoagulants on thrombus stability remains unknown. Objective: We developed a novel intravital mouse model to explore the hypothesis that administration of clinical anticoagulants would decrease early thrombus stability, thereby potentially increasing PE risk. Methods: The trachea and jugular vein were cannulated, and the femoral vein isolated, in wild type C57/Bl6 female mice. Platelets were labeled in vivo using anti-mouse CD41 Fab fragments conjugated to Alexa Fluor-488. A 1 × 2 mm filter paper strip, saturated in 4% ferric chloride, was applied to the femoral vein for 5 minutes to induce thrombus formation. Wide-field fluorescent microscopy was used to quantify thrombus stability. Stability was related to the number of embolic events and loss of platelet intensity captured downstream of the thrombus at 5, 15, 30, 45, and 60 minutes post thrombus formation. Results: The mean number of embolic events and loss of platelet intensity decreased over time in wild type mice (n = 12). This suggested that thrombus stability increases over time. Anticoagulants were administered via a jugular vein catheter, at 12 minutes post thrombus formation, to assess impact on embolization. The anticoagulants examined were hirudin (8U/g mouse body weight), unfractionated heparin (UFH) (0.1U/g), a covalent antithrombin-heparin complex (ATH) (0.08U/g), and fondaparinux (0.1μg/g). We observed an overall a) increase in the number of embolic events and b) increase in platelet intensity lost over time in mice injected with hirudin (n = 12) and UFH (n = 12) when compared to untreated wild type control mice. The total number of embolic events occurring over one hour substantially increased in the hirudin-treated group (p = 0.09), which was also associated with an overall increase in total platelet intensity (p = 0.08), compared to untreated control mice. In addition, there was an increase in the total number of embolic events compared to the UFH-treated group (p = 0.09). Administration of hirudin, a direct thrombin inhibitor (DTI), and UFH, an indirect thrombin inhibitor, could result in decreased venous thrombus stability. However, it appears that the DTI is associated with greater thrombus instability. In the ATH-treated group (n = 12), an increase in embolic events at 15 minutes was observed, followed by a decrease in embolization. ATH could initially disrupt thrombus stability through inhibition of fibrin-bound thrombin, before acting in a stabilizing manner. Administration of fondaparinux (n = 6), an indirect factor-Xa inhibitor, demonstrated an overall decrease in embolic events and platelet intensity lost over time. When compared to control groups, there was a significant decrease in total number of embolic events and total amount of platelet intensity lost in the fondaparinux group (p < 0.05). Use of a factor-Xa inhibitor appears to enhance thrombus stability more effectively in comparison to direct and indirect thrombin inhibitors. Conclusion: Use of anticoagulants that inhibit thrombin predominantly could decrease early thrombus stability and potentially increase the likelihood of a PE event. Disclosures: No relevant conflicts of interest to declare.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".