Results of rotational thromboelastometry, coagulation activation markers and thrombin generation assays in orthopedic patients during thromboprophylaxis with rivaroxaban and enoxaparin
Bibliographic record
Abstract
BACKGROUND: A prospective observational study was conducted in two clinical cohorts of patients to compare the effect of enoxaparin and rivaroxaban on rotational thromboelastometry (ROTEM), coagulation activation markers and thrombin generation. METHODS: A total of 188 consecutive patients scheduled for major orthopedic surgery receiving 40-mg enoxaparin subcutaneously or 10-mg rivaroxaban orally were evaluated. Blood samples were taken before induction of anesthesia and on day 4 after surgery [postoperative day 4 (pod 4)]. The extrinsically (EXTEM) and the intrinsically (INTEM) activated ROTEM assay, antithrombin, prothrombin fragments (F1 + 2), thrombin-antithrombin complex (TAT) and D-dimers were measured, and the thrombodynamic ratio (TDR) was calculated. Thrombin generation was determined using calibrated automated thrombography. To compare the groups, changes (Δ) in baseline versus pod 4 were calculated. RESULTS: EXTEM clotting time (CT) increased more with rivaroxaban than with enoxaparin; values above the reference range were observed (median ΔEXTEM-CT 15 vs. 5 s, P ≤ 0.0001). The increase in INTEM-CT (values remained within the normal ranges) was slight with enoxaparin and significant with rivaroxaban; ΔINTEM-CT was comparable. EXTEM-TDR, unchanged with rivaroxaban, increased significantly with enoxaparin, whereas ΔINTEM-TDR was comparable. ΔAT, ΔF1 + 2 and ΔTAT were significantly lower in the rivaroxaban group. Endogenous thrombin potential (ETP), unchanged with rivaroxaban, decreased significantly with enoxaparin; the maximal rising slope (mean velocity rate index) decreased more with rivaroxaban. CONCLUSION: Data show that prolonged CT in the extrinsic ROTEM and thrombin generation assays reflecting initiation and propagation of thrombin may be useful for detecting treatment with rivaroxaban. The significance of observed differences in markers of coagulation needs to be investigated further.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".