Impact of venous thromboembolism on clinical management and therapy after hip and knee arthroplasty
Bibliographic record
Abstract
Postoperative deep vein thrombosis (DVT) occurs most often in the large veins of the legs in patients undergoing major joint arthroplasty and major surgical procedures. These patients remain at high risk for venous thromboembolic events. In patients undergoing total hip or total knee arthroplasty (THA or TKA, respectively), different patterns of altered venous hemodynamics and hypercoagulability have been found, thus the rate of distal DVT is higher than that of proximal DVT after TKA. In addition, symptomatic venous thromboembolism (VTE) occurs earlier after TKA than THA; however, most of those events occur after hospital discharge. Consequently, extended thromboprophylaxis after discharge should be considered and is particularly important after THA owing to the prolonged risk period for VTE. Evidence-based guideline recommendations for the prevention of VTE in these patients have not been fully implemented. This is partly owing to the limitations of traditional anticoagulants, such as the parenteral route of administration or frequent coagulation monitoring and dose adjustment, as well as concerns about bleeding risks. The introduction of new oral agents (e.g., dabigatran etexilate and rivaroxaban) may facilitate guideline adherence, particularly in the outpatient setting, owing to their oral administration without the need for routine coagulation monitoring. Furthermore, the direct Factor Xa inhibitor rivaroxaban has been shown to be more effective than enoxaparin in preventing VTE.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".