Enoxaparin Versus Dalteparin for Venous Thromboembolism Prophylaxis in Hip and Knee Arthroplasty: A Systematic Review
Bibliographic record
Abstract
Venous thromboembolism (VTE) is a serious postoperative complication in patients undergoing total hip or knee arthroplasty, with both pulmonary embolisms and deep vein thromboses being major causes of preventable morbidity and mortality. Low-molecular-weight heparins such as enoxaparin and dalteparin are widely used for thromboprophylaxis, but direct comparative data are limited. We aimed to do a systematic review of the literature to compare the efficacy and safety of enoxaparin and dalteparin in preventing VTE following total hip or knee replacement surgery. A systematic literature search was conducted in MEDLINE, PubMed, Embase, and the Cochrane Library. After deduplication, 145 studies were screened, 28 full texts were assessed, and three papers were included. Eligible studies were randomised controlled trials (RCTs) or observational studies comparing enoxaparin and dalteparin in adult patients undergoing hip or knee arthroplasty, reporting VTE rates as the primary outcome. Risk of bias (ROB) was assessed using the Cochrane RoB 2 tool for randomised trials and the Newcastle-Ottawa Scale for observational studies. Three studies - one RCT and two retrospective cohort studies with a total of 1,167 patients - met the inclusion criteria. Across all studies, VTE incidence was low with no significant difference between enoxaparin and dalteparin. Some evidence suggested dalteparin may be associated with fewer bleeding events and lower transfusion rates, with one study also reporting cost savings. ROB was moderate in the observational studies, with some concerns in the RCTs. Enoxaparin and dalteparin appear similarly effective for VTE prevention after hip or knee arthroplasty. However, dalteparin may be associated with a lower bleeding risk and reduced transfusion rates, with potential cost savings. Current evidence is limited by the small number and quality of studies. Further high-quality randomised trials are needed to confirm these findings and inform clinical decision-making.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".