Aspirin Versus <scp>LMWH</scp> for Thromboprophylaxis Following Hip or Knee Arthroplasty—Clinical Implications and Budget Impact
Bibliographic record
Abstract
Venous thromboembolism (VTE) remains a significant concern for patients undergoing hip or knee arthroplasty, with a need to balance effective thromboprophylaxis and bleeding risk. We aimed to compare the efficacy, safety, and budget impact of aspirin versus low-molecular-weight heparin (LMWH) as sole thromboprophylactic agents initiated immediately postoperatively in this population. First, we conducted a systematic review of randomized controlled trials (RCTs) from Ovid MEDLINE, Embase, and Cochrane CENTRAL databases, assessing clinical outcomes and healthcare costs. Subsequently, a simplified budget impact analysis was performed using data from the largest identified and most recent RCT (CRISTAL trial) and its secondary analyses. Primary outcomes included symptomatic VTE, bleeding events, and reoperation rates. Through a systematic search, seven RCTs were considered to be eligible, with the CRISTAL trial providing the most compelling evidence. Aspirin was non-inferior to LMWH for all-cause mortality but was associated with a significantly higher symptomatic VTE rate (3,27% vs. 1,76%) and deep vein thrombosis (DVT), predominantly distal DVT. The budget impact analysis revealed that despite aspirin's lower per tablet cost, thromboprophylaxis with LMWH led to annual savings of $35,912,459 to $110,431,241 for U.S. healthcare stakeholders, and $17,075 to $56,450 for single hospitals performing 1000 arthroplasty procedures annually. To conclude, enoxaparin appears to offer superior clinical efficacy and cost-effectiveness compared to aspirin for thromboprophylaxis following hip and knee arthroplasty. These findings support the preferential use of LMWH in this setting, while highlighting the need for further investigation into the clinical significance of aspirin's higher distal DVT and pulmonary embolism 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 | 0.015 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".