Topical Versus Systemic Tranexamic Acid to Reduce Blood Loss After Total Knee and Total Hip Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Tranexamic acid (TXA) has been shown to reduce blood loss during total knee arthroplasty (TKA) and total hip arthroplasty (THA), but the most effective administration method has yet to be determined. This systematic review and meta-analysis aimed to compare topical and systemic TXA administration to reduce operative blood loss. METHODS: MEDLINE, Embase, and Cochrane CENTRAL were screened for randomized controlled trials comparing topical and systemic TXA for patients who underwent elective TKA and THA. The primary outcome was the total volume of operative blood loss, and the secondary outcomes were postoperative transfusion requirements, hemoglobin drop, hospital length of stay, and the frequencies of the main adverse events (infections and thromboembolic events). Data pooling was performed using RStudio. Subgroup analyses compared outcomes between TKA and THA. RESULTS: Fifty-nine randomized controlled trials with a total of 6,791 patients were included in this review. Data analysis showed no significant difference between topical and systemic TXA application in terms of total blood loss (Hedges g = 0.11; 95% confidence interval [CI], -0.04 to 0.26; I 2 = 82.4%). There was also no significant difference between the 2 groups in hemoglobin drop, hospital length of stay, and transfusion requirements. Subgroup analysis showed that patients undergoing TKA who received topical TXA had a significant reduction in total blood loss (g = 0.19; 95% CI, 0.00 to 0.38; I 2 = 85%; p = 0.046) compared with those who received systemic TXA. CONCLUSIONS: Topical and systemic TXA were equally effective in reducing blood loss in the analysis in which THA and TKA were combined. However, in TKA, topical application significantly reduced blood loss compared with systemic administration, while the reverse was true in THA. Further research is still necessary to find the optimal TXA dosage and administration route. LEVEL OF EVIDENCE: Therapeutic Level I . See Instructions for Authors for a complete description of levels of evidence.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.012 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".