Tranexamic Acid Utilization in Foot and Ankle Surgery: A Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Tranexamic acid (TXA) has been widely used in various orthopaedic subspecialities to decrease blood loss, transfusions, and wound complications. However, the role of TXA in foot and ankle surgery is not clearly delineated. This meta-analysis aims to report the efficacy and safety of TXA in relation to foot and ankle surgical procedures. METHODS: Database searches were conducted for eligible studies from data inception through January 2022. Clinical studies on the use of TXA in foot and ankle procedures reporting the desired outcomes were included. Outcomes were estimated blood loss, change in hemoglobin, and overall complications. Risk of bias was assessed using the Newcastle-Ottawa quality assessment scale and the Joanna Briggs Institute (JBI) critical appraisal tool. RESULTS: Nine studies met the inclusion criteria. A total of 752 foot and ankle procedures were included, in which 511 (67.95%) procedures received TXA whereas 241 (32.05%) served as controls and did not receive TXA. The pooled data of change in hemoglobin and overall complications showed no difference between the TXA and control group. Estimated blood loss was significantly lower in the patients who received TXA. CONCLUSION: In conclusion, TXA use was associated with lower estimated blood loss in foot and ankle surgeries without increased risk of thromboembolic events, wound complications, or changes in hemoglobin. LEVEL OF EVIDENCE: Level IV, meta-analysis.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.039 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".