Tranexamic acid in endoscopic sinus and skull base surgery: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: Endoscopic sinus surgery (ESS) and endoscopic skull base surgery (ESBS) approaches have revolutionized the management of sinonasal and intracranial pathology. Maintaining surgical hemostasis is essential as bleeding can obscure the visibility of the surgical field, thus increasing surgical duration, risk of complications, and procedural failure. Tranexamic acid (TXA) acts to reduce bleeding by inhibiting fibrin degradation. This review aims to assess whether TXA improves surgical field quality and reduces intraoperative blood loss compared with control. METHODS: We searched PubMed, MEDLINE, Embase, Web of Science, and Cochrane Library from inception until September 1, 2022. Two reviewers independently screened citations, extracted data, and assessed methodological quality using the Cochrane risk-of-bias tool for randomized trials. Data were pooled using a random-effect model, with continuous data presented as mean differences and dichotomous data presented as odds ratios. RESULTS: Seventeen ESS randomized controlled trials (n = 1377) and one ESBS randomized controlled trial (n = 50) were reviewed. Significant improvement in surgical field quality was achieved with both systemic TXA (six studies, p < 0.00001) and topical TXA (six studies, p = 0.01) compared with the control. Systemic TXA (eight studies) and topical TXA (three studies) both achieved a significant reduction in intraoperative blood loss compared with the control (p < 0.00001). There were significant differences in operative times (p < 0.001) but no significant difference in perioperative outcomes (p = 0.30). CONCLUSION: This meta-analysis demonstrated that the administration of TXA in ESS can improve surgical field quality and reduce intraoperative blood loss. TXA use did not result in increased perioperative complications including thrombotic events.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.024 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".