A systematic review on the efficacy of tranexamic acid in head and neck surgery
Bibliographic record
Abstract
BACKGROUND: Intraoperative and postoperative blood loss is a major risk in head and neck (H&N) surgery. Recently the use of tranexamic acid (TXA) has been investigated by multiple studies for reducing intraoperative and postoperative bleeding, however reported results are variable. OBJECTIVES: To determine the safety and efficacy of TXA use in H&N surgery. METHODS: Systematic review of MEDLINE, EMBASE, CINAHL, Cochrane Library, PubMed, ClinicalKey, and Clinicaltrials.gov according to the PRISMA guidelines. Studies were included if they reported on intraoperative bleeding, volume or duration of postoperative drain or return to theatre rate for postoperative haemorrhage in adult populations following use of TXA. Risk of bias assessment with Cochrane Risk of Bias (RoB2) tool for randomised controlled trials and Newcastle-Ottawa Scale tool for non-randomised studies. RESULTS: Sixteen studies were identified (114 407 patients). Eight studies evaluated TXA in major H&N surgery and eight studies in tonsillectomy. Primary outcomes were reduction in intraoperative or postoperative bleeding. Secondary outcomes included the duration of postoperative drain placement and return to theatre rate. No adverse events were reported in any patients. TXA is effective in reducing intraoperative blood loss in tonsillectomy. However, the effect on posttonsillectomy haemorrhage was unclear. Insufficient evidence exists of benefit of TXA on intraoperative bleeding in major H&N procedures. Postoperative drainage volumes were significantly reduced in most major H&N studies. The duration of drain placement and risk of blood transfusion was unchanged in most cases. CONCLUSION: TXA use is safe in H&N patients. Whilst sufficient evidence exists to support the use of TXA in tonsillectomy, insufficient evidence exists to recommend use in major H&N surgery.
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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| 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) | 0.005 | 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".