Exclusion criteria and adverse events in perioperative trials of tranexamic acid: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Tranexamic acid (TXA) is an inexpensive therapy effective at minimizing perioperative blood loss and transfusion. However, it remains underutilized due to safety concerns. To date, no evidence-based guidelines exist identifying which patients should not receive TXA therapy. This study determined patient groups for whom safety information regarding TXA is lacking due to common exclusion from perioperative TXA trials. STUDY DESIGN AND METHODS: A systematic review searching the databases Medline, EMBASE, CENTRAL, and Clinicaltrials.gov was performed. Randomized controlled trials (RCTs) administering systemic TXA perioperatively to elective or emergent surgery patients were eligible. Our primary outcome was to describe exclusion criteria of RCTs, and the secondary outcome was TXA safety. A descriptive synthesis of exclusion criteria was performed, and TXA safety was assessed by meta-analysis. RESULTS: A total of 268 eligible RCTs were included. Meta-analysis showed that systemic TXA did not increase risk of adverse events compared to placebo or no intervention (relative risk, 1.05; 95% confidence interval, 0.99-1.12). Patient groups commonly excluded from perioperative TXA trials, and thus potentially lacking TXA safety data, were those with major comorbidities, a history of thromboembolism, medication use affecting coagulation, TXA allergy, and coagulopathy. Exclusion of patients with major comorbidities may not be necessary; we showed that the risk of adverse events was similar in studies that excluded patients with major comorbidities and those that did not. CONCLUSION: Sufficient evidence exists to develop perioperative guidelines for TXA use in many populations. Further studies evaluating perioperative TXA use in patients with a history of thromboembolism are warranted.
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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 | 0.039 | 0.096 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.043 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".