The impact of tranexamic acid on perioperative outcomes in urological surgeries: A systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Tranexamic acid (TXA) is an antifibrinolytic agent widely used in surgery to decrease bleeding and reduce the need for blood product transfusion. The role of TXA in urology is not well-summarized. We conducted a systematic review of studies reporting outcomes of TXA use in urological surgery. METHODS: A comprehensive search was conducted from the following databases: PubMed, Embase, Cochrane Library, and Web of Science. Two reviewers performed title and abstract screening, full-text review, and data collection. Primary outcomes included estimated blood loss (EBL), decrease in hemoglobin, decrease in hematocrit, and blood transfusion rates. Secondary outcomes included TXA administration characteristics, length of stay, operative time, and postoperative thromboembolic events. RESULTS: A total of 26 studies consisting of 3261 patients were included in the final analysis. These included 11 studies on percutaneous nephrolithotomy, 10 on transurethral resection of prostate, three on prostatectomy, and one on cystectomy. EBL, transfusion rate, hemoglobin drop, operative time, and length of stay were significantly improved with TXA administration. In addition, the use of TXA was not associated with an increased risk of venous thromboembolism (VTE ). The route, dosage, and timing of TXA administration varied considerably between included studies. CONCLUSIONS: TXA use may improve blood loss, transfusion rates, and perioperative parameters in urological procedures. In addition, there is no increased risk of VTE associated with TXA use in urological surgery; however, there is still a need to determine the most effective TXA administration route and dose. This review provides evidence-based data for decision-making in urological surgery.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.006 | 0.008 |
| 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) | 0.003 | 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".