Systemic vs. in-irrigation tranexamic acid in percutaneous nephrolithotomy
Bibliographic record
Abstract
INTRODUCTION: Percutaneous nephrolithotomy (PCNL) is the gold-standard treatment for large renal stones. One potentially significant complication of PCNL is blood loss, which can result in transfusion requirement and poorer stone-free outcomes. Tranexamic acid (TXA) has emerged as a promising intervention, administered systemically (TXA-S) or as part of irrigation fluid (TXA-I) in endourology. This study aimed to comprehensively analyze existing evidence regarding the applications of TXA in PCNL through a Bayesian network meta-analysis, offering insights into its efficacy and comparative effectiveness. METHODS: In February 2022, a PRISMA-compliant systematic review (PROSPERO registration number CRD 42021270593) was performed to identify randomized controlled clinical trials (RCT) on TXA as either systemic therapy or in irrigation fluid. Studies in languages other than English and Spanish were not considered. A Bayesian network was built using results from identified studies to create models that were later run through Markov Chain Monte Carlo sampling through 200 000 iterations. RESULTS: Eight RCTs compared TXA-S vs. placebo, one TXA-I vs. placebo, and one TXA-I vs. TXA-S. TXA-I had lower risk of transfusion (relative risk [RR] 0.63 [0.47,0.84], SUCRA 0.950) than TXA-S (RR 0.79 [0.65,0.95], SUCRA 0.545). TXA-I had a lower risk of complications (RR 0.38 [0.21,0.67], SUCRA=0.957) compared to TXA-S (RR 0.55 [0.39, 0.78], SUCRA 0.539). TXA-I had a lower postoperative decrease in hemoglobin (mean difference [MD] -1.2 [1.3, 1.0], SUCRA 0.849) compared to TXA-S (MD -0.97 [-1.0, -0.93], SUCRA 0.646]). CONCLUSIONS: TXA, regardless of the route of administration, is an effective intervention in decreasing bleeding, postoperative complications, and risk of transfusion when compared with placebo. Further studies directly comparing TXA-S to TXA-I would be useful to determine the optimal route of delivery.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".