Tranexamic acid for prevention of bleeding in cesarean delivery: An overview of systematic reviews
Bibliographic record
Abstract
BACKGROUND: Bleeding is the leading cause of maternal mortality in the world. Tranexamic acid reduces bleeding in trauma and surgery. Several systematic reviews of randomized trials have investigated tranexamic acid in the prevention of bleeding in cesarean delivery. However, the conclusions from systematic reviews are conflicting. This overview aims to summarize the evidence and explore the reasons for conflicting conclusions across the systematic reviews. METHODS: A comprehensive literature search of Medline, Embase, and Cochrane Database of Systematic Reviews was conducted from inception to April 2021. Screening, data extraction, and quality assessments were performed by two independent reviewers. A Measurement Tool to Assess Reviews 2 and the Risk of Bias Assessment Tool for Systematic Reviews were used for study appraisal. A qualitative synthesis of evidence is presented. RESULTS: In all, 14 systematic reviews were included in our analysis. Across these reviews, there were 32 relevant randomized trials. A modest reduction in blood transfusions and bleeding outcomes was found by most systematic reviews. Overall confidence in results varied from low to critically low. All of the included systematic reviews were at high risk of bias. Quality of evidence from randomized trials was uncertain. CONCLUSIONS: Systematic reviews investigating prophylactic tranexamic acid in cesarean delivery are heterogeneous in terms of methodological and reporting quality. Tranexamic acid may reduce blood transfusion and bleeding outcomes, but rigorous well-designed research is needed due to the limitations of the included studies. Data on safety and adverse effects are insufficient to draw conclusions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".