Evidence map›Paper›PMID 39076261›Full record

SynthesisReviews in cardiovascular medicine2023

Intravenous Tranexamic Acid Reduces Post-Operative Bleeding and Blood Transfusion in Patients Undergoing Aortic Surgery: A PRISMA-Compliant Systematic Review and Meta-Analysis.

Bo Zhang, Li-Xian He, Yun-Tai Yao, Evidence in Cardiovascular Anesthesia (EICA) Group

Abstract readSystematic Review
In one paragraph

Synthesis in Reviews in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Bo ZhangDepartment of Anesthesiology, Tianjin Union Medical Center, 300121 Tianjin, China.
Li-Xian HeDepartment of Anesthesiology, Fuwai Yunnan Cardiovascular Hospital, 650000 Kunming, Yunnan, China.
Yun-Tai YaoDepartment of Anesthesiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, 100037 Beijing, China.
Evidence in Cardiovascular Anesthesia (EICA) Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tranexamic acid (TXA), an antifibrinolytic agent, has been demonstrated to reduce blood loss and transfusion requirements in both cardiac and non-cardiac surgery. However, the evidence regarding the efficacy of intravenous TXA in aortic surgery has been seldomly analyzed. Therefore, the current study was performed to address this question. Methods: Searches of PubMed, EMBASE, OVID, Cochrane Library and CNKI were conducted comprehensively for randomized controlled trials (RCTs) comparing intravenous TXA versus no-TXA. Independently and in duplicate, we reviewed titles, abstracts and full-text articles, extracted data and evaluated bias risks. A random effect or fixed effect model was utilized to pool data. Results: The database search yielded 4 RCTs involving 273 patients. Meta-analysis revealed that, there was a significant reduction in bleeding volume within the first 4 hours post-operatively [(weighted mean difference (WMD) = -74.33; 95% confidence interval (CI): -133.55 to -15.11; Conclusions: The current study preliminarily demonstrated that, TXA significantly reduced postoperative bleeding, blood transfusion requirements and postoperative complications among patients undergoing aortic surgery. More well-designed studies are warrant to confirm the efficacy and safety of intravenous TXA in patients undergoing aortic surgery.

Indexed as

aortic surgerypost-operative bleedingtranexamic acid

Identifiers

PMID39076261
PMCPMC11273041

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.