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CC BY 4.0 · Thromb Haemost
DOI: 10.1055/a-2806-3484
Original Article: Coagulation and Fibrinolysis

Approach to Optimizing Tranexamic Acid Use in Trauma: Potential Utilization of Trauma Phenotypes

Autor*innen

  • Jotaro Tachino 

    1   Department of Traumatology and Acute Critical Medicine, Graduate School of Medicine, The University of Osaka, Suita City, Osaka, Japan

  • Shunichiro Nakao

    1   Department of Traumatology and Acute Critical Medicine, Graduate School of Medicine, The University of Osaka, Suita City, Osaka, Japan

  • Hisatake Matsumoto

    1   Department of Traumatology and Acute Critical Medicine, Graduate School of Medicine, The University of Osaka, Suita City, Osaka, Japan

  • Yusuke Katayama

    1   Department of Traumatology and Acute Critical Medicine, Graduate School of Medicine, The University of Osaka, Suita City, Osaka, Japan

  • Tetsuhisa Kitamura

    2   Division of Environmental Medicine and Population Sciences, Department of Social and Environmental Medicine, Graduate School of Medicine, The University of Osaka, Suita City, Osaka, Japan

  • Shigeto Seno

    3   Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, The University of Osaka, Suita City, Osaka, Japan

  • Jun Oda

    1   Department of Traumatology and Acute Critical Medicine, Graduate School of Medicine, The University of Osaka, Suita City, Osaka, Japan

Funding Information This study was supported by JSPS KAKENHI (grant number 23K15629) and the Takeda Science Foundation (grant number 2024045547).
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Graphical Abstract

Abstract

Background

Tranexamic acid (TXA) reduces mortality in patients with trauma; however, optimal patient selection remains unclear. This study aimed to identify trauma subgroups most likely to benefit from TXA administration by integrating systematic evidence mapping with trauma phenotype analysis derived from the Japan Trauma Data Bank.

Methods

We conducted a two-phase study: first, a systematic search of MEDLINE, Web of Science, and the Cochrane Library databases (inception to June 28, 2024) and identified randomized controlled trials (RCTs) evaluating TXA in trauma; second, we assessed TXA's association with mortality across phenotypes derived through machine learning–based clustering using 14 variables available during initial trauma care. Among eligible studies, control group mortality and number needed to treat (NNT) were calculated and visualized via bubble plots (size = sample size).

Results

Five RCTs (n = 894–20,127; published 2010–2023) and one phenotype study (n = 24,058; four phenotypes) were included, all reporting mortality as an outcome. At approximately 1 month post-injury, control group mortality in RCTs ranged from 10 to 21.8%, whereas in-hospital mortality across phenotypes ranged from 3.9 to 51.4%. NNT varied from 22 to 68 (RCTs) and from 10 to 98 (phenotype study), with an inverse relationship between baseline mortality and NNT, indicating greater TXA benefit in higher-risk groups.

Conclusion

This study suggests that TXA is more effective in trauma subgroups with higher baseline mortality. Phenotype-driven stratification using initial clinical data may support more targeted TXA administration and improve patient outcomes. Further research is needed to validate these phenotypes for clinical implementation.

Keywords

tranexamic acid - trauma phenotypes - machine learning - precision medicine

Data Availability Statement

The RCT data used in the systematic analysis were obtained from publicly available published literature and can be accessed through the original publications. The datasets related to the Japan Trauma Data Bank that were used and/or analyzed in the current study are not publicly available but can be obtained from the corresponding authors upon reasonable request.


Supplementary Material



Publikationsverlauf

Eingereicht: 14. Juli 2025

Angenommen nach Revision: 04. Februar 2026

Artikel online veröffentlicht:
16. Februar 2026

© 2026. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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