Researchers from Osaka University use machine learning to identify patients more likely to survive traumatic injury if treated with tranexamic acid.
Early treatment with a drug called tranexamic acid stops excessive bleeding by reducing the body’s ability to break down blood clots. However, tranexamic acid can cause unnecessary drug side effects in patients who do not need it, so it is necessary to select truly effective target patients based on objective criteria.
Now, in a study published in Critical Care, researchers from Osaka University have addressed this treatment challenge by identifying subgroups of trauma patients who are more likely to survive if treated with tranexamic acid. The team found these subgroups by examining trauma patients who shared similar traits (also known as phenotypes)
https://ccforum.biomedcentral.com/articles/10.1186/s13054-024-04871-w
