Researchers have used machine learning to identify subgroups of trauma patients who are more likely to survive their injuries if treated with tranexamic acid. This treatment controls bleeding and thereby prevents death from hemorrhage. The team also identified subgroups of trauma patients who do not benefit from tranexamic acid.
These findings should help guide treatment decisions after traumatic injury and provide trauma patients with more personalized care.
"We identified eight different trauma phenotypes, and then we evaluated the benefits of tranexamic acid treatment based on these phenotypes," explains lead author Jotaro Tachino."We found subgroups of patients with significantly lower in-hospital mortality when they received tranexamic acid. We also found subgroups of patients who received no benefit from treatment."
The researchers say"Trauma patients are a heterogeneous population with injuries that vary greatly in type and severity. This makes it difficult to predict how effective a treatment will be in an individual patient.""We hope our results will help individual trauma patients receive more personalized care as well as improve the quality of care for all trauma patients."
Association between tranexamic acid administration and mortality based on the trauma phenotype: a retrospective analysis of a nationwide trauma registry in JapanResearchers use machine learning methods on a large dataset of trauma patients to determine the factors that correlate with survival, which may significantly improve triage and rapid treatment ...
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