Background: Trauma is a heterogeneous condition, and specific clinical phenotypes may identify target populations that could benefit from certain treatment strategies. In this retrospective study, we determined clinical phenotypes and identified new target populations of trauma patients and their treatment strategies.
Methods: We retrospectively analyzed datasets from the Japan Trauma Data Bank and determined trauma death clinical phenotypes using statistical machine learning techniques and evaluation of biological profiles.
Results: The analysis included 71,038 blunt trauma patients [median age, 63 (interquartile range [IQR], 40-78) years; 45,479 (64.0%) males; median Injury Severity Score, 13 (IQR, 9-20)], and the derivation and validation cohorts included 42,780 (60.2%) and 28,258 (39.8%) patients, respectively. Of eight derived phenotypes (D-1-D-8), D-8 (n = 2178) had the highest mortality (48.6%) with characteristic severely disturbed consciousness and was further divided into four phenotypes: D-8α, multiple trauma in the young (n = 464); D-8β, head trauma with lower body temperature (n = 178); D-8γ, severe head injury in the elderly (n = 957); and D-8δ, multiple trauma, with higher predicted mortality than actual mortality (n = 579). Phenotype distributions were comparable in the validation cohort. Biological profile analysis of 90 trauma patients revealed that D-8 exhibited excessive inflammation, including enhanced acute inflammatory response, dysregulated complement activation pathways, and impaired coagulation, including downregulated coagulation and platelet degranulation pathways, compared with other phenotypes.
Conclusions: We identified clinical phenotypes with high mortality, and the evaluation of the molecular pathogenesis underlying these clinical phenotypes suggests that lethal trauma may involve excessive inflammation and coagulation disorders.
Keywords: Inflammatory response; Personalized medicine; Phenotype; Trauma.
© 2022. The Author(s).