Injury Severity is a Key Contributor to Coagulation Dysregulation and Fibrinogen Consumption.

BACKGROUND

Traumatic injury is a leading cause of death for those under the age of 45, with 40% occurring due to hemorrhage. Severe tissue injury and hypoperfusion lead to marked changes in coagulation, thereby preventing formation of a stable blood clot and increasing hemorrhage associated mortality.

OBJECTIVES

We aimed to quantify changes in clot formation and mechanics occurring after traumatic injury and the relationship to coagulation kinetics, and fibrinolysis.

METHODS

Plasma was isolated from injured patients upon arrival to the emergency department. Coagulation kinetics and mechanics of healthy donors and patient plasma were compared with rheological, turbidimetric and thrombin generation assays. ELISA's were performed to determine tissue plasminogen activator (tPA) and D-dimer concentration, as fibrinolytic markers.

RESULTS

Sixty-three patients were included in the study. The median injury severity score (ISS) was 17, median age was 37.5 years old, and mortality rate was 30%. Rheological, turbidimetric and thrombin generation assays indicated that trauma patients on average, and especially deceased patients, exhibited reduced clot stiffness, increased fibrinolysis and reduced thrombin generation compared to healthy donors. Fibrinogen concentration, clot stiffness, D-dimer and tPA all demonstrated significant direct correlation to increasing ISS. Machine learning algorithms identified and highlighted the importance of clinical factors on determining patient outcomes.

CONCLUSIONS

Viscoelastic and biochemical assays indicate significant contributors and predictors of mortality for improved patient treatment and therapeutic target detection.

ESSENTIALS

Traumatic injury may lead to alterations in a patient's ability to form stable blood clotsA study was performed to assess how trauma severity affects coagulation kineticsKey alterations were observed in trauma patients, who exhibit weaker and slower forming clotsPaired with machine learning methods, the results indicate key aspects contributing to mortality.