Characterizing and predicting progressive hemorrhagic injury: A problem with significant public health impact
Background: Progressive hemorrhagic injury (PHI) occurs in 20-60% of patients with severe traumatic brain injury (TBI) and is associated with worse outcomes including mortality. PHI pathophysiology remains poorly understood and is difficult to predict. We hypothesize that fibrinolysis is associated with PHI and that fibrinolytic markers may predict PHI. ^ Methods: A retrospective review of a cohort of highest-level activation adult polytrauma patients with prospectively collected data was performed. Severe TBI was defined by a Head Acute Injury Severity Score ≥3 and intracranial hemorrhage (ICH) on initial CT. In patients with TBI, stable hemorrhage (SH) and PHI was determined based on the absence or presence of ICH expansion on repeat CT within 6 hours, respectively. Demographic and clinical parameters were collected. Levels of fibrinolytic proteins, urokinase plasminogen activator (uPA), tissue plasminogen activator (tPA), plasminogen activator inhibitor (PAI-1), plasminogen (PLG), plasmin-antiplasmin (PAP), α2-antiplasmin (α2-AP), and d-dimer (DD), were determined from blood samples collected at 0, 2, 4, and 6 hours after admission. ^ Results: Twenty-five patients met inclusion criteria and were dichotomized into SH (n=6, 24%) and PHI (n=19, 76%) groups. There were no group differences in regards to demographics, injury severity scores, rapid thromboelastography parameters, or outcomes. Longitudinal analysis determined that collectively across time, tPA is positively associated while α2-AP is negatively associated with developing PHI (both p<0.05). Moreover, DD exhibits strong time-interactions, and higher levels were associated with higher likelihood of developing PHI. Receiver operating curve analysis determined 12,820 ng/mL of admission DD to be a cutoff level to differentiate SH from PHI patients. ^ Conclusion: Fibrinolysis is associated with PHI. DD may represent a readily available clinical biomarker for early prediction of PHI.^
Karri, Jay, "Characterizing and predicting progressive hemorrhagic injury: A problem with significant public health impact" (2016). Texas Medical Center Dissertations (via ProQuest). AAI10127466.