Background: Acute traumatic coagulopathy (ATC) is a syndrome of early, endogenous clotting dysfunction that afflicts up to 30% of severely injured patients, signaling an increased likelihood of all-cause and hemorrhage-associated mortality. To aid identification of patients within the likely therapeutic window for ATC and facilitate study of its mechanisms and targeted treatment, we developed and validated a prehospital ATC prediction model.
Methods: Construction of a parsimonious multivariable logistic regression model predicting ATC - defined as an admission international normalized ratio >1.5 - employed data from 1963 severely injured patients admitted to an Oregon trauma system hospital between 2008 and 2012 who received prehospital care but did not have isolated head injury. The prediction model was validated using data from 285 severely injured patients admitted to a level 1 trauma center in Seattle, WA, USA between 2009 and 2013.
Results: The final Prediction of Acute Coagulopathy of Trauma (PACT) score incorporated age, injury mechanism, prehospital shock index and Glasgow Coma Score values, and prehospital cardiopulmonary resuscitation and endotracheal intubation. In the validation cohort, the PACT score demonstrated better discrimination (area under the receiver operating characteristic curve 0.80 vs. 0.70, p = 0.032) and likely improved calibration compared to a previously published prehospital ATC prediction score. Designating PACT scores ≥196 as positive resulted in sensitivity and specificity for ATC of 73% and 74%, respectively.
Conclusions: Our prediction model uses routinely available and objective prehospital data to identify patients at increased risk of ATC. The PACT score could facilitate subject selection for studies of targeted treatment of ATC.
Keywords: Acute traumatic coagulopathy; Massive transfusion; Post-traumatic coagulopathy; Prediction model; Prediction score; Prehospital; Risk stratification; Trauma.