Coagulopathy in patients with traumatic brain injury is associated with an increase in morbidity and mortality. Although timely and aggressive treatment of coagulopathy is of paramount importance, excessive transfusion of blood products has been linked with poor long-term outcomes in patients with traumatic brain injury. A pointof-care thromboelastometric-guided algorithm could assist in creating a more individually tailored approach to each patient. The aim of this study was to evaluate the feasibility of implementing a thromboelastometricguided algorithm in centres that were formerly na€ ıve to thromboelastometry. Hence, we developed such an algorithm and provided training to four centres across Europe to direct the haemostatic management of patients with severe traumatic brain injury. The primary outcome was adherence to the algorithm and timing of the availability of relevant results. Thirty-two patients were included in the study. Complete adherence to the algorithm was observed in 20 out of 32 cases. The availability of thromboelastometric results after hospital admission was reported significantly earlier than conventional coagulation tests (median (IQR [range]) 33 (20-40 [14-250]) min vs. 71 (51-101 [32-290]) min; p = 0.037). Although only 5 out of 32 patients had abnormalities of conventional coagulation tests, 21 out of 32 patients had a coagulopathic baseline thromboelastometric trace. Implementing a thromboelastometric-guided algorithm for the haemostatic therapy of traumatic brain injury is feasible in centres formerly na€ ıve to this technology and may lead to more rapid and precise coagulation management. Further large-scale studies are warranted to confirm the results of this pilot trial and evaluate clinical outcomes.

Background Trauma-induced coagulopathy in patients with traumatic brain injury (TBI) is associated with high rates of complications, unfavourable outcomes and mortality. The mechanism of the development of TBI-associated coagulopathy is poorly understood. Methods This analysis, embedded in the prospective, multi-centred, observational Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, aimed to characterise the coagulopathy of TBI. Emphasis was placed on the acute phase following TBI, primary on subgroups of patients with abnormal coagulation profile within 4 h of admission, and the impact of pre-injury anticoagulant and/or antiplatelet therapy. In order to minimise confounding factors, patients with isolated TBI (iTBI) (n = 598) were selected for this analysis. Results Haemostatic disorders were observed in approximately 20% of iTBI patients. In a subgroup analysis, patients with pre-injury anticoagulant and/or antiplatelet therapy had a twice exacerbated coagulation profile as likely as those without premedication. This was in turn associated with increased rates of mortality and unfavourable outcome post-injury. A multivariate analysis of iTBI patients without pre-injury anticoagulant therapy identified several independent risk factors for coagulopathy which were present at hospital admission. Glasgow Coma Scale (GCS) less than or equal to 8, base excess (BE) less than or equal to − 6, hypothermia and hypotension increased risk significantly. Conclusion Consideration of these factors enables early prediction and risk stratification of acute coagulopathy after TBI, thus guiding clinical management.

Fig. 1. Study inclusion and exclusion process. Diagram demonstrating the inclusion and exclusion process for this systematic review. Articles written in languages other than English (non-English), articles involving animal models (nonhuman), and articles not pertaining to the review question (not relevant) were excluded during title/abstract screening. Articles that investigated an exposure other than platelet transfusion (wrong exposure) or an outcome other than mortality (wrong outcome), or studies that used a study design other than randomized controlled trial or cohort study (wrong study design), were excluded during full-text screening.

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Background and objectives: Prompt identification of patients with acute traumatic coagulopathy (ATC) is necessary to expedite appropriate treatment. An early clinical prediction tool that does not require laboratory testing is a convenient way to estimate risk. Prediction models have been developed, but none are in widespread use. This systematic review aimed to identify and assess accuracy of prediction tools for ATC. Materials and Methods: A search of OVID Medline and Embase was performed for articles published between January 1998 and February 2018. We searched for prognostic and predictive studies of coagulopathy in adult trauma patients. Studies that described stand-alone predictive or associated factors were excluded. Studies describing prediction of laboratory-diagnosed ATC were extracted. Performance of these tools was described. Results: Six studies were identified describing four different ATC prediction tools. The COAST score uses five prehospital variables (blood pressure, temperature, chest decompression, vehicular entrapment and abdominal injury) and performed with 60% sensitivity and 96% specificity to identify an International Normalised Ratio (INR) of >1.5 on an Australian single centre cohort. TICCS predicted an INR of >1.3 in a small Belgian cohort with 100% sensitivity and 96% specificity based on admissions to resuscitation rooms, blood pressure and injury distribution but performed with an Area under the Receiver Operating Characteristic (AUROC) curve of 0.700 on a German trauma registry validation. Prediction of Acute Coagulopathy of Trauma (PACT) was developed in USA using six weighted variables (shock index, age, mechanism of injury, Glasgow Coma Scale, cardiopulmonary resuscitation, intubation) and predicted an INR of >1.5 with 73.1% sensitivity and 73.8% specificity. The Bayesian network model is an artificial intelligence system that predicted a prothrombin time ratio of >1.2 based on 14 clinical variables with 90% sensitivity and 92% specificity. Conclusions: The search for ATC prediction models yielded four scoring systems. While there is some potential to be implemented effectively in clinical practice, none have been sufficiently externally validated to demonstrate associations with patient outcomes. These tools remain useful for research purposes to identify populations at risk of ATC.