Data-driven Development of ROTEM and TEG Algorithms for the Management of Trauma Hemorrhage: A Prospective Observational Multicenter Study

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Abstract

Objective:

Developing pragmatic data-driven algorithms for management of trauma induced coagulopathy (TIC) during trauma hemorrhage for viscoelastic hemostatic assays (VHAs).

Background:

Admission data from conventional coagulation tests (CCT), rotational thrombelastometry (ROTEM) and thrombelastography (TEG) were collected prospectively at 6 European trauma centers during 2008 to 2013.

Methods:

To identify significant VHA parameters capable of detecting TIC (defined as INR > 1.2), hypofibrinogenemia (< 2.0 g/L), and thrombocytopenia (< 100 x109/L), univariate regression models were constructed. Area under the curve (AUC) was calculated, and threshold values for TEG and ROTEM parameters with 70% sensitivity were included in the algorithms.

Results:

A total of, 2287 adult trauma patients (ROTEM: 2019 and TEG: 968) were enrolled. FIBTEM clot amplitude at 5 minutes (CA5) had the largest AUC and 10 mm detected hypofibrinogenemia with 70% sensitivity. The corresponding value for functional fibrinogen (FF) TEG maximum amplitude (MA) was 19 mm. Thrombocytopenia was similarly detected using the calculated threshold EXTEM-FIBTEM CA5 30 mm. The corresponding rTEG-FF TEG MA was 46 mm. TIC was identified by EXTEM CA5 41 mm, rTEG MA 64 mm (80% sensitivity). For hyperfibrinolysis, we examined the relationship between viscoelastic lysis parameters and clinical outcomes, with resulting threshold values of 85% for EXTEM Li30 and 10% for rTEG Ly30.

Results:

Based on these analyses, we constructed algorithms for ROTEM, TEG, and CCTs to be used in addition to ratio driven transfusion and tranexamic acid.

Conclusions:

We describe a systematic approach to define threshold parameters for ROTEM and TEG. These parameters were incorporated into algorithms to support data-driven adjustments of resuscitation with therapeutics, to optimize damage control resuscitation practice in trauma.

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