D Brilej1, D Stropnik2, R Lefering3, R Komadina2. 1. Trauma Department, General and Teaching Hospital Celje, Oblakova 5, 3000, Celje, Slovenia. Drago.Brilej@guest.arnes.si. 2. Trauma Department, General and Teaching Hospital Celje, Oblakova 5, 3000, Celje, Slovenia. 3. Institut fur Forschung in der Operative Medizin, Fakultat fur Gesundheit der Universitat Witten/Herdecke, Ostmerheimer str 200, 51109, Koln, Germany.
Abstract
BACKGROUND: Early recognition and management of trauma related coagulopathy improves the outcome. Trauma facilities should implement an algorithm to identify the bleeding trauma patient with coagulopathy. OBJECTIVE: The scope of the paper is to identify the indicators of early coagulopathy and to optimize the indications for thromboelastometry and coagulation support. DESIGN: Cohort study based on data from trauma registry. SETTING: Data of 493 major trauma patients treated in GH Celje from 2006 to 2014 were included into The TraumaRegister DGU® (TR-DGU). PATIENTS: Patients were selected for inclusion into TR-DGU according to the following criteria: polytraumatized patients with Injury severity score (ISS) ≥ 18, patients with injuries to single region with AIS 5, patients with major injuries to a single region and abnormal vital signs. All patients that were dead on arrival to hospital, patients presented to hospital >24 h after the injury, and head injuries that occurred with a low energy mechanism in patients on anticoagulation drugs were excluded. MEASUREMENTS: Two groups were formed (with or without coagulopathy). Mortality, morbidity, length of mechanical ventilation, ICU and hospital stay were used as outcome and compared between the groups. A coagulopathy prediction model (CPM) was developed to identify the patients who were at high risk of coagulopathy. RESULTS: Coagulopathy was present in 51 % of patients. Severe injuries to the torso and limbs, infusion of >1000 ml of fluids in the prehospital settings, and hypotension were included into CPM. If all three criteria were present, the sensitivity of the model to predict coagulopathy was 93 %. By adding the blood gas analysis (BE ≤ -5), the specificity increased to 81.7 %. LIMITATIONS: Shortcomings of our analysis are mainly related to the quality of data in the registry that may not be comparable to a clinical trial where data are collected specifically to address a given issue. CONCLUSIONS: The Criteria for activation of coagulation support treatment remain centre dependent. In our settings the CPM is the tool to select patients for ROTEM® analysis. By adding data from blood gas analysis, treatment of coagulopathy is justifiable before complete test results are available.
BACKGROUND: Early recognition and management of trauma related coagulopathy improves the outcome. Trauma facilities should implement an algorithm to identify the bleeding traumapatient with coagulopathy. OBJECTIVE: The scope of the paper is to identify the indicators of early coagulopathy and to optimize the indications for thromboelastometry and coagulation support. DESIGN: Cohort study based on data from trauma registry. SETTING: Data of 493 major traumapatients treated in GH Celje from 2006 to 2014 were included into The TraumaRegister DGU® (TR-DGU). PATIENTS: Patients were selected for inclusion into TR-DGU according to the following criteria: polytraumatized patients with Injury severity score (ISS) ≥ 18, patients with injuries to single region with AIS 5, patients with major injuries to a single region and abnormal vital signs. All patients that were dead on arrival to hospital, patients presented to hospital >24 h after the injury, and head injuries that occurred with a low energy mechanism in patients on anticoagulation drugs were excluded. MEASUREMENTS: Two groups were formed (with or without coagulopathy). Mortality, morbidity, length of mechanical ventilation, ICU and hospital stay were used as outcome and compared between the groups. A coagulopathy prediction model (CPM) was developed to identify the patients who were at high risk of coagulopathy. RESULTS:Coagulopathy was present in 51 % of patients. Severe injuries to the torso and limbs, infusion of >1000 ml of fluids in the prehospital settings, and hypotension were included into CPM. If all three criteria were present, the sensitivity of the model to predict coagulopathy was 93 %. By adding the blood gas analysis (BE ≤ -5), the specificity increased to 81.7 %. LIMITATIONS: Shortcomings of our analysis are mainly related to the quality of data in the registry that may not be comparable to a clinical trial where data are collected specifically to address a given issue. CONCLUSIONS: The Criteria for activation of coagulation support treatment remain centre dependent. In our settings the CPM is the tool to select patients for ROTEM® analysis. By adding data from blood gas analysis, treatment of coagulopathy is justifiable before complete test results are available.
Entities:
Keywords:
Coagulopathy; Major injury; Prediction model; Trauma registry
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