• Ajeet D Sharma, Antoine Al-Achi, John F Seccombe, Richard Hummel, Matt Preston, and Dana Behrend.
• aDepartment of Cardiac Anesthesia/Cardiac Surgery, St Vincent's Hospital Heart Center, Green Bay, Wisconsin bDepartment of Pharmaceutical Sciences, Campbell University, Buies Creek, North Carolina, USA.
• Blood Coagul. Fibrinolysis. 2014 Sep 1;25(6):561-70.

AbstractCardiopulmonary bypass (CPB) coagulopathy increases utilization of allogenic blood/blood products, which can negatively affect patient outcomes. Thromboelastography (TEG) is a point-of-care measurement of clot formation and fibrinolysis. We investigated whether the addition of TEG parameters to a clinically based bleeding model would improve the predictability of postoperative bleeding. A total of 439 patients' charts were retrospectively investigated for 8-h chest tube output (CTO) postoperatively. For model 1, the variables recorded were patient age, gender, body surface area, clopidogrel use, CPB time, first post-CPB fibrinogen serum level, first post-CPB platelet count, first post-CPB international normalized ratio, the total amount of intraoperative cell saver blood transfused, and postoperative first ICU hematocrit level. Model 2 had the model 1 variables, TEG angle, and maximum amplitude. The outcome was defined as 0-8-h CTO. The predictor variables were placed into a forward stepwise regression model for continuous outcomes. Analysis of variance with adjusted R was used to assess the goodness-of-fit of both predictive models. The predictive accuracy of the model was examined using CTO as a dichotomous variable (75th percentile, 480 ml) and receiver operating characteristic curves for both models. Advanced age, male gender, preoperative clopidogrel use for 5 days or less, greater cell saver blood utilization, and lower postoperative hematocrit levels were associated with increased 8-h CTO (P < 0.05). Adding TEG angle and maximum amplitude to model 1 did not improve CTO predictability. When TEG angle and maximum amplitude were added as predictor factors, the predictability of the bleeding model did not improve.

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