A retrospective validation of ROTEM algorithms for detecting hyperfibrinolysis demonstrates poor agreement for prediction of in-hospital mortality and transfusion requirement in a general, non-cardiac, surgical population

Abstract

IntroductionHyperfibrinolysis diagnosed on Rotational Thromboelastography (ROTEM) is associated with increased transfusion requirements and mortality in trauma. The diagnosis and significance of hyperfibrinolysis in a mixed, non-cardiac, general surgical population has not been investigated. We aimed to measure agreement between four ROTEM algorithms for diagnosing hyperfibrinolysis and transfusion requirements and mortality in general surgical patients. These algorithms mostly incorporate measures of early or late clot amplitude reduction on the Extrinsic Clotting Pathway Test with Tissue Factor (EXTEM) channel. MethodFour hospital administrative data sets were linked from 2019 to 2022. Adults >18 years were included if a ROTEM was performed during their surgery (intraoperative period) or within 24-h of the surgery completion (postoperative period). The four hyperfibrinolysis criteria were applied to the ROTEM data and assessed for their agreement, intraoperative and postoperative transfusion requirements and in-patient mortality. ResultsWe linked 933 ROTEMs to 558 patient-procedures. One algorithm identified hyperfibrinolysis on only three patients so was excluded. Agreement between the remaining three was slight (Cohens Kappa 0.18 (p < 0.001)) with hyperfibrinolysis diagnosed between 22 and 69 % of the procedures. The association between hyperfibrinolysis diagnosis and intraoperative or postoperative transfusion requirement was inconsistent between the criteria. However, an algorithm put forward by Goerling et al. was more often associated with transfusion requirement and inpatient mortality. DiscussionThe poor agreement between criteria suggests that some ROTEM criteria may not transfer directly to general surgical patients. Future research should focus on optimising hyperfibrinolysis cut-off values to update algorithms for bleeding general surgical patients.