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372 Predictive Value of Thromboelastography for Outcome Prediction of Aneurysmal Subarachnoid Hemorrhage
Journal article   Peer reviewed

372 Predictive Value of Thromboelastography for Outcome Prediction of Aneurysmal Subarachnoid Hemorrhage

Anant Naik, Joshua Catapano, Elsa Nico, Ashia Hackett, Stefan Wolfgang Koester, Ethan A. Winkler, Joelle Nicole Hartke, Brandon Michael Fox, Ruchira Jha, Ashutosh Jadhav, …
Neurosurgery, Vol.71(Supplement_1), pp.89-90
04/2025

Abstract

INTRODUCTION:Thromboelastography (TEG) is a routine, relatively inexpensive blood test that measures the coagulative properties of a blood sample. Previous studies have demonstrated its efficacy in predicting coagulation profiles in patients with subarachnoid hemorrhage (SAH), however, its relationship to neurological presentation and clinical outcome in patients with aneurysmal subarachnoid hemorrhage (aSAH) remains understudied.METHODS:We retrospectively identified 139 patients from July 2020 - September 2022 with aSAH that obtained TEGs with and without platelet mapping. Our primary outcomes were Hunt-Hess grade (HH), modified Fisher Grade (mFG), Glasgow Coma Scale (GCS), and discharge modified Rankin Scale (D-mRS). We used probability-boosted multivariate linear regression to predict outcomes using values in TEG. For D-mRS, we conducted a sensitivity analysis to identify the added accuracy of TEG to clinical parameters.RESULTS:The mean age of our sample was 60.93 (SD = 13.39). TEG was found to accurately predict HH (R = 0.56, p < 0.001), mFG (R = 0.44, p = 0.002), and GCS (0.636, p < 0.001). PLM6s AA and ADP Inhibition were found to have the highest correlation with outcomes. In the prediction of discharge mRS, our TEG and clinical model were the most predictive (R = 0.748, p < 0.001) compared to our TEG-only and clinical-only models, with a 59.35% and 61.67% reduction in sum-of-squared error (SSE).CONCLUSIONS:In this analysis, we demonstrate the utility of TEG in predicting clinical presentation-based parameters, such as HH, mFG, and GCS, and we demonstrate its added value in predicting discharge mRS. Our data present a powerful argument for the increased utilization of TEG in the management of aSAH patients to better monitor their progression throughout hospital admission and possibly prognosticate their outcomes.

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