Universität zu Köln

Schaefer, Simon T., Otto, Anne-Christine, Acevedo, Alice-Christin, Goerlinger, Klaus, Massberg, Steffen, Kammerer, Tobias ORCID: 0000-0001-8920-7187 and Groene, Philipp ORCID: 0000-0001-8357-5552 (2021). Point-of-care detection and differentiation of anticoagulant therapy - development of thromboelastometry-guided decision-making support algorithms. Thromb. J., 19 (1). LONDON: BMC. ISSN 1477-9560

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Abstract

Background: DOAC detection is challenging in emergency situations. Here, we demonstrated recently, that modified thromboelastometric tests can reliably detect and differentiate dabigatran and rivaroxaban. However, whether all DOACs can be detected and differentiated to other coagulopathies is unclear. Therefore, we now tested the hypothesis that a decision tree-based thromboelastometry algorithm enables detection and differentiation of all direct Xa-inhibitors (DXals), the direct thrombin inhibitor (DTI) dabigatran, as well as vitamin K antagonists (VKA) and dilutional coagulopathy (DIL) with high accuracy. Methods: Following ethics committee approval (No 17-525-4), and registration by the German clinical trials database we conducted a prospective observational trial including 50 anticoagulated patients (n = 10 of either DOACNKA) and 20 healthy volunteers. Blood was drawn independent of last intake of coagulation inhibitor. Healthy volunteers served as controls and their blood was diluted to simulate a 50% dilution in vitro. Standard (extrinsic coagulation assay, fibrinogen assay, etc.) and modified thromboelastometric tests (ecarin assay and extrinsic coagulation assay with low tissue factor) were performed. Statistical analyzes included a decision tree analyzes, with depiction of accuracy, sensitivity and specificity, as well as receiver-operating-characteristics (ROC) curve analysis including optimal cut-off values (Youden-Index). Results: First, standard thromboelastometric tests allow a good differentiation between DOACs and VKA, DIL and controls, however they fail to differentiate DXals, DTIs and VKAs reliably resulting in an overall accuracy of 78%. Second, adding modified thromboelastometric tests, 9/10 DTI and 28/30 DXaI patients were detected, resulting in an overall accuracy of 94%. Complex decision trees even increased overall accuracy to 98%. ROC curve analyses confirm the decision-tree-based results showing high sensitivity and specificity for detection and differentiation of DTI, DXals, VKA, DIL, and controls. Conclusions: Decision tree-based machine-learning algorithms using standard and modified thromboelastometric tests allow reliable detection of DTI and DXals, and differentiation to VKA, DIL and controls.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Schaefer, Simon T. UNSPECIFIED UNSPECIFIED UNSPECIFIED Otto, Anne-Christine UNSPECIFIED UNSPECIFIED UNSPECIFIED Acevedo, Alice-Christin UNSPECIFIED UNSPECIFIED UNSPECIFIED Goerlinger, Klaus UNSPECIFIED UNSPECIFIED UNSPECIFIED Massberg, Steffen UNSPECIFIED UNSPECIFIED UNSPECIFIED Kammerer, Tobias UNSPECIFIED orcid.org/0000-0001-8920-7187 UNSPECIFIED Groene, Philipp UNSPECIFIED orcid.org/0000-0001-8357-5552 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-575737
DOI:	10.1186/s12959-021-00313-7
Journal or Publication Title:	Thromb. J.
Volume:	19
Number:	1
Date:	2021
Publisher:	BMC
Place of Publication:	LONDON
ISSN:	1477-9560
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language DIRECT ORAL ANTICOAGULANTS; TRAUMATIC BRAIN-INJURY; ROTATIONAL THROMBELASTOMETRY; LABORATORY ASSESSMENT; RIVAROXABAN; ENOXAPARIN; THROMBOPROPHYLAXIS; GENERATION; MANAGEMENT; MONITOR Multiple languages Hematology; Peripheral Vascular Disease Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/57573