ArticleThrombosis journal2021
Point-of-care detection and differentiation of anticoagulant therapy - development of thromboelastometry-guided decision-making support algorithms.
Article in Thrombosis journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Evaluating the Clinical Significance of Pre- and Postoperative Platelet Function Testing in Coronary Artery Bypass Grafting Surgery.Journal of clinical medicine · 2026Article
- Precision hemostasis: how viscoelastic testing guides real-time decision-making in trauma.Trauma surgery & acute care open · 2026Review
- Redefining haemostasis: Role of rotational thromboelastometry in critical care settings.World journal of critical care medicine · 2025Review
- Viscoelastic monitoring of direct oral anticoagulants (DOAC).Blood transfusion = Trasfusione del sangue · 2025Article
- Systematic Scoping on Point-of-care Monitoring of Direct Oral Anticoagulants in Patients with Non-valvular Atrial Fibrillation: Current Status and Future Perspectives in Malaysia.European cardiology · 2025Review
- Anticoagulation for cardiopulmonary bypass, Part 2: alternatives and pathological states.BJA education · 2023Review
- The methods for removal of direct oral anticoagulants and heparins to improve the monitoring of hemostasis: a narrative literature review.Thrombosis journal · 2023Review
- Point-of-Care Assessment of Direct Oral Anticoagulation in Acute Ischemic Stroke: Protocol for a Prospective Observational Diagnostic Accuracy Study.Thrombosis and haemostasis · 2022Article
- Modified thromboelastometric tests provide improved sensitivity and specificity to direct oral anticoagulants compared to standard thromboelastometric tests in-vitro.Thrombosis journal · 2022Article
- Biological Variation in Rotational Thromboelastometry in Patients with Atrial Fibrillation Receiving Rivaroxaban.Journal of cardiovascular development and disease · 2022Article
- "In Less than No Time": Feasibility of Rotational Thromboelastometry to Detect Anticoagulant Drugs Activity and to Guide Reversal Therapy.Journal of clinical medicine · 2022Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundDOAC 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 (DXaIs), the direct thrombin inhibitor (DTI) dabigatran, as well as vitamin K antagonists (VKA) and dilutional coagulopathy (DIL) with high accuracy.
methodsFollowing 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 DOAC/VKA) 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).
resultsFirst, standard thromboelastometric tests allow a good differentiation between DOACs and VKA, DIL and controls, however they fail to differentiate DXaIs, 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, DXaIs, VKA, DIL, and controls.
conclusionsDecision tree-based machine-learning algorithms using standard and modified thromboelastometric tests allow reliable detection of DTI and DXaIs, and differentiation to VKA, DIL and controls.
trial registrationClinical trial number: German clinical trials database ID: DRKS00015704 .
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