CytoSorb® Hemoadsorption as a Promising Tool to Handle COVID-19-Induced Cytokine Storm.

Accumulating evidence suggests that a patient subgroup with severe COVID-19 develops a cytokine release syndrome leading to capillary leakage and organ injury. Recent publications addressing therapy of cytokine storms recommended new extracorporeal therapies such as hemoadsorption. This case report describes a 59-year-old SARS-CoV-2-positive patient with severe ARDS. Due to severe hyperinflammation with concomitant hemodynamic instability and progressive renal failure, combination of continuous renal replacement and CytoSorb® hemoadsorption therapy was initiated. Treatment resulted immediately in a control of the hyperinflammatory response. Simultaneously, lung function continued to improve accompanied by profound hemodynamic stabilization. We report the successful utilization of CytoSorb® hemoadsorption in the treatment of a patient with SARS-CoV-2-induced cytokine storm syndrome.

Point-of-care detection and differentiation of anticoagulant therapy - development of thromboelastometry-guided decision-making support algorithms.

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 (DXaIs), 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 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). RESULTS: First, 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. CONCLUSIONS: Decision 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 REGISTRATION: Clinical trial number: German clinical trials database ID: DRKS00015704 .

Coagulation under Mild Hypothermia Assessed by Thromboelastometry.

INTRODUCTION: While previous studies have shown a significant impact of extreme hypo- and hyperthermia on coagulation, effects of much more frequently occurring perioperative mild hypothermia are largely unknown. This study therefore aimed to analyze the effects of mild hypothermia using rotational thromboelastometry in vitro. MATERIALS AND METHODS: Twelve healthy volunteers were included in this study. Standard thromboelastometric tests (EXTEM, INTEM, FIBTEM) were used to evaluate coagulation in vitro at 39, 37, 35.5, 35, and 33°C. Beyond standard thromboelastometric tests, we also evaluated the effects of mild hypothermia on the TPA-test (ClotPro, Enicor GmbH, Munich, Germany), a new test which aims to detect fibrinolytic capacity by adding tissue plasminogen activator to the sample. Data are presented as the median with 25/75th percentiles. RESULTS: Extrinsically activated coagulation (measured by EXTEM) showed a significant increase in clot formation time (CFT; 37°C: 90 s [81/105] vs. 35°C: 109 s [99/126]; p = 0.0002), while maximum clot firmness (MCF) was not significantly reduced. Intrinsically activated coagulation (measured by INTEM) also showed a significant increase in CFT (37°C: 80 s [72/88] vs. 35°C: 94 s [86/109]; p = 0.0002) without significant effects on MCF. Mild hypothermia significantly increased both the lysis onset time (136 s [132/151; 37°C] vs. 162 s [141/228; 35°C], p = 0.0223) and lysis time (208 s [184/297; 37°C] vs. 249 s [215/358; 35°C]; p = 0.0259). CONCLUSION: This demonstrates that even under mild hypothermia coagulation is significantly altered in vitro. Perioperative temperature monitoring and management are greatly important and can help to prevent mild hypothermia and its adverse effects. Further investigation and in vivo testing of coagulation under mild hypothermia is needed.

Real-time detection and differentiation of direct oral anticoagulants (rivaroxaban and dabigatran) using modified thromboelastometric reagents.

INTRODUCTION: Timely measurement of direct oral anticoagulants (DOACs) is challenging, though clinically important. We tested the hypotheses, that thromboelastometry is able to detect dabigatran and rivaroxaban and discriminates between dabigatran and rivaroxaban as representatives of the two groups of DOACs. METHODS AND MATERIALS: We conducted a prospective-observational study: In-vitro dose-effect-curves for rivaroxaban and dabigatran were performed (n = 10). Ex-vivo: Patients with indication of DOAC treatment (stroke; dabigatran/rivaroxaban) were included (n = 21). Blood samples were analyzed before first intake, at first estimated peak level and at 24 h after first but before following intake and 3 h after 24 h-intake. Standard and modified thromboelastometric-assays, using low tissue factor concentrations (TFTEM) or ecarin (ECATEM) were used. Receiver-operating-characteristics-curve-analysis (ROC), regression-analysis and two-way-ANOVA were performed. RESULTS: In-vitro: TFTEM detected dabigatran and rivaroxaban (ROC_AUC: 0.99; sensitivity/specificity: 100%/98%) but could not discriminate. Dabigatran prolongs CTECATEM whereas rivaroxaban did not. Clotting Time (CT)-ratio TFTEM/ECATEM discriminated highly sensitive (100%) and specific (100%) between dabigatran and rivaroxaban even at very low concentrations (ROC_AUC:1.0). CTECATEM correlated with dabigatran spiked concentrations (r = 0.9985; p < 0.001) and CTTFTEM (r = 0.9363; p = 0.006) with rivaroxaban. Similarly results could be demonstrated with patient data: We confirmed the performance for the differentiation of CT-ratio TFTEM/ECATEM (sensitivity 100%/specificity 100%) at any time after first intake of either DOAC. CONCLUSION: The thromboelastometric tests TFTEM and ECATEM detect and differentiate rivaroxaban and dabigatran. Further investigations evaluate the other DOACs and the differentiation to phenprocoumon. However, results need to be confirmed in a larger study, and especially cut off values for differentiation need to be calculated from a larger sample size.