Point-of-care testing for emergency assessment of coagulation in patients treated with direct oral anticoagulants including edoxaban.

BACKGROUND: Direct oral anticoagulants (DOAC) including edoxaban are increasingly used for stroke prevention in atrial fibrillation. Despite treatment, annual stroke rate in these patients remains 1-2%. Rapid assessment of coagulation would be useful to guide thrombolysis or reversal therapy in this growing population of DOAC/edoxaban-treated stroke patients. Employing the Hemochron™ Signature Elite point-of-care test system (HC-POCT), clinically relevant plasma concentrations of dabigatran and rivaroxaban can be excluded in a blood sample. However, no data exists on the effect of edoxaban on HC-POCT results. We evaluated whether edoxaban plasma concentrations above the current treatment thresholds for thrombolysis or anticoagulation reversal (i.e., 30 and 50 ng/mL) can be ruled out with the HC-POCT. METHODS: We prospectively studied patients receiving a first dose of edoxaban. Six blood samples were collected from each patient: before, 0.5, 1, 2, 8, and 24 h after drug intake. HC-POCT-based INR (HC-INR), activated clotting time (HC-ACT+ and HC-ACT-LR), activated partial thromboplastin time (HC-aPTT), and mass spectrometry for edoxaban plasma concentrations were performed at each time-point. We calculated correlations, receiver operating characteristics (ROC) and test-specific cut-offs for ruling out edoxaban concentrations > 30 and > 50 ng/mL in a blood sample. RESULTS: One hundred twenty blood samples from 20 edoxaban-treated patients were analyzed. Edoxaban plasma concentrations ranged from 0 to 512 ng/mL. HC-INR/HC-ACT+/HC-ACT-LR/HC-aPTT ranged from 0.7-8.3/78-310 s/65-215 s/19-93 s, and Pearson's correlation coefficients showed moderate to very strong correlations with edoxaban concentrations (r = 0.95/0.79/0.70/0.60). With areas under the ROC curve of 0.997 (95% confidence interval: 0.991-0.971) and 0.989 (0.975-1.000), HC-INR most reliably ruled out edoxaban concentrations > 30 and > 50 ng/mL, respectively, and HC-INR results ≤1.5 and ≤ 2.1 provided specificity/sensitivity of 98.6% (91.2-99.9)/98.0% (88.0-99.9) and 96.8% (88.0-99.4)/96.5% (86.8-99.4). CONCLUSIONS: Our study represents the first systematic evaluation of the HC-POCT in edoxaban-treated patients. Applying sufficiently low assay-specific cut-offs, the HC-POCT may not only be used to reliably rule out dabigatran and rivaroxaban, but also very low edoxaban concentrations in a blood sample. Because the assay-specific cut-offs were retrospectively defined, further investigation is warranted. TRIAL REGISTRATION: ClinicalTrials.gov, registration number: NCT02825394 , registered on: 07/07/2016, URL.

Point-of-care testing of coagulation in patients treated with edoxaban.

Edoxaban, alongside other direct oral anticoagulants (DOAC), is increasingly used for prevention of thromboembolism, including stroke. Despite DOAC therapy, however, annual stroke rate in patients with atrial fibrillation remains 1-2%. Rapid exclusion of relevant anticoagulation is necessary to guide thrombolysis or reversal therapy but, so far, no data exists on the effect of edoxaban on available point-of-care test systems (POCT). To complete our previous investigation on global coagulation-POCT for the detection of DOAC, we evaluated whether CoaguChek®-INR (CC-INR) is capable of safely ruling out edoxaban concentrations above the current treatment thresholds of 30/50 ng/mL in a blood sample. We studied patients receiving a first dose of edoxaban; excluding subjects receiving other anticoagulants. Six blood samples were collected from each patient: before drug intake, 0.5, 1, 2 and 8 h after intake, and at trough (24 h). CC-INR and mass spectrometry for edoxaban concentrations were performed for each time-point. One hundred and twenty blood samples from 20 patients contained 0-302 ng/mL of edoxaban. CC-INR ranged from 0.9 to 2.3. Pearson's correlation coefficient showed strong correlation between CC-INR and edoxaban concentrations (r = 0.73, p < 0.001). Edoxaban concentrations > 30 and > 50 ng/mL were ruled out by CC-INR ≤ 1.0 and ≤ 1.1, respectively, with high specificity (> 95%), and a sensitivity of 44% (95%-confidence interval: 30-59%) and 86% (74-93%), respectively. Our study represents the first evaluation of coagulation-POCT in edoxaban-treated patients. CC-POCT is suitable to safely exclude clinically relevant edoxaban concentrations prior to thrombolysis, or guide reversal therapy in stroke patients.

Will a Decaying Atom Feel a Friction Force?

We show how a simple calculation leads to the surprising result that an excited two-level atom moving through a vacuum sees a tiny friction force of first order in v/c. At first sight this seems to be in obvious contradiction to other calculations showing that the interaction with the vacuum does not change the velocity of an atom. It is even more surprising that this change in the atom's momentum turns out to be a necessary result of energy and momentum conservation in special relativity.

Image reconstruction from photon sparse data.

We report an algorithm for reconstructing images when the average number of photons recorded per pixel is of order unity, i.e. photon-sparse data. The image optimisation algorithm minimises a cost function incorporating both a Poissonian log-likelihood term based on the deviation of the reconstructed image from the measured data and a regularization-term based upon the sum of the moduli of the second spatial derivatives of the reconstructed image pixel intensities. The balance between these two terms is set by a bootstrapping technique where the target value of the log-likelihood term is deduced from a smoothed version of the original data. When compared to the original data, the processed images exhibit lower residuals with respect to the true object. We use photon-sparse data from two different experimental systems, one system based on a single-photon, avalanche photo-diode array and the other system on a time-gated, intensified camera. However, this same processing technique could most likely be applied to any low photon-number image irrespective of how the data is collected.