Current strategies of anticoagulation therapy for patients with non-valvular atrial fibrillation

Novel assay based on diluted prothrombin time reflects anticoagulant effects of direct oral factor Xa inhibitors: Results of multicenter study in Japan

BACKGROUND

Direct oral anticoagulants targeting factor Xa (DXaIs) are administered as prophylaxis for various venothrombotic diseases without routine monitoring required. However, assessment of their anticoagulant effects is necessary to prevent severe events, including major bleeding and/or refractory thrombosis.

OBJECTIVES

We examined the correlation of ratio of inhibited thrombin generation (RITG), determined using a novel assay based on dilute prothrombin time (dPT), with coagulant markers and laboratory test results to show drug effects. In addition, RITG usefulness as a confirmation test for DXaI therapy was investigated.

METHODS

Citrated plasma samples were obtained from patients treated with rivaroxaban (n = 882), apixaban (n = 1214), or edoxaban (n = 820) at 4 different institutions in Japan. Laboratory tests, including prothrombin time (PT), activated partial thromboplastin time (APTT), D-dimer, and plasma concentrations of DXaIs, were conducted, with drug concentrations divided into peak and trough groups, within and after 5 h of administration.

RESULTS

In each DXaI group, RITG was positively correlated with PT, APTT, and drug concentration, and negatively with D-dimer. RITG fluctuation during the peak and trough periods reflected the anticoagulant activity characteristic of each DXaI, which was different from blood concentration fluctuations. RITG showed a significant decrease in cases with thrombosis, while that was increased in those with hemorrhage.

CONCLUSION

We developed RITG, a novel measurement method based on dPT. RITG represents residual coagulation ability in plasma samples, and is useful for assessment of bleeding and thrombotic tendencies in DXaI patients. RITG can be utilized to confirm the effectiveness of oral anticoagulation therapy with DXaI agents.

Perioperative management of patients with atrial fibrillation receiving anticoagulant therapy

The number of patients with atrial fibrillation (AF) and the number of patients indicated for anticoagulant therapy have been increasing because AF would affect patient survival due to thromboembolism. Once AF develops, following the disappearance of pulsation, the circumstances within the atrium become prothrombotic and thrombus formation within the left atrium occurs in patients with AF. In recent years, not only warfarin but also new oral anticoagulants were introduced clinically and have become used as oral anticoagulants. In the perioperative period, the risk of major hemorrhage needs to be reduced. On the other hand, the suspension of anticoagulant therapy and neutralization of anticoagulant effects elevate the risk of thrombosis. The perioperative management of patients receiving anticoagulant therapy is different from that of scheduled surgery and emergency surgery. In addition, knowledge of the characteristics of each oral anticoagulant is required at drug cessation and resumption. Unlike warfarin, which has been used in the past five decades, direct oral anticoagulants (DOACs) do not have sensitive indicators such as prothrombin time-international normalized ratio. To avoid major hemorrhages and thromboembolism, quantitative assays can be implemented for DOAC monitoring and for reversal therapies in perioperative settings.

Neural network and wavelet average framing percentage energy for atrial fibrillation classification

ECG signals are an important source of information in the diagnosis of atrial conduction pathology. Nevertheless, diagnosis by visual inspection is a difficult task. This work introduces a novel wavelet feature extraction method for atrial fibrillation derived from the average framing percentage energy (AFE) of terminal wavelet packet transform (WPT) sub signals. Probabilistic neural network (PNN) is used for classification. The presented method is shown to be a potentially effective discriminator in an automated diagnostic process. The ECG signals taken from the MIT-BIH database are used to classify different arrhythmias together with normal ECG. Several published methods were investigated for comparison. The best recognition rate selection was obtained for AFE. The classification performance achieved accuracy 97.92%. It was also suggested to analyze the presented system in an additive white Gaussian noise (AWGN) environment; 55.14% for 0dB and 92.53% for 5dB. It was concluded that the proposed approach of automating classification is worth pursuing with larger samples to validate and extend the present study.