Evolution of Coagulation and Platelet Activation Markers after Transcatheter Edge-to-Edge Mitral Valve Repair
Journal of clinical medicine（2025）
Quebec Heart and Lung Institute
Abstract
Background/Objectives: The recommendations for antithrombotic therapy after transcatheter edge-to-edge mitral valve repair (TEER) are empirical, and the benefit of antiplatelet (APT) or anticoagulation therapy (ACT) remains undetermined. The study sought to investigate the degree and the timing of coagulation and platelet marker activation after TEER. Methods: This was a prospective study including 46 patients undergoing TEER. The markers of coagulation activation, namely prothrombin fragment 1 + 2 (F1 + 2) and thrombin-antithrombin III (TAT), and the markers of platelet activation, namely soluble P-Selectin and soluble CD-40 ligand (sCD40L), were measured at baseline, 24 h, 1 month, and 1 year after TEER. Results: At discharge, 20 (43%) patients received APT (single: 16, dual: 4), 24 (52%) received ACT, and 2 (4%) had both single APT and ACT. Levels of F1 + 2 and TAT significantly increased at 24 h post TEER (both p < 0.001), rapidly returning to baseline levels at 1 month. However, levels of F1 + 2 and TAT remained higher at 1 month in patients without ACT compared to patients with ACT (respectively, 303.1 vs. 148.1 pmol/L; p < 0.001 and 4.6 vs. 3.0 µg/L; p = 0.020), with a similar trend at 1 year. Levels of soluble P-selectin and sCD40L remained stable at all times after TEER (respectively, p = 0.071 and p = 0.056), regardless of the APT. Conclusions: TEER is associated with an acute activation of the coagulation system, with no increase in platelet activation markers. Hence, the use of dual APT is questionable in this population. Our results raise the hypothesis that the optimal antithrombotic therapy after TEER could be short-term ACT over APT. Further larger studies are warranted.
MoreTranslated text
Key words
transcatheter mitral valve repair,coagulation,platelets,antithrombin III,P-selectin
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper