Precise Phenotyping Classification in Atrial Fibrillation

Brief summary (registry, in English)

This study aims to integrate multi-omics data (genomics, imaging, serology, etc.) to achieve precise phenotyping classification for atrial fibrillation (AF) patients and explore personalized rhythm control strategies. By enrolling over 1,000 AF patients, we will collect genomic data including GWAS and single-cell sequencing, combined with cardiac MRI, CT, echocardiography imaging, and serum biomarkers, to uncover AF pathological mechanisms and recurrence risks at molecular and structural levels. Machine learning and AI algorithms will be employed to develop AF phenotypic classification models, which will be validated across multiple centers to assess their accuracy and reliability in predicting AF recurrence and therapeutic responses. Furthermore, clinical trials will evaluate the efficacy of oral dronedarone hydrochloride tablets and intravenous nicorandil hydrochloride in preventing post-catheter ablation recurrence and their safety/effectiveness in early cardioversion. Finally, based on advanced phenotyping results, we will establish personalized rhythm control strategies integrating pharmacotherapy, catheter ablation, and lifestyle interventions to optimize AF management.

What you commit to

• Study type: Observational
• Planned participants: 1000
• From 1 Aug 2025 to the primary completion date, 31 May 2030
• 1 site in 1 country
• Visits and tests: ask the trial team, the registry does not list them

Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.

Who cannot take part

Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.

Who the study is looking for

Sex: All · Does not accept healthy volunteers

Full criteria on ClinicalTrials.gov

Sites (1)

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