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Precise Phenotyping Classification in Atrial Fibrillation

NCT07044011 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2025-06-29

No results posted yet for this study

Summary

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.

Conditions

Sponsors & Collaborators

  • China National Center for Cardiovascular Diseases

    lead OTHER_GOV

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-08-01
Primary Completion
2030-05-31
Completion
2030-05-31

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07044011 on ClinicalTrials.gov