Multimodality Prediction of Success of Atrial Fibrillation Rhythm Control Strategy

NCT ID: NCT02009683

Last Updated: 2018-04-26

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 220 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2014-05-31
• Study Completion Date: 2018-09-30

Brief Summary

In this study the investigators aim to build a model to predict the maintenance of sinus rhythm (SR) after successful direct current cardioversion (DCC) incorporating standard predictors such as echocardiographic parameters, clinical parameter and 12-lead ECG parameters and new parameters, including 17-lead ECG, Oesophageal-ECG and single nucleotide polymorphisms (SNPs). Using this novel integrated prediction model will help in the identification of patients who will maintain SR after cardioversion. Another innovative aspect of our study is the use of daily rhythm monitoring using a versatile device (MyDiagnostick®). The clinical impact this study will have is that it helps the cardiologist to make a patient tailored strategy in the treatment of AF as advocated by the guidelines and to prevent exposing patients not likely to maintain SR to the potentially harmful side-effect of a rhythm-control strategy.

Primary objectives To show that a model incorporating the novel predictors 17-lead ECG, Oesophageal-ECG and SNPs is superior to existing models in predicting maintenance of sinus rhythm after successful DCC in patients with persistent AF.

Secondary objectives To assess the predictive value of new predictors (the Oesophageal-ECG, 17-lead ECG and SNPs) for maintenance of SR after successful DCC separately.

To assess the predictive value of new predictors (the Oesophageal-ECG, 17-lead ECG and SNPs) for time to recurrence of AF.

To assess the predictive value of predictors with respect to complete failure of cardioversion.

To assess the predictive value of predictors with respect to cardiovascular morbidity.

Hypothesis The investigators hypothesise that a model incorporating the novel predictors the 17-leads ECG, Oesophageal-ECG and SNPs performs significantly better than existing models using only clinical, echocardiographic and ECG parameters on a standard 12-lead ECG in predicting maintenance of SR after successful DCC. In addition the investigators hypothesise that Oesophageal-ECG is the best single predictor for maintenance of SR after successful DCC.

Conditions

Atrial Fibrillation

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Eligibility Criteria

Inclusion Criteria

• Haemodynamic stable patients with persistent AF scheduled for DCC.
• Written informed consent.
• Patients > 18 years old.

Exclusion Criteria

• Atrial flutter at time of DCC.
• Patients with known oesophageal disease.
• Patients with previous operations on throat or oesophagus.
• Postoperative atrial fibrillation.
• Patients with previous ablation for AF.
• Previous inclusion in this study.
• Patients on anti-arrhythmic drugs (AAD).
• Patients with pacemakers unable to detect AF and with a regular paced rhythm during AF.
• Planned ablation for AF.
• Myocardial infarction within the last 4 weeks.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Maastricht University Medical Center

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

H Crijns, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Maastricht University Medical Centre

Locations

Maastricht University Medical Centre

Maastricht, , Netherlands

Site Status: RECRUITING

Countries

Netherlands

Central Contacts

Theo Lankveld, MD

Role: CONTACT

theo.lankveld@mumc.nl

+31433871611

Facility Contacts

Harry J Crijns, Md, PhD

Role: primary

043-3875091

Other Identifiers

METC 13-2-033.3

Identifier Type: -

Identifier Source: org_study_id