Atrial Fibrillation Clinical Trial
— EKGOfficial title:
Variaciones En El Elctrocardiograma Como Prediccion Del Desarrollo De Fibrilacion AURIC
| NCT number | NCT01405209 |
| Other study ID # | 1713 |
| Secondary ID | |
| Status | Completed |
| Phase | |
| First received | |
| Last updated | |
| Start date | July 2011 |
| Est. completion date | December 2014 |
| Verified date | August 2019 |
| Source | Hospital Italiano de Buenos Aires |
| Contact | n/a |
| Is FDA regulated | No |
| Health authority | |
| Study type | Observational |
Atrial fibrillation (AF) is the most common arrhythmia, affecting 1% of adults, with its
prevalence increasing with age [1]. It is associated with increased morbidity and mortality.
Most patients who develop AF have architectural and anisotropic micro changes in the atrial
myocardium. These cause heterogeneous and discontinuous changes in the patterns of impulse
propagation, heterogeneous atrial activation and shortening of atrial refractory period [2,
3].
Since 1911 the standard EKG [4] (approximately 15 seconds of recording and bandwidth 0.05 to
150 Hz) is the most used tool for the evaluation of patients with arrhythmias, due to its low
cost and high availability. Various electrocardiographic patterns are known predictors of AF
as evidenced by direct visual inspection. For example, prolongation of P wave duration during
sinus rhythm would correlate with structural changes such as increasing the size of the left
atrium (the increase in left atrial pressure) or a decrease in driving time [5]. These
changes favor the development of reentry circuits responsible for the development and
maintenance of AF.
The registration of the electrocardiographic activity provides much more information than
evidenced by direct visual inspection. Biosignal processing of these specific techniques to
detect potential delays caused by abnormal conduction of the myocardium that favor re-entry
mechanisms [6-10]. For this purpose prolonged ECG with 1000 Hz sampling frequency. Knowledge
about the prediction of the development of AF with the standard ECG is not obvious on visual
inspection is limited.
Many of these structural changes and anisotropic, occur slowly over time and may be evidenced
by direct variations between 2 ECG from the same individual [11]. Little is known about
whether differences in morphology, axis, scope or duration of P wave related to these
structural changes may predict the development of AF.
Our main purpose is to evaluate the prognostic performance of a set of parameters as
evidenced by direct inspection of the ECG, and ECG changes from 2 to predict the FA
development. The design of this tool could allow future generation of software capable of
identifying and reporting these variations, most useful prognostic risk in patients with AF.
| Status | Completed |
| Enrollment | 100 |
| Est. completion date | December 2014 |
| Est. primary completion date | December 2014 |
| Accepts healthy volunteers | No |
| Gender | All |
| Age group | 18 Years and older |
| Eligibility |
Inclusion Criteria: 1. Patients over 18 years Health Plan members of the Italian Hospital of Buenos Aires with at least 2 ECG separated . Exclusion Criteria: 1. Patients with sinus rhythm different. 2. Patients with a history of congenital heart disease (tetralogy of fallot, CIA) 3. Patients with implanted defibrillator or pacemaker. 4. Patients with a history of cardiac surgery or performing heart surgery from the last ECG and the development of AF. 5. Patients with a history of radiofrequency ablation for treatment of arrhythmias. |
| Country | Name | City | State |
|---|---|---|---|
| Argentina | Hospital Italiano de Buenos AIres | Buenos Aires |
| Lead Sponsor | Collaborator |
|---|---|
| Hospital Italiano de Buenos Aires |
Argentina,
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | Variations (differences or deltas) between 2 standard ECG separated in time | To describe and evaluate the association between the variations (differences or deltas) between 2 standard ECG separated in time (eg difference in p-wave amplitude, difference in wavelength p) to predict development of AF | at least 20 days after the first ekg |
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