This study will test the ability of computer algorithms to predict successful ablation therapy for atrial arrhythmias.
Patients will be recruited prospectively from among those undergoing ablation for atrial fibrillation (AF) or atrial tachycardias (AT) which may be reentrant or focal. Each patient will undergo careful data collection, including electrogram data and sites of ablation lesions. Ablation will proceed in operator-dependent fashion, and will not be modified in any way for this study. The research question is whether algorithms based on data such as electrograms and details of the ablation performed can predict which patients will have a successful case. Primary endpoints are measures of clinical success defined by (a) acute termination of atrial arrhythmia during the case; (b) long-term reduction in arrhythmia burden; (c) long-term freedom from arrhythmia. Secondary endpoints include (a) identification of sites of arrhythmia termination; (b) improved clinical status.
Study Type
OBSERVATIONAL
Enrollment
11
Diagnostic algorithms (test) will be run on already acquired clinical data. No study intervention in operator-prescribed clinical ablation. Predictive accuracy of test for study outcome will then be determined in follow-up
Stanford Hospital
Stanford, California, United States
Reduction in AF burden on follow-up
Reduction in amount of arrhythmia per unit time, compared to prior to the procedure.
Time frame: 2 years
Freedom from arrhythmia on follow-up
Absence of arrhythmia, defined by clinical thresholds.
Time frame: 2 years
Clinical status as measured by the EQ5D
Patient feeling better subjectively in EQ5D
Time frame: 2 years
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