Why the study?
Do non-invasive measures of AF complexity accurately discriminate between short-term and long-term AF and predict invasive complexity measures in a goat model?
Do non-invasive measures of AF complexity accurately discriminate between short-term and long-term AF and predict invasive complexity measures in a goat model?
An optimal set of non-invasive measures can accurately assess atrial fibrillation substrate complexity and discriminate between short- and long-term AF in an animal model, potentially aiding patient-tailored therapy.
Non-invasive AF complexity metrics show promise in goats; leaves open translation to human patient stratification.
AIMS: To present a comparison of electrocardiogram-based non-invasive measures of atrial fibrillation (AF) substrate complexity computed on invasive animal recordings to discriminate between short-term and long-term AF. The final objective is the selection of an optimal sub-set of measures for AF complexity assessment. METHODS AND RESULTS: High-density epicardial direct contact mapping recordings (234 leads) were acquired from the right and the left atria of 17 goats in which AF was induced for 3 weeks (short-term AF group, N = 10) and 6 months (long-term AF group, N = 7). Several non-invasive measures of AF organization proposed in the literature in the last decade were investigated to assess their power in discriminating between the short-term and long-term group. The best performing measures were identified, which when combined attained a correct classification rate of 100%. Their ability to predict standard invasive AF complexity measures was also tested, showing an average R(2) of 0.73 ± 0.04. CONCLUSION: An optimal set of measures of the AF substrate complexity was identified out of the set of non-invasive measures analysed in this study. These measures may contribute to improve patient-tailored diagnosis and therapy of sustained AF.
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Bonizzi et al. (2014) studied this question.
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