Why the study?
Does cycle length variability detection (CLVD) analysis accurately measure beat-to-beat cycle lengths during atrial fibrillation compared to dominant frequency analysis in a canine model?
Does cycle length variability detection (CLVD) analysis accurately measure beat-to-beat cycle lengths during atrial fibrillation compared to dominant frequency analysis in a canine model?
The CLVD analysis is an accurate algorithm for detecting the rate and regularity of atrial electrograms during AF, outperforming dominant frequency analysis in an experimental model.
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CLVD merits testing in human AF models; leaves open clinical translation versus dominant frequency analysis.
Lee et al. (2012) studied this question.
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