Why the study?
Does surface ECG time-frequency analysis predict spontaneous termination in atrial fibrillation recordings?
Does surface ECG time-frequency analysis predict spontaneous termination in atrial fibrillation recordings?
Surface ECG analysis using fibrillatory frequency and exponential decay can accurately predict spontaneous termination of atrial fibrillation, which may help avoid unnecessary treatments.
May identify likely self-terminating AF on ECG; hypothesis-generating and should not yet change practice.
By recognizing and characterizing conditions under which atrial fibrillation (AF) is likely to terminate spontaneously or be sustained, improved treatment of sustained AF may result and unnecessary treatment of self-terminating AF avoided. Time-frequency measures that characterize AF, such as fibrillatory frequency, amplitude, and waveform shape (exponential decay), are extracted from the residual ECG following QRST cancellation. Three complexity measures are also studied, characterizing the degree of organization of atrial activity. All measures are analysed using a training set, consisting of 20 recordings of AF with known termination properties, and a test set of 30 recordings. Spontaneous termination was best predicted by a low and stable fibrillatory frequency and a low exponential decay. Using these predictors, 90% of the test set was correctly classified into terminating and sustained AF. Neither fibrillation amplitude nor the complexity measures differed significantly between the two sets.
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Nilsson et al. (2006) studied this question.
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