Table 4 Comparison between the most recent studies presented to predict ECV outcome
Study | Database | Short description of methods | Diagnostic accuracy |
|---|---|---|---|
This work | Own database with 63 patients: 31 relapsed to AF, 22 maintained NSR and 10 presented unsuccessful ECV | CTM from the first differences scatter plot of the wavelet coefficient vector associated to the AF frequency scale of the AA | 86% |
Alcaraz et al 2011 [35] | Own database with 63 patients: 31 relapsed to AF, 22 maintained NSR and 10 presented unsuccessful ECV | Combination of f waves amplitude and SampEn computed from the MAW of the AA | 90% |
Alcaraz & Rieta 2009 [38] | Own database with 63 patients: 31 relapsed to AF, 22 maintained NSR and 10 presented unsuccessful ECV | Discriminant model based on time and frequency parameters obtained from the AA | 86% |
Alcaraz & Rieta 2008 [30] | Own database with 40 patients: 21 relapsed to AF, 14 maintained NSR and 5 presented unsuccessful ECV | Regularity analysis via SampEn of time and wavelet domains of the AA | 94% |
Watson et al 2007 [43] | Own database with 30 patients: 17 relapsed to AF and 13 maintained NSR | Non-parametric combination of several wavelet transform-based statistical markers | 93% |
Holmqvist et al 2006 [44] | Own database with 54 patients: 30 relapsed to AF and 24 maintained NSR | Assessment of the atrial harmonic decay with time-frequency analysis of the ECG | 70% |
Zohar et al 2005 [45] | Own database with 44 patients: 21 relapsed to AF and 23 maintained NSR | Non-deterministisc model based on genetic programming | 84% |
Berg et al 2004 [46] | Own database with 66 patients: 32 relapsed to AF, 22 maintained NSR and 12 presented unsuccessful ECV | Analysis of 3D RR intervals as a quantifier of AF organization | 52% |