Key result
A decision tree combining dominant atrial frequency, sample entropy, and f-wave average power from preoperative ECGs predicted Cox-maze surgery outcome at discharge with 90% accuracy.
Why the study?
Can preoperative ECG parameters (DAF, SampEn, fWP) predict the rhythm outcome of Cox-maze surgery at discharge in patients with atrial fibrillation?
Observational (n=30)
Can preoperative ECG parameters (DAF, SampEn, fWP) predict the rhythm outcome of Cox-maze surgery at discharge in patients with atrial fibrillation?
Preoperative ECG analysis of f-wave patterns and atrial activity organization can accurately predict the rhythm outcome of Cox-maze surgery at discharge.
May aid preoperative Cox-maze risk stratification; hypothesis-generating and requires prospective validation.
The Cox-maze surgery is an effective procedure for terminating atrial fibrillation (AF) in patients requiring open-heart surgery associated with another heart disease. After the intervention, regardless of the patient's rhythm, all are treated with oral anticoagulants and antiarrhythmic drugs prior to discharge. Furthermore, patients maintaining AF before discharge could also be treated with electrical cardioversion (ECV). In view of this, a preoperative prognosis of the patient's rhythm at discharge would be helpful for optimizing drug therapy planning as well as for advancing ECV therapy. This work analyzes 30 preoperative electrocardiograms (ECGs) from patients suffering from AF in order to predict the Cox-maze surgery outcome at discharge. Two different characteristics of the AF pattern have been studied. On the one hand, the atrial activity (AA) organization, which provides information about the number of propagating wavelets in the atria, was investigated. AA organization has been successfully used in previous studies related to spontaneous reversion of paroxysmal AF and to the outcome of ECV. To assess organization, the dominant atrial frequency (DAF) and sample entropy (SampEn) have been computed. On the other hand, the second characteristic studied was the fibrillatory wave (f-wave) amplitude, which has been demonstrated to be a valuable indicator of the Cox-maze surgery outcome in previous studies. Moreover, this parameter has been obtained through a new methodology, based on computing the f-wave average power (fWP). Finally, all the computed indices were combined in a decision tree in order to improve prediction capability. Results for the DAF yielded a sensitivity (Se), a specificity (Sp) and an accuracy (Acc) of 61.54%, 82.35% and 73.33%, respectively. For SampEn the values were 69.23%, 76.00% and 73.33%, respectively, and for fWP they were 92.31%, 82.35% and 86.67%, respectively. Finally, the decision tree combining the three parameters analyzed improved the preoperative prognosis of the Cox-maze outcome with values of Se, Sp and Acc of 100%, 82.35% and 90%, respectively. As a consequence, the analysis of parameters related to the f-wave pattern, extracted from the preoperative ECG, has provided a considerable ability to predict the outcome of AF Cox-maze surgery at discharge.
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Hernández et al. (2014) conducted an observational in Atrial fibrillation requiring open-heart surgery (n=30). Preoperative ECG parameters (DAF, SampEn, fWP) was evaluated on Cox-maze surgery outcome at discharge. A decision tree combining dominant atrial frequency, sample entropy, and f-wave average power from preoperative ECGs predicted Cox-maze surgery outcome at discharge with 90% accuracy.
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