Novel non-invasive P wave analysis for the prediction of paroxysmal atrial fibrillation recurrences in patients without structural heart disease (original) (raw)
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International Journal of …, 2010
Objectives: The pathogenetic mechanisms responsible for the initiation and recurrence of PAF are not fully elucidated and vary among individuals. We evaluated the ability of a novel non-invasive approach based on P wave wavelet analysis to predict symptomatic paroxysmal atrial fibrillation (PAF) recurrences in individuals without structural heart disease. Methods: We studied 50 patients (24 males, mean age 54.9 ± 9.8 years) presented to our emergency department with a symptomatic episode of PAF. The patients were followed-up for 12.1 ± 0.1 months and classified into two groups according to the number of PAF episodes: Group A (b 5 PAF, n = 33), Group B (≥5 PAF, n = 17). A third Group of 50 healthy individuals without history of PAF was used as control. Study groups underwent echocardiography and orthogonal ECG-based wavelet analyses of P waves at baseline and follow-up. Maximum and mean P wave energies were calculated in each subject at each orthogonal lead using the Morlet wavelet analysis. Results: Larger P wave energies at X lead and relatively larger left atrium were independently associated with N 5 PAF episodes vs. b 5 PAF episodes. No difference in P wave duration was detected between Groups A and B (p N 0.1), whereas Group A and B patients had longer P waves at Z lead compared to Group C (86.4 ± 13 vs. 71.5 ± 15 msec, p b 0.001). Conclusions: P wave wavelet analysis can reliably predict the generation and recurrence of PAF within a year. P wave wavelet analysis could contribute to the early identification of patients at risk for increased number of PAF recurrences.
Study on the P-wave feature time course as early predictors of paroxysmal atrial fibrillation
Physiological Measurement, 2012
Atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice, increasing the risk of stroke and all-cause mortality. Its mechanisms are poorly understood, thus leading to different theories and controversial interpretation of its behavior. In this respect, it is unknown why AF is selfterminating in certain individuals, which is called paroxysmal AF (PAF), and not in others. Within the context of biomedical signal analysis, predicting the onset of PAF with a reasonable advance has been a clinical challenge in recent years. By predicting arrhythmia onset, the loss of normal sinus rhythm could be addressed by means of preventive treatments, thus minimizing risks for the patients and improving their quality of life. Traditionally, the study of PAF onset has been undertaken through a variety of features characterizing P-wave spatial diversity from the standard 12-lead electrocardiogram (ECG) or from signal-averaged ECGs. However, the variability of features from the P-wave time course before PAF onset has not been exploited yet. This work introduces a new alternative to assess time diversity of the P-wave features from single-lead ECG recordings. Furthermore, the method is able to assess the risk of arrhythmia 1 h before its onset, which is a relevant advance in order to provide clinically useful PAF risk predictors. Results were in agreement with the electrophysiological changes taking place in the atria. Hence, P-wave features presented an increasing variability as PAF onset approximates, thus suggesting intermittently disturbed conduction in the atrial tissue. In addition, high PAF risk prediction accuracy, greater than 90%, has been reached in the two considered scenarios, i.e. discrimination between healthy individuals and PAF patients and between patients far from PAF and close to PAF onset. Nonetheless, more long-term studies have to be analyzed and validated in future works.
Can P wave wavelet analysis predict atrial fibrillation after coronary artery bypass grafting?
Pacing and clinical …, 2003
Lake City, Utah VASSILIKOS V., ET AL.: Can P Wave Wavelet Analysis Predict Atrial Fibrillation After Coronary Artery Bypass Grafting? The purpose of this study was the evaluation of Morlet wavelet analysis of the P wave as a means of predicting the development of atrial fibrillation (AF) in patients who undergo coronary artery bypass grafting (CABG). The P wave was analyzed using the Morlet wavelet in 50 patients who underwent successful CABG. Group A consisted of 17 patients, 12 men and 5 women, of mean age 66.9 ± 5.9 years, who developed AF postoperatively. Group B consisted of 33 patients, 29 men and 4 women, mean age 62.4 ± 7.8 years, who remained arrhythmia-free. Using custom-designed software, P wave duration and wavelet parameters expressing the mean and maximum energy of the P wave were calculated from 3-channel digital recordings derived from orthogonal ECG leads (X, Y, and Z), and the vector magnitude (VM) was determined in each of 3 frequency bands
P-wave dispersion index: a marker of patients with paroxysmal atrial fibrillation
International Journal of Cardiology, 1996
The P-wave triggered signal-averaged ECG (PSA-ECG) has shown controversial results in the evaluation of patients with paroxysmal atria1 fibrillation (PAF). Previously tested PSA-ECG parameters, i.e. P-wave filtered duration (Pd), root mean square voltage of the last 20 ms of the P-wave vector magnitude (RMS20) were compared with an index of P-wave dispersion (PDi = Pd (X, Y, Z lead) S.D./mean value x 100) in the evaluation of 40 subjects (24 M, 54 + 7 years) with or without PAP, without anti-arrhythmic therapy. Patients presented vs. controls higher Pd values (138 2 14 ms vs. 120 ? 12 ms, P < O.OOOS), PDi (8 -C 2 ms vs. 1 t 1 ms, P < 0.0001) but no difference in RMS20. In the comparison of patients vs. controls, Pd 2 125 ms presented 62% sensitivity and 78% specificity, PDi 2 5.5 ms showed 83% sensitivity and 81% specificity: the combination of these two criteria differentiated a subgroup of patients with no recurrence of PAF in a 12 2 4 months follow-up. PDi and Pd could be powerful criteria in the identification of patients and could be able to identify patients with low recurrences of PAF.
P Wave Indices to Predict Atrial Fibrillation Recurrences Post Pulmonary Vein Isolation
Arquivos Brasileiros de Cardiologia, 2013
Background: P-wave indices are appealing markers for predicting atrial fibrillation (AF) recurrences post ablation. Objective: This study evaluates the value of P wave indices to predict recurrences post pulmonary vein isolation (PVI) in patients with paroxysmal AF. Methods: We selected 198 patients (57 ± 8 years, 150 males) with symptomatic drug-refractory paroxysmal AF undergoing PVI in our hospital. A 12-lead electrocardiogram was used to measure P wave duration in lead II, P wave terminal force (PWTF) in lead V1, P wave axis and dispersion. Results: During a follow-up of 9 ± 3 months, recurrences occurred in 60 (30.3%) patients. The patients that had AF recurrence had longer mean P wave duration (122.9 ± 10.3 vs 104.3 ± 14.2 ms, p < 0.001), larger P wave dispersion (40.7 ± 1.7 ms vs 36.6 ± 3.2 ms, p < 0.001). P wave duration ≥ 125 ms has 60% sensitivity, 90% specificity, positive predictive value (PPV) of 72% and negative predictive value (NPV) of 83.7%, whereas P wave dispersion ≥ 40 ms has 78% sensitivity, 67% specificity, PPV of 51% and NPV of 87.6% 48/66 (72.7%) patients with PWTF ≤-0.04 mm/second vs 12/132(9%) with PWTF >-0.04 mm/second showed recurrence of AF (p < 0.001). P wave axis was not different between two groups. On multivariate analysis, P wave indices were not independent from left atrial size and age. Conclusions: P wave duration ≥ 125 ms, P wave dispersion ≥ 40 ms and PWTF in V1 ≤-0.04 mm/sec are good clinical predictors of AF recurrences post PVI in patients with paroxysmal atrial fibrillation; however they were not independent from left atrial size and age.
The American Journal of Cardiology, 2007
Atrial fibrillation (AF) is the most prevalent arrhythmia in the elderly, associated with high mortality and morbidity rates. Changes in electrocardiographic P waves were associated with AF in patient series, but the long-term prognostic value of P-wave characteristics in the development of AF was not shown. The aim was to evaluate P-wave duration and morphologic characteristics as potential independent risk markers for the long-term development of AF in the general population. A nested case-control design was adopted in subjects aged 55 to 74 years and apparently healthy at baseline. Baseline P-wave items of 40 patients who developed AF within the 10-year period were compared retrospectively with those of 120 matched controls. Broad maximum P waves (>120 ms) at baseline were observed in 70% of patients with AF and 41% of controls (p ؍ 0.002). Maximum P-wave duration proved to be a significant risk marker independent of blood pressure, body mass index, and other electrocardiographic findings. However, this association seems overruled by the predictive value of morphologic changes defined as notched or deflected P waves (p ؍ 0.0002). The joint occurrence of longer duration in combination with morphologic changes in the P wave proved a very important risk indicator for the development of AF over 10 years, with an adjusted odds ratio of 13.4 (95% confidence interval 3.3 to 46.6). In conclusion, enhanced clinical appreciation of P-wave items on the standard electrocardiogram at rest, preferably evaluated in all 12 leads, may help identify a group at high risk of the development of AF at an early stage.