Next Article in Journal
Investigation of the Clinical Value of Four Visualization Modalities for Congenital Heart Disease
Next Article in Special Issue
Beyond Clinical Factors: Harnessing Artificial Intelligence and Multimodal Cardiac Imaging to Predict Atrial Fibrillation Recurrence Post-Catheter Ablation
Previous Article in Journal
Assessment of the Aorto-Septal Angle Post-Thoracic Endovascular Aortic Repair through Segmentation and the Semi-Automatic Analysis of Cardiosynchronized Computed Tomography Angiography Images
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JCDD
Volume 11
Issue 9
10.3390/jcdd11090277
jcdd-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Role of P Wave Parameters in Predicting Pulmonary Vein Isolation Outcomes for Paroxysmal Atrial Fibrillation: An Observational Cohort Study

by
Ibrahim Antoun
1,*,
Xin Li
2,
Ahmed I. Kotb
1,
Zakkariya Vali
1,3,
Ahmed Abdelrazik
1,
Abdulmalik Koya
1,
Akash Mavilakandy
1,
Ivelin Koev
1,
Ali Nizam
3,
Hany Eldeeb
3,
Riyaz Somani
1,3 and
André Ng
1,3,4
1
Department of Cardiology, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester LE3 9QP, UK
2
Department of Engineering, University of Leicester, Leicester LE1 7RH, UK
3
Department of Cardiovascular Sciences, Clinical Science Wing, University of Leicester, Glenfield Hospital, Leicester LE3 9QP, UK
4
National Institute for Health Biomedical Centre, Leicester LE3 9QP, UK
*
Author to whom correspondence should be addressed.
J. Cardiovasc. Dev. Dis. 2024, 11(9), 277; https://doi.org/10.3390/jcdd11090277
Submission received: 21 July 2024 / Revised: 28 August 2024 / Accepted: 3 September 2024 / Published: 5 September 2024
(This article belongs to the Special Issue Extensive Approach to Atrial Fibrillation: Background and Future Perspectives)
Browse Figure
Versions Notes

Abstract

:
Background: Pulmonary vein isolation (PVI) is an effective management method for paroxysmal atrial fibrillation (PAF). The P wave in the 12-lead electrocardiogram (ECG) represents atrial depolarisation. This study aims to utilise the P wave to predict PVI outcomes for PAF. Methods: This single-centre retrospective study aimed to predict PVI outcomes using P wave parameters. It included 211 consecutive patients with first PVI for PAF between 2018 and 2019 and targeted the pulmonary veins (PVs). Procedure success was defined by freedom of ECG-documented AF at 12 months. Digital 12-lead ECGs with 1–50 hertz bandpass filters were monitored before the procedure. Corrected P wave duration (PWDc), P wave amplitude (PWV), P wave dispersion (PWDisp), intra-atrial block (IAB), P wave area (PWA), and P wave terminal force in V1 (PTFV1) were measured before ablation and correlated with the outcomes. Results: Successful PVI occurred in 154 patients (73%). Demographics were similar between both arms. P wave parameters correlated with PVI failure included increased PWDc in all leads except for lead III, aVR, and V3, decreased PWV in lead I (hazard ratio [HR]: 0.7, 95% confidence interval [CI]: 0.53–0.95), lead II (HR: 0.45, 95% CI: 0.22–0.65), aVL (HR: 0.58, 95% CI: 0.22–0.98), and aVF (HR: 0.67, 95% CI: 0.58–0.87), decreased PWA in lead I (HR: 0.55, 95% CI: 0.21–0.76), lead II (HR: 0.48, 95% CI: 0.34–0.87), aVL (HR: 0.65, 95% CI: 0.45–0.96), and aVF (HR: 0.61, 95% CI: 0.32–0.89), and the presence of IAB (HR: 2, 95% CI: 1.4–4.2, p = 0.02). PWDisp and PTFV1 were not correlated with PVI outcome. Conclusions: PWDc, PWA, PWV, and IAB are valuable predictors for PVI outcome for PAF at 12 months.

1. Introduction

AF ablation with the goal of pulmonary vein isolation (PVI) has emerged as an effective rhythm control method for paroxysmal atrial fibrillation (PAF) [1]. This is mainly conducted by electrically isolating the pulmonary veins (PVs). During the last decade, the prevalence of AF in the UK has increased, and it is projected to grow within the following 30 years [2]. Pulmonary vein isolation (PVI) emerged as the standard of care in symptomatic AF during the last two decades when rhythm control was preferred [3]. Atrial cardiomyopathy is a recently defined condition encompassing changes in the macro and microstructure and various functional aspects of the atria, including the conduit, reservoir, electrical conduction, and contractile function [4,5]. Evidence strongly suggests that atrial cardiomyopathy, which is associated with a heightened risk of AF, is also linked to a greater incidence of AF-related complications such as heart failure, cognitive decline, ischaemic stroke, dementia, and mortality [6]. Notably, the impact of this condition on cognitive and cardiovascular health is distinct from its effects on AF, highlighting its unique prognostic significance. There is an urgent need to develop accurate methods for identifying these issues that can be easily used in a clinical setting. The 12-lead ECG, a conventional clinical tool, may be pivotal in detecting this condition.
The normal P wave, generated by the atria, has various measured parameters, including duration, morphology, voltage, spatial axis, and area. These parameters can be combined to form a P wave index (PWI), such as the morphology–voltage–P wave duration ECG (MVP ECG) risk score. Changes in these parameters, especially in duration and morphology, can indicate atrial chamber enlargement and conduction blocks and are considered risk factors for clinical events such as AF and ischaemic stroke. The predictive value of P wave parameters has been recognised for decades, with an advanced inter-atrial block (IAB) being described in the 1980s as a marker for the risk of AF or atrial flutter [7,8,9]. Furthermore, P wave parameters, including P wave duration (PWD) [10], P wave dispersion (PWDisp) [11], P wave voltage (PWV) [12], P wave terminal force in V1 (PTFV1) [13,14], and P wave area (PWA) [15] have been associated with AF, dementia, stroke, and death. Novel P wave markers were also correlated with AF ablation failure, including beat-to-beat variation, duration-to-amplitude ratio, and a notched P wave [16,17,18]. Modifying the electrical substrate has been suggested to change P wave parameters significantly. Hence, they have been used to predict PVI outcomes, which this study aimed for.

2. Material and Methods

2.1. Patient Selection and Data Collection

This retrospective observational cohort study included consecutive patients who had completed their first PVI for PAF between January 2018 and December 2019 in Glenfield Hospital, Leicester, UK. Patients taking amiodarone before the procedure were excluded as amiodarone could alter P wave morphology [19]. Patients with previous ablation procedures, patients with pacing devices, patients with valvular disease, patients with additional ablations outside PVs, and patients who did not complete their 12-month follow-up were also excluded. PVI was conducted by contact force radiofrequency ablation, or second-generation catheters were used for cryoballoon ablation. All involved patients had complete PVI with confirmed bidirectional block. Recurrence was defined by AF lasting for 30 s or more on Holter monitoring (24–72 h).
Patient demographics and medication details were obtained electronically by examining clinic appointment letters which provided clinical information, medications, ablation details, and follow-up appointments. Patients who had first-time PVI for PAF had continuous electronic monitoring. P wave parameters were measured before PVI and correlated with procedure success. PVI success was defined by the lack of ECG-documented AF or atrial flutter between 3 months (blanking period) and 12 months following ablation using 12-lead ECG or ambulatory monitoring. The study was reviewed and ethically approved by the University of Leicester ethical committee (reference number: 35479-ia196). The study was reported according to the STROBE guidelines [20].

2.2. Ablation Details

In the radiofrequency procedures, a circular mapping catheter was precisely deployed in the superior and inferior PVs, followed by circumferential ablation of the left-sided and right-sided ipsilateral PVs, all meticulously guided by three-dimensional left atrial mapping (CARTO3, Biosense-Webster, Irvine, CA, USA). The PVI was expertly conducted using a 3.5 mm ablation catheter with an externally irrigated tip (ThermoCool SmartTouch Catheter, Biosense-Webster, Diamond Bar, CA, USA), with ablation index guidance. Post-procedure, dormant conduction of the PVs was effectively examined using rapid adenosine triphosphate injection.
In cryoballoon ablation, a seamless transition from a long sheath (8.5 Fr SL0, Abbott Laboratories, Chicago, IL, USA) to a steerable sheath (FlexCath, Medtronic, Minneapolis, MN, USA) set the stage for the insertion of a second-generation cryoballoon (28 mm) into the LA over an inner-lumen circumferential mapping catheter (Achieve, Medtronic, Dublin, Ireland). The cryoballoon was meticulously frozen at the ostium of the superior/inferior left/right PVs. The goal of achieving a bidirectional conduction block between the left atrium and the PVs was pursued as the endpoint of the PVI procedure.

2.3. P Wave Analysis

In this study, 12-lead ECG tracings before, during, and after PVI were electronically archived with a resolution of 16 bits. Digital ECGs had a voltage range between 5 and −5 mV (range = 10 mV). The ECG data was filtered using a 1–50 hertz bandpass and a notch filter. One minute of digital ECG tracing directly before PVI and one minute of digital ECG tracing directly after PVI were exported (Figure 1) The ECG data file (1 min) was exported from LabSystems Pro, Massachusetts, USA in the format of .txt files and imported to Matlab for analysis. A digital bandpass filter (second-order Bessel filter) with a cut-off frequency of 1 hertz and 50 hertz was applied. The P wave peak was detected as the peak with a minimum duration/width of 15 ms in the window of interest for P wave peak detection.
The P wave onset detection window was defined from the T wave end to the P wave peak. P wave onset was detected and defined as the point with a minimum perpendicular distance to the line connecting the two T wave and P wave peak points. The MatLab script allows interactive operations, allowing the user to censor and adjust detected points using the computer. This process is demonstrated in Figure 1. Twenty P wave measurements were averaged to one number representing the P wave parameter in that lead. PWD was adjusted similarly to the QT interval adjustment using the Hodges formula. P wave beginning is defined by the first point of rise above the isoelectric line, while P wave peak is defined by the P wave point with the most vertical distance from the isoelectric line. These can be adjusted manually during the measurement process.
The following P wave parameters are produced:
  • PWD: Distance from P wave onset to offset. It represents atrial depolarization;
  • PWV: The area under the P wave was estimated using the trapezoidal method, which involves integrating the total area into a little trapezoid;
  • PWIDisp: The max difference between P wave durations;
  • PTFV1: The product of the maximum absolute amplitude and duration of the second half of the biphasic P wave in mm·s;
  • PWV: Can be calculated by 0.5 × PWD × PWV [7];
  • IAB: Defined by PWD ≥ 120 and a biphasic P wave morphology in leads III, II, or aVF [21].

2.4. Statistical Analysis

Categorical variables were expressed as frequency and percentage. The mean ± standard error of the mean was adopted to describe continuous parametric data. Pearson’s χ2 or Fisher’s exact tests were used for categorical variables between groups. Student’s t-tests and Mann–Whitney U tests were used to compare continuous variables, including P wave parameters, between the groups depending on the normality of the distribution.
A two-sided p-value < 0.05 was considered statistically significant. Statistical analyses were performed using GraphPad Prism V9.3 (San Diego, CA, USA).

2.5. Intraobserver Variability Test

There was a human factor in analysing the P wave and manually annotating the P wave’s start and end. Therefore, intraobserver variability tests were conducted to establish the data’s reproducibility. Twenty-two randomly selected 12-lead ECGs were analysed anonymously on two consecutive days. In total, 5280 P waves were analysed and compared twice in two days. Variability was calculated using raw numbers and a percentage. The results of the intraobserver variability showed the highest variability in the PWDisp measurement (4.5 ± 0.3 ms, 19%) followed by PWV (0.03 mV ± 0.001, 13%), PTFV1 (0.4 ± 0.1 mm·s, 10%), PWA (1 ± 0.2 ms·mV, 8%), and PWD (4.5 ± 0.3 ms, 4%).

3. Results

3.1. Patients Characteristics

After applying the inclusion and exclusion criteria, 211 PAF patients were involved in the final analysis, of which 154 patients (73%) had successful ablation at 12 months, and 81 patients (30%) had radiofrequency ablation. Table 1 demonstrates demographics stratified by procedure outcome. Males comprised 71% of the patients; the mean age was 61 ± 1.3 years. There was no statistically significant difference in age, diabetes mellitus, ischaemic heart disease, cerebrovascular events, hypertension, indexed left atrial volume, body mass index, and the type of antiarrhythmic drugs (ADDs) prescribed between both arms. However, more in the failed group were on long-term AADs (55% versus 25%, p < 0.001). The proportion of patients who had radiofrequency ablation and cryoballoon ablation did not differ between successful and failed PVIs.

3.2. P Wave Parameters

The PWDc results are demonstrated in Table 2. Increased PWDc was associated with PVI failure in lead I (hazard ratio [HR]: 2.1, 95% confidence interval [CI]: 1.3–4.3, p = 0.02), lead II (HR: 1.7, 95% CI: 1.1–3.9, p = 0.03), aVL (HR: 4.1, 95% CI: 2.1–7.3, p < 0.001), aVF (HR: 1.7, 95% CI: 1.2–4.5, p = 0.039), V1 (HR: 1.9, 95% CI: 1.3–4.5, p = 0.039), V2 (HR: 2.5, 95% CI: 1.6–5.3, p = 0.023), V4 (HR: 2.2, 95% CI: 1.4–5.8, p = 0.042), V5 (HR: 2, 95% CI: 1.3–7.4, p = 0.034), and V6 (HR: 3.8, 95% CI: 1.9–4.8, p < 0.001).
Table 3 demonstrates the PWV results. Lower PWV was associated with failed PVI in lead I (HR: 0.62, 95% CI: 0.22–0.93, p = 0.03), lead II (HR: 0.42, 95% CI: 0.13–0.76, p = 0.01), aVL (HR: 0.39, 95% CI: 0.24–0.83, p = 0.001), and aVF (HR: 0.56, 95% CI: 0.41–0.93, p = 0.032).
The PWDisp results in Table 4 did not show a statistically significant difference between both study arms. The PWA results are in Table 5. Lower PWA was associated with failed PVI in lead I (HR: 0.55, 95% CI: 0.21–0.76, p = 0.021), lead II (HR: 0.48, 95% CI: 0.34–0.87, p = 0.002), aVL (HR: 0.65, 95% CI: 0.45–0.96, p = 0.04), and aVF (HR: 0.61, 95% CI: 0.32–0.89, p = 0.04). PTFV1 was not statistically different before successful and failed ablation (HR: 1.1, 95% CI: 0.8–1.3, p = 0.86). The presence of IAB was associated with failed ablation (HR: 2, 95% CI: 1.4–4.2, p = 0.02).

4. Discussion

This is the first study to assess PWDc, PWA, PWV, IAB, and PWdisp in all 12 leads before PVI in correlation to the outcome of PAF patients. Furthermore, this is the first study that corrected P wave duration for heart rate to predict PVI outcome. This study proposes three main findings:
  • The PWDc increase in leads I, II, aVL, aVF, V1, V2, V4, V5, and V6 was associated with PVI failure at 12 months;
  • A decrease in PWV and PWA in leads I, II, aVL, and aVF was associated with PVI failure at 12 months;
  • The presence of IAB is correlated with PVI failure.
Recent research has focused on predicting PVI outcomes (Table 6). These generally included increased PWD and PWDisp. Other scoring systems for AF recurrence following AF, including the APPLE (age > 65 years, persistent AF, impaired kidney function, LA diameter ≥ 43 mm, left ventricular ejection fraction < 50% [22]) and MB-LATER scores (male, bundle branch block, LA diameter ≥ 47 mm, type of AF [paroxysmal, persistent, or long-standing persistent]) [23], could not be measured due to some within our PAF cohort without LA diameter (only LA volume) or information about bundle branch block.
Previous studies have assessed P wave parameters to determine whether they can predict new AF incidence [10], as the P wave represents atrial depolarisation and PV cardiac tissue excitation. Furthermore, PWDisp has been utilised to predict persistent AF progression from PAF [24]. With the increased PVI in clinical practice, several studies correlated P wave parameters before and after ablation to clinical outcomes, summarised in Table 7. These mainly included increased PWD, PWDisp, and PTFV1 as predictors of PVI failure. Furthermore, other markers were utilised to predict outcomes. For example, a study demonstrated that the beat-to-beat P wave index had a twofold risk for AF recurrence [17].
In our study, increased PWDc was correlated with procedure failure in leads I, II, aVF, aVL, V1, V2, V4, V5, and V6. PWD represents the time for electrical impulses to occur and spread through both atria. Understanding PWD is vital for diagnosing and managing conditions related to atrial activity. Our results are in line with those published by several authors [25,26,27,28,29,30,31,32,33,34,35,36,37]. Furthermore, a meta-analysis containing a total cohort of 1010 patients showed a highly significant association between prolonged PWD and AF recurrence after radiofrequency ablation (Z = 14.20, p < 0.000) [38]. High PWDc is seen with failed ablation. This is justified by the higher degree of remodelling and scarring in patients who went on to have failed ablations [39]. The fibrosis causes delayed intra-atrial and inter-atrial conduction, increasing PWD [40,41].
A recent study identified five factors related to ablation failure: female sex, left atrial appendage emptying flow velocity ≤ 31 cm/s, estimated glomerular filtration rate < 65.8 mL/(min·1.73 m2), PWD in lead aVF ≥ 120 ms, and P wave duration in lead V1 ≥ 100 ms, and constructed a nomogram [37]. This supports the hypothesis that AF recurrence is influenced by a complex interplay between atrial remodelling and demographics. Although our successful and failed PVIs had PWDc >100 ms and 120 ms in V1 and aVF, respectively, PWDc in failed ablations was significantly more prolonged than in successful ablations, supporting the same hypothesis (HR: 1.7 and 1.9, respectively). Increased PWDc indicates conduction delay signalling and extensive remodelling, which may reduce the effectiveness of ablation in restoring normal sinus rhythm. Also, it contributes to creating re-entrant circuits, wavefront collisions, and forming stable re-entrant pathways that are challenging to eliminate with ablation. This study did not use imaging studies to assess atrial fibrosis, but it would benefit future analysis. It is noted that the significant difference was not notable in some leads, including aVR. This can occur due to the heart’s unique anatomical orientation, the limited projection of the atrial depolarisation vector in this lead, and the baseline characteristics of the P wave in aVR. For example, leads II, III, aVF, and I are particularly relevant for assessing atrial depolarisation vectors and their changes concerning PVI outcomes because they align well with the typical direction of atrial depolarisation.
Decreased PWV in leads I, II, AVL, and aVF was associated with PVI failure. Although low-voltage areas signifying LA scarring were mainly detected in persistent AF in the literature, there is evidence that these areas are also seen in PAF [12,42]. These low-voltage areas can cause delayed conduction in the LA, often indicating underlying structural abnormalities such as fibrosis or scarring. These changes can create a more complex and heterogeneous electrical environment that is harder to modify or isolate during ablation. We observed that decreased PWA in leads I, II, AVL, and aVF was associated with PVI failure. A reduced PWA often indicates significant atrial remodelling, fibrosis, and impaired conduction. These factors contribute to less effective atrial depolarisation and could be a sign of advanced atrial disease. Such changes may also indicate a higher chance of ablation failure.
The PWDisp was not different between successful and failed PVIs. PWDisp is the difference between the maximum and the minimum PWD recorded from the ECG leads. It represents the inhomogeneous propagation of sinus impulses and prolonging inter-atrial and intra-atrial conduction time [43]. Previous studies summarized in Table 7 correlated PWDisp increase with failed PVI. These studies did not comment on the exact ablation technique used. PWDisp provides information about atrial conduction heterogeneity, with greater refractoriness variation and a shorter refractory period leading to AF recurrence [44]. According to a recent study, the PWDisp association with recurrence can also be explained by scar tissue formation identified by electroanatomical mapping [45]. Still, its lack of specificity, sensitivity, and measurement variability limits its predictive value for PVI outcomes. Inconsistent results further contribute to its limited predictive value as it can be affected by multiple factors, including cardiovascular, renal, respiratory, endocrine, and respiratory disorders [43]. Therefore, more comprehensive and integrative approaches are needed to predict PVI success in patients with PAF better using PWDisp.
IAB was associated with an increased risk for AF (HR 3.09, 95% CI 2.51 to 3.79) [46]. Also, in individuals aged 60 to 70 with cardiovascular disease, the 10-year risk of AF was 50% in those with advanced IAB compared with 10% in those with a normal P wave [47].
The PTFV1 before ablation was not different between successful and failed PVIs. PTFV1 was first described in 1964 [13] and was correlated with the LA volume in 1969 [48]. It represents the negative phase of the P wave in V1. It was considered abnormal when more than 0.03 mm·s [13]. The highest tertile of PTFV1 (78–97 ms) was associated with the highest risk of AF (HR 1.37; 95%, CI 1.23–1.52) and highest risk of stroke (HR 1.13; 95% CI 1.05–1.20) [49]. Also, another study suggested PTFV1 ≥0.06 mm·s was associated with an increased risk of death (HR: 1.76, 95% CI: 1.45–2.12, p < 0.001) and AF (HR: 1.91, 95% CI: 1.34–2.73, p < 0.001) [50].
PTFV1 was altered after PVI due to the loss of PV antrum signals [51], making it relevant before and after PVI [51]. Regarding the role of PTFV1 in predicting PVI, a previous study correlated PTFV1 < −0.04 mm·s with PVI failure for PAF [29]. Patients with failed PVI in the previous study were older and had larger LA volumes (known to cause abnormal PTFV1 [29]). This can explain the lack of difference in PTFV1 in our study. AF is a complex heart rhythm disorder involving multiple factors, such as electrical, structural, and autonomic changes in the atria. While PTFV1 (a measure of left atrial activation delay) is essential, it does not capture all aspects of AF, like focal triggers, re-entrant circuits, or atrial fibrosis. Additionally, comorbid conditions such as hypertension, diabetes, and other cardiovascular diseases can independently influence the success of PVI and affect PTFV1, making it difficult to assess the relationship between PTFV1 and ablation outcomes. In our study, patients who did not stop their AADs were likely to have failed PVIs. This can be explained by advanced atrial cardiomyopathy or the drugs that differently affect the action potentials that have become heterogeneous and, therefore, lead to the recurrence of AF after ablation [52,53].
This study was not conducted without its limitations. This is a single-centre retrospective study with AF recurrence detected using 12-lead ECG or ambulatory monitoring. Long-term monitoring (implantable loop recorder) was not conducted, and the AF burden was not evaluated. This could have missed subclinical and micro-AF episodes. Imaging studies for assessing LA fibrosis were not utilised. The relatively low sample size was not derived from formal power calculations, increasing the odds of a type 2 error because of the low power. Electroanatomical mapping of the LA was not obtained. Therefore, a correlation between low voltage areas and PWV was not conducted. Flecainide and sotalol used in our cohort could have affected PWD [52,53]. P wave axis and beat-to-beat were not technically possible in this study and are suggested to be performed in future studies.
Patients stopping their antiarrhythmic drugs were included in the analysis. Future studies must match patients with antiarrhythmic drugs and their cessation to limit confounding factors. The Hodges formula is currently not verified as a methodology in the literature to correct PWD for HR. A future dedicated study would help confirm the utility of this formula for future studies utilising PWD.
Table 6. Studies that demonstrated factors correlated with ablation failure for atrial fibrillation.
Table 6. Studies that demonstrated factors correlated with ablation failure for atrial fibrillation.
StudyCharacteristics Associated with Failed PVIComments
Themistoclakis et al., 2008 [54]Non-paroxysmal atrial fibrillation with duration ↑, hypertensionLonger AF duration (OR 1.03), history of hypertension (OR 1.32), left atrial enlargement (OR 1.55), permanent AF (OR 1.72), and lack of superior vena cava isolation (OR 1.60) were significantly associated with EAT. Independent predictors of LAT were longer AF duration (OR 1.03), history of hypertension (OR 1.65), persistent (OR 2.17) or permanent AF (OR 2.28), and occurrence of EAT (OR 30.62).
Tuan et al., 2010, Vermeersch et al., 2021 [55,56]Age ↑, 20% of elderly patients had meaningful ↓ QoL over one yearSubjects were divided into three groups according to their age, as follows: Group I: age ≤ 50 (n = 141), Group II: age = 51–64 (n = 149), and Group III: age ≥65 (n = 60).
The younger age group had a significantly smaller LA diameter (Group I vs. Group II vs. Group III, 36.89 ± 7.11 vs. 39.16 ± 5.65 vs. 40.77 ± 4.95 mm, p = 0.002) and higher LA bipolar voltage (2.09 ± 0.83 vs. 1.73 ± 0.73 vs. 1.86 ± 0.67 mV, respectively, p = 0.024), compared with the older AF patients.
Vermeersch et al., 2021: global 2 years efficacy of CB-A PVI in persAF is 43.4%. A lower success rate is achieved in the older patients (36.1%) (≥75 years) compared to the younger age group (47.0%)
Chao et al., 2010, Wang et al., 2020, Creta et al., 2020 [57,58,59]Diabetes mellitus, poor diabetes controlA total of 228 patients with paroxysmal AF who had undergone catheter ablation. Abnormal glucose metabolism (n = 65) was defined as diabetes mellitus or an impaired fasting glucose.
The AF recurrence rate was also greater in the patients with an abnormal glucose metabolism (18.5% vs. 8.0%, p = 0.022) than in those without.
Wang et al. 2020: arrhythmia recurrence was significantly higher in the DM group compared to the non-DM group after adjustment for baseline differences (adjusted hazard ratio [HR] 2.24; 95% confidence [CI] 1.42–3.55; p = 0.001).
Creta et al. 2020: DM was also an independent predictor of AF recurrence on the multivariate analysis (hazard ratio 1.39; 95% confidence interval 95%1.07 to 1.88; p = 0.016).
Chang et al., 2011 [60]Non-paroxysmal atrial fibrillation classificationVery early recurrences of AF occurred in 39 (15%) patients with paroxysmal AF and 26 (34%) with non-paroxysmal AF. Patients with very early recurrence had a higher incidence of non-paroxysmal AF (40% vs. 18.6%, p < 0.001), requirement of electrical cardioversion during the procedure, larger left atrial (LA) diameter (43 ± 7 vs. 39 ± 6 mm, p < 0.001), lower left ventricular ejection fraction (54 ± 10% vs. 59 ± 7, p < 0.001), longer procedural time, and lower LA voltage (1.5 ± 0.7 vs. 1.9 ± 0.8 mV, p < 0.001).
Ng et al., 2011a [61]Obstructive sleep apnoeaPatients with OSA have a 25% greater risk of AF recurrence after catheter ablation than those without OSA (risk ratio 1.25, 95% confidence interval 1.08 to 1.45, p = 0.003).
D’Ascenzo et al., 2013 [62]Recurrence within 30 days, valvular atrial fibrillationThe most powerful predictors of AF ablation failure in the overall population were a recurrence within 30 days (OR 4.30; 2.00–10.80), valvular AF (OR 5.20; 2.22–9.50), and a left atrium diameter of more than 50 mm (OR 5.10 2.00–12.90; all CI 95%).
Letsas et al., 2013 [63]CHA2DS2-Vasc ≥ 2
Li et al., 2014a [64]Chronic kidney disease (PAF patients were at higher risk)The meta-analysis of these studies showed that CKD was associated with higher AF recurrence rate following single catheter ablation (HR = 1.96, 95% CI 1.35–2.85, p = 0.0004).
A subgroup analysis showed that CKD has a higher recurrence risk in patients with 100% paroxysmal AF (HR = 2.45, 95% CI 1.28–4.70, p = 0.007) than in patients with non-100% paroxysmal AF (HR = 1.65, 95% CI 1.15–2.36, p = 0.006).
Qiao et al., 2015 [65]Alcohol intake ↑Daily alcohol consumption independently predicted the presence of LVZs (odds ratio [OR], 1.097; 95% confidence interval [CI], 1.001–1.203; p = 0.047). During a mean follow-up of 20.9 ± 5.9 months, 40 patients (35.1%) experienced AF recurrence. Success rates were 81.3%, 69.2%, and 35.1% in alcohol abstainers, moderate drinkers, and heavy drinkers, respectively (overall log rank, p < 0.001).
In conclusion, daily alcohol consumption was associated with atrial remodelling, and heavy drinkers have a substantial risk for AF recurrence after CPVI.
Sultan et al., 2017 [66]In hospital recurrence, females, non-paroxysmal atrial fibrillationThe multivariate analysis revealed that female sex and AF type prior to the procedure were predictors for AF recurrence. Furthermore, comorbidities such as valvular heart disease and renal failure as well as an early AF relapse were also predictors of AF recurrence during 1 y FU.
Pallisgaard et al., 2017 [67]Female sex, hypertension, atrial fibrillation duration >2 years, cardioversion < 1 year of ablationOne-year risk of recurrent AF following first-time ablation has almost halved from 2006 to 2014. Hypertension, female sex, cardioversion 1 year prior to ablation, and AF duration for more than 2 years all increased the associated risk of recurrent AF.
Winkle et al., 2017, Pranata et al., 2021 [68,69]Obesity, body mass index ≥35 kg/m2In patients undergoing AF ablation, increasing BMI is associated with more patient comorbidities and more persistent and long-standing AF. BMI ≥ 35 kg/m2 adversely impacts ablation outcomes, and BMI ≥ 40 kg/m2 increases minor complications.
There was a total of 52,771 patients from 20 studies. Obesity was associated with higher AF recurrence (odds ratio [OR] 1.30 [95% confidence interval [CI] 1.16–1.47], p < 0.001; I2: 72.7%) and similar rate of adverse events (OR 1.21 [95% CI 0.87–1.67], p = 0.264; I2: 23.9%).
Kuck et al., 2018, Li et al., 2020, Liu et al., 2021 [70,71,72]Female sex, height in femalesAfter catheter ablation of paroxysmal AF, female sex was associated with an almost 40% increase in the risks of primary efficacy failure and cardiovascular rehospitalization.
A total of 689 patients (470 males; age, 53.0 ± 11.7 years) with symptomatic paroxysmal AF receiving index catheter ablation (CA) between 2003 and 2013 were enrolled in this study.
Patients in the lower quartiles of height had a lower incidence of AF recurrence (log-rank p = 0.022). Height in female patients was strongly associated with AF recurrence (p = 0.027) after an index ablation in the 6.33 ± 4.32 years of follow-up.
Kim et al., 2020 [73]Anaemia before ablationNon-genetic risk factors for new-onset atrial fibrillation may have a similar impact on different age groups. Except for sex, these non-genetic risk factors can be modifiable.
Chew et al., 2020 [74]Diagnosis to ablation time ↑A total of 4950 participants undergoing AF ablation for symptomatic AF. A shorter DAT ≤ 1 year was associated with a lower relative risk of AF recurrence compared with DAT > 1 year (relative risk, 0.73 [95% CI, 0.65–0.82]; p < 0.001).
Wu et al., 2021b [75]Family history of atrial fibrillationAfter a mean follow-up of 26.2 ± 19.6 months, 318 out of the 645 patients (49.3%) with FAF and 3339 out of the 7553 patients (44.2%) without FAF experienced AT recurrence, corresponding to annual recurrence rates of 22.8% and 20.2%, respectively. Patients with FAF had a significantly higher risk of AT recurrence (adjusted hazard ratio 1.129, 95% confidence interval 1.005–1.267) in multivariable analysis.
McCready et al., 2011 [76]Left atrium size ↑Wide area circumferential ablation with linear and electrogram-based left atrial (LA) ablation was performed in 191 consecutive patients for persistent AF. After a mean follow-up of 13.0 ± 8.9 months, the overall success was 64% requiring a mean of 1.5 procedures. The single procedure success rate was 32%. Left atrial size was a univariate predictor of recurrence after a single procedure (p = 0.04). Only LA size [hazard ratio (HR) 1.05/mm with 95% confidential interval (CI) 1.02–1.08] was an independent predictor of recurrence after a single procedure. Only LA size was a univariate predictor of recurrence after multiple procedures (p < 0.01).
D’Ascenzo et al., 2013, Bergau et al., 2022 [62,77]Left atrium diameter ↑Patients with AF/AT recurrence were older (60 ± 8 vs. 57 ± 10 years; p = 0.019), had a higher CHA2DS2-Vasc score (2.47 ± 1.46 vs. 1.98 ± 1.50; p = 0.01) and presented with a larger left atrium (LA) diameter (43 ± 5.6 vs. 40 ± 5.1 mm; p = 0.002). The LA diameter was also a significant predictor for AF/AT recurrence after CB-PVI (odds ratio: 0.939, 95% confidence interval: [0.886, 0.992], p = 0.03).
Platek et al., 2020 [78]Visfatin ↑ (adipokine made by visceral fat which played a role in inflammation and fibrosis)Patients with AF recurrence had higher visfatin levels (1.7 ± 2.4 vs. 2.1 ± 1.9 ng/mL; p < 0.0001) and multivariate logistic regression analysis containing age, sex, and other independent variables showed that patients with elevated visfatin levels were almost three times more likely to experience AF recurrence (odds ratio 2.92; 95% confidence interval 1.60 to 5.32).
Yunpeng et al., 2020 [79]Low density lipid ↓, total cholesterol ↓ in femalesA total of 71 patients (24.7%) experienced AF recurrence during 3 to 12 months after ablation. By univariate Cox regression survival analysis, TC (HR, 0.63; 95%CI, 0.48–0.82), LDL-C (HR, 0.61; 95%CI, 0.44–0.84), non-paroxysmal AF type (HR, 2.56; 95%CI, 1.52–4.21), and left atrial diameter (HR, 2.18; 95%CI, 1.46–3.24) were significantly associated with AF recurrence.
Reyat et al., 2020 [80]mRNA plasma PITX2 ↑, mRNA LA PITX2 ↓ (cardiac transcription factor)Reduced left atrial cardiomyocyte PITX2 and elevated plasma concentrations of the PITX2-repressed, secreted atrial protein BMP10 identify patients at risk of recurrent AF after ablation.
Suehiro et al., 2021 [81]Intermediate monocytes ↑ (profibrotic marker)Intermediate monocytes were significantly positively correlated with SRM. PIM ≥ 10% was associated with a VR ≥ 13.3% on LGE-MRI, which predicted AF recurrence after catheter ablation.
Wang et al., 2021a [82]Carbohydrate antigen-125 ↑Of the 353 enrolled patients, 85 patients (24.1%) had AF recurrence at the 12-month follow-up. These patients had significantly higher baseline CA-125 levels than those without AF recurrence [(18.71 ± 12.63) vs. (11.27 ± 5.40) U/mL, p < 0.001].
Themistoclakis et al., 2008 [54]Non-paroxysmal atrial fibrillation with duration ↑, hypertensionEAT (within the first 3 months of ablation) developed in 514 (40%) patients and LAT (after 3 months post-ablation) in 292 (22%) patients.
Longer AF duration (OR 1.03), history of hypertension (OR 1.32), left atrial enlargement (OR 1.55), permanent AF (OR 1.72), and lack of superior vena cava isolation (OR 1.60) were significantly associated with EAT. Independent predictors of LAT were longer AF duration (OR 1.03), history of hypertension (OR 1.65), persistent (OR 2.17) or permanent AF (OR 2.28), and occurrence of EAT (OR 30.62).
Tuan et al., 2010, Vermeersch et al., 2021 [55,56]Age ↑, 20% of elderly patients had meaningful ↓ QoL over one yearSubjects were divided into three groups according to their age, as follows: Group I: age ≤ 50 (n = 141), Group II: age = 51–64 (n = 149), and Group III: age ≥ 65 (n = 60).
The younger age group had a significantly smaller LA diameter (Group I vs. Group II vs. Group III, 36.89 ± 7.11 vs. 39.16 ± 5.65 vs. 40.77 ± 4.95 mm, p = 0.002) and higher LA bipolar voltage (2.09 ± 0.83 vs. 1.73 ± 0.73 vs. 1.86 ± 0.67 mV, respectively, p = 0.024), compared with the older AF patients.
Vermeersch et al., 2021: global 2-year efficacy of CB-A PVI in persAF is 43.4%. A lower success rate is achieved in the older patients (36.1%) (≥75 years) compared to the younger age group (47.0%)
Chao et al., 2010, Wang et al., 2020, Creta et al., 2020 [57,58,59]Diabetes mellitus, poor diabetes controlA total of 228 patients with paroxysmal AF who had undergone catheter ablation… abnormal glucose metabolism (n = 65) was defined as diabetes mellitus or an impaired fasting glucose.
The AF recurrence rate was also greater in the patients with an abnormal glucose metabolism (18.5% vs. 8.0%, p = 0.022) than in those without.
Wang et al. 2020: arrhythmia recurrence was significantly higher in the DM group compared to the non-DM group after adjustment for baseline differences (HR 2.24; 95% CI: 1.42–3.55; p = 0.001).
Creta et al. 2020: DM was also an independent predictor of AF recurrence in the multivariate analysis (HR: 1.39; 95% confidence interval 95%1.07 to 1.88; p = 0.016).
OSA: obstructive sleep apnoea; DM: diabetes mellitus; AF: atrial fibrillation; HR: hazard ratio; CI: confidence interval; LDL: low density lipid; EAT: early atrial tachyarrhythmia; LAT: late atrial tachyarrhythmia.
Table 7. Previous studies that correlated P wave parameters to atrial fibrillation outcomes.
Table 7. Previous studies that correlated P wave parameters to atrial fibrillation outcomes.
Author and YearnRecurrenceCut-OffComments
(Jiang et al., 2006) [83]108↑ PWDisp In 108 consecutive patients (93 men, 15 women; mean age 51 +/− 8 years) with paroxysmal AF and no structural heart disease, segmental PVI guided by a Lasso catheter was performed. Forty-one percent (44/108) of AF patients had an early recurrence of AF after a single PVI. Univariate analysis revealed that left atrial diameter (p = 0.004), age (p = 0.024), and PWDisp (p = 0.045) were significantly related to the early recurrence of AF.
(Ogawa et al., 2007a) [26]27↑ PWD At baseline, the maximal P wave duration in patients without AF recurrence (161 +/− 7 ms) was slightly shorter than that in patients with AF recurrence (168 +/− 10 ms, p < 0.05). After ablation, patients without recurrence showed a significant reduction of P wave duration from 161 +/− 7 ms to 151 +/− 8 ms (p < 0.0001). In contrast, no change of P wave duration was noted in patients with recurrences.
(Okumura et al., 2007) [25]51↑ PWD>150 msFifteen patients suffered from AF recurrences 3 months or more after the PVI. The pre-filtered PWD was significantly longer in patients with recurrence than in those without (166.8 +/− 14.8 ms vs. 145.9 +/− 12.6 ms, p < 0.0001).
(Van Beeumen et al., 2010) [27]39↑ PWD≤5 ms changePWD was significantly shorter in cases of successful outcomes after catheter ablation.
(Caldwell et al., 2013) [28]100↑ PWD>140 msThe selective cohort consisted of 100 patients out of a total of 170 PVIs: age 58 ± 11 years, 72% male, left ventricular ejection fraction 62 ± 9%, 18% ischaemic heart disease, and 13% diabetic. Thirty-five had prolonged PWD, which was associated with greater AF recurrence rates compared to those without prolonged PWD (63 vs. 38%, p < 0.05).
(Salah et al., 2013) [29]198↑ PWDisp ↓ PTFV1
↑PWD		>40 ms
≤ −0.04 mV.ms
PWD > 120 ms		PWD ≥ 125 ms, PWDisp ≥ 40 ms, as well as a PTFV1≤ −0.04 mm/sec are good clinical predictors of the already known deleterious sequelae, mainly atrial fibrillation recurrence, post PVI in patients with paroxysmal atrial fibrillation; however, they were not independent from left atrial size and age.
(Blanche et al., 2013) [30]102↑PWDPWD > 140 msA filtered PWD >140 ms is a marker of AF recurrence after PVI and probably reflects the extent of atrial remodelling.
(Mugnai et al., 2016a) [31]426↑PWDisp
↑PWD		 Patients with a prolonged PWD had higher rates of atrial fibrillation recurrence compared with those without prolonged PWD (49 vs. 14%; p < 0.001). AF recurrence was significantly associated with prolonged PWD (129 ± 13 vs. 119 ± 11 ms; p < 0.001) and P wave dispersion (54 ± 12 vs. 42 ± 10 ms; p < 0.001) compared with those who remained in sinus rhythm.
(Hu et al., 2016) [32]171↑PWD PWD variation in lead II is an effective predictor of post-ablation AF recurrence.
(Wu et al., 2016) [84]204↑ PWD During the mean follow-up period of 13.9 ± 6.2 months (range, 3–27 months), 62 patients (30.4%) developed a recurrence of AF. The recurrence rate was higher in patients with advanced IAB than those without advanced IAB (46.3% vs. 26.4%, p = 0.006).
(Kanzaki et al., 2016) [85]76↑ PTFV1>9.3 mm·sDuring the mean follow-up of 10.2 months, AF recurred in 11 (14%) patients. The PTFV1 month after ablation was significantly higher in the recurrence group compared to that in the non-recurrence group (8.8 ± 3.1 mVms vs. 6.5 ± 2.9 mVms, p = 0.017). Higher PTFV1 after cryoballoon ablation was associated with poor prognosis during follow-up. The PTFV1 may be a useful and non-invasive marker to predict the recurrence of AF.
(Jadidi et al., 2018) [33]72↑ PWD>150 msPWD ≥150 ms during sinus rhythm measured prior to ablation identifies patients with persistent AF who are at increased risk for arrhythmia recurrence following PVI.
(Knecht et al., 2018) [34]129↑ PWD>120 msThe recurrence rate was significantly higher in patients with persistent AF, with a higher AF burden, with prolonged PWD, and with an indexed LA volume > 55 mL/m2. In multivariable analysis, AFB (hazard ratio: 2.018 (1.383–2.945), p > 0.001) and a prolonged P wave (hazard ratio: 2.612 (1.248–5.466), p = 0.011) were identified as significant predictors for AF recurrence.
(Yanagisawa et al., 2019) [86]115↓ Then ↑ PWD The reverse dynamics of PWD after initial shortening directly following ablation were significantly associated with PV reconnection.
(Auricchio et al., 2021) [87]282↓ PWD>110 msOne out of five patients referred for pulmonary vein isolation had a short PWD which was associated with a higher rate of AF after the index procedure. Computer simulations suggest that shortening of atrial action potential duration leading to a faster atrial conduction may be the cause of this clinical observation.
(Supanekar et al., 2021) [88]160PR↑ and PWD ↓ Shorter PWD combined with longer atrioventricular node delay, as measured by the proportion of the PR that the P wave occupies, was the best predictor of AF recurrence post-ablation.
(Ohguchi et al., 2021) [35]84↑ PWD≥120 msA total of 84 consecutive patients (47 with paroxysmal AF and 37 with persistent AF) who underwent PVI were included. PWD and amplitude in all leads were examined during sinus rhythm immediately after pulmonary vein isolation. During 12 months of follow-up, 20 patients experienced recurrence. The cut-off value of PWD > 120 ms in lead I showed a sensitivity of 75% and specificity of 69% for predicting recurrence. PWD was significantly correlated with left atrial volume, low voltage, and conduction velocity. Significantly higher recurrence rates were observed in patients with PWD > 120 ms than in those with PWD ≤ 120 ms (p < 0.001).
(Miao et al., 2022) [36]273↑ PWD In patients with early persistent AF who underwent the radiofrequency ablation procedure for the first time and converted to sinus rhythm, the PWD within 72 h after the procedure was independently associated with the risk of atrial fibrillation recurrence, and the association was linear and positive.
(Huang et al. 2023) [37]310PWD ↑ in V1 and aVF>120 ms aVF, >100 ms V1Five factors related to ablation failure were as follows: female sex, left atrial appendage emptying flow velocity ≤31 cm/s, estimated glomerular filtration rate <65.8 mL/(min·1.73 m2), P wave duration in lead aVF ≥ 120 ms, and that in lead V1 ≥ 100 ms.
PWD: P wave duration; PWdisp: P wave dispersion; PTFV1: P wave terminal force in V1; PVI: pulmonary vein isolation; LA: left atrium; AF: atrial fibrillation.

5. Conclusions

The factors associated with PVI failure for PAF include the presence of IAB, increased PWDc, decreased PWV, and decreased PWA, while PWDisp and PTFV1 were not predictive of PVI outcomes.

Author Contributions

I.A.: Conceptualization, methodology, validation, and formal analysis were used to collect the data. X.L.: validation, software, data curation. A.K., Z.V., A.A., A.I.K., A.M., A.N. (Ali Nizam), H.E., I.K., A.N. (André Ng) and R.S.: writing—review and editing. A.N. (André Ng): supervision, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of the University of Leicester (protocol code 35479-ia196, 11 August 2022).

Informed Consent Statement

The project was conducted and approved by the University of Leicester (reference number: 35479-ia196) and involved prospective analysis of retrospectively collected anonymised data. Therefore, the need for consent was waived.

Data Availability Statement

Data relating to this study are available upon reasonable request from the corresponding author.

Acknowledgments

GA Ng is supported by a British Heart Foundation Programme Grant (RG/17/3/32,774) and the Medical Research Council Biomedical Catalyst Developmental Pathway Funding Scheme (MR/S037306/1).

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Cosedis Nielsen, J.; Johannessen, A.; Raatikainen, P.; Hindricks, G.; Walfridsson, H.; Kongstad, O.; Pehrson, S.; Englund, A.; Hartikainen, J.; Mortensen, L.S.; et al. Radiofrequency ablation as initial therapy in paroxysmal atrial fibrillation. N. Engl. J. Med. 2012, 367, 1587–1595. [Google Scholar] [CrossRef]
  2. Lippi, G.; Sanchis-Gomar, F.; Cervellin, G. Global epidemiology of atrial fibrillation: An increasing epidemic and public health challenge. Int. J. Stroke 2020, 16, 217–221. [Google Scholar] [CrossRef]
  3. Mulder, B.A.; Luermans, J.G.; Hindricks, G.; Blaauw, Y. Innovations and paradigm shifts in atrial fibrillation ablation. EP Eur. 2021, 23, ii23–ii27. [Google Scholar] [CrossRef] [PubMed]
  4. Goldberger, J.J.; Arora, R.; Green, D.; Greenland, P.; Lee, D.C.; Lloyd-Jones, D.M.; Markl, M.; Ng, J.; Shah, S.J. Evaluating the atrial myopathy underlying atrial fibrillation: Identifying the arrhythmogenic and thrombogenic substrate. Circulation 2015, 132, 278–291. [Google Scholar] [CrossRef] [PubMed]
  5. Goette, A.; Kalman, J.M.; Aguinaga, L.; Akar, J.; Cabrera, J.A.; Chen, S.A.; Chugh, S.S.; Corradi, D.; D’avila, A.; Dobrev, D. EHRA/HRS/APHRS/SOLAECE expert consensus on atrial cardiomyopathies: Definition, characterization, and clinical implication. Heart Rhythm 2017, 14, e3–e40. [Google Scholar] [CrossRef] [PubMed]
  6. Kamel, H.; Okin, P.M.; Longstreth Jr, W.; Elkind, M.S.; Soliman, E.Z. Atrial cardiopathy: A broadened concept of left atrial thromboembolism beyond atrial fibrillation. Future Cardiol. 2015, 11, 323–331. [Google Scholar] [CrossRef]
  7. Chen, L.Y.; Ribeiro, A.L.P.; Platonov, P.G.; Cygankiewicz, I.; Soliman, E.Z.; Gorenek, B.; Ikeda, T.; Vassilikos, V.P.; Steinberg, J.S.; Varma, N. P wave parameters and indices: A critical appraisal of clinical utility, challenges, and future research—A consensus document endorsed by the International Society of Electrocardiology and the International Society for Holter and Noninvasive Electrocardiology. Circ. Arrhythmia Electrophysiol. 2022, 15, e010435. [Google Scholar]
  8. de Luna, A.B.; Oter, M.C.R.; Guindo, J. Interatrial conduction block with retrograde activation of the left atrium and paroxysmal supraventricular tachyarrhythmias: Influence of preventive antiarrhythmic treatment. Int. J. Cardiol. 1989, 22, 147–150. [Google Scholar] [CrossRef]
  9. Alexander, B.; Milden, J.; Hazim, B.; Haseeb, S.; Bayes-Genis, A.; Elosua, R.; Martínez-Sellés, M.; Yeung, C.; Hopman, W.; Bayes de Luna, A. New electrocardiographic score for the prediction of atrial fibrillation: The MVP ECG risk score (morphology-voltage-P-wave duration). Ann. Noninvasive Electrocardiol. 2019, 24, e12669. [Google Scholar] [CrossRef]
  10. Nielsen, J.B.; Kühl, J.T.; Pietersen, A.; Graff, C.; Lind, B.; Struijk, J.J.; Olesen, M.S.; Sinner, M.F.; Bachmann, T.N.; Haunsø, S.; et al. P-wave duration and the risk of atrial fibrillation: Results from the Copenhagen ECG Study. Heart Rhythm 2015, 12, 1887–1895. [Google Scholar] [CrossRef]
  11. Dilaveris, P.E.; Gialafos, J.E. P-Wave Dispersion: A Novel Predictor of Paroxysmal Atrial Fibrillation. Ann. Noninvasive Electrocardiol. 2001, 6, 159–165. [Google Scholar] [CrossRef] [PubMed]
  12. Park, J.-K.; Park, J.; Uhm, J.-S.; Joung, B.; Lee, M.-H.; Pak, H.-N. Low P-wave amplitude (<0.1 mV) in lead I is associated with displaced inter-atrial conduction and clinical recurrence of paroxysmal atrial fibrillation after radiofrequency catheter ablation. Europace 2016, 18, 384–391. [Google Scholar] [PubMed]
  13. Morris, J.J., Jr.; Estes, E.H., Jr.; Whalen, R.E.; Thompson, H.K., Jr.; McIntosh, H.D. P-Wave Analysis in Valvular Heart Disease. Circulation 1964, 29, 242–252. [Google Scholar] [CrossRef]
  14. Gutierrez, A.; Norby, F.L.; Maheshwari, A.; Rooney, M.R.; Gottesman, R.F.; Mosley, T.H.; Lutsey, P.L.; Oldenburg, N.; Soliman, E.Z.; Alonso, A. Association of abnormal P-wave indices with dementia and cognitive decline over 25 years: ARIC-NCS (the atherosclerosis risk in communities neurocognitive study). J. Am. Heart Assoc. 2019, 8, e014553. [Google Scholar] [CrossRef]
  15. Zeng, C.; Wei, T.; Zhao, R.; Wang, C.; Chen, L.; Wang, L. Electrocardiographic diagnosis of left atrial enlargement in patients with mitral stenosis: The value of the P-wave area. Acta Cardiol. 2003, 58, 139–141. [Google Scholar] [CrossRef]
  16. Doğduş, M.; Turan, O.E.; Başkurt, A.A.; Yılancıoğlu, R.Y.; Özgül, U.; İnevi, U.D.; Özcan, E.E. An Effective Novel Index for Predicting the Recurrence of Atrial Fibrillation Ablation: P Wave Duration-to-Amplitude Ratio. Turk. Kardiyol. Dern. Ars. 2022, 50, 498–504. [Google Scholar] [CrossRef] [PubMed]
  17. Tachmatzidis, D.; Tsarouchas, A.; Mouselimis, D.; Filos, D.; Antoniadis, A.P.; Lysitsas, D.N.; Mezilis, N.; Sakellaropoulou, A.; Giannopoulos, G.; Bakogiannis, C. P-wave beat-to-beat analysis to predict atrial fibrillation recurrence after catheter ablation. Diagnostics 2022, 12, 830. [Google Scholar] [CrossRef] [PubMed]
  18. Okuyama, T.; Kabutoya, T.; Kario, K. Notched P-wave on digital electrocardiogram predicts the recurrence of atrial fibrillation in patients who have undergone catheter ablation. J. Arrhythm. 2024, 40, 472–478. [Google Scholar] [CrossRef]
  19. Burashnikov, A.; Di Diego, J.M.; Sicouri, S.; Ferreiro, M.; Carlsson, L.; Antzelevitch, C. Atrial-selective effects of chronic amiodarone in the management of atrial fibrillation. Heart Rhythm 2008, 5, 1735–1742. [Google Scholar] [CrossRef]
  20. Vandenbroucke, J.P.; Von Elm, E.; Altman, D.G.; Gøtzsche, P.C.; Mulrow, C.D.; Pocock, S.J.; Poole, C.; Schlesselman, J.J.; Egger, M.; Initiative, S. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and elaboration. PLoS Med. 2007, 4, e297. [Google Scholar] [CrossRef]
  21. de Luna, A.B.; Escobar-Robledo, L.A.; Aristizabal, D.; Restrepo, D.W.; Mendieta, G.; van Roessel, A.M.; Elosua, R.; Bayés-Genís, A.; Martínez-Sellés, M.; Baranchuk, A. Atypical advanced interatrial blocks: Definition and electrocardiographic recognition. J. Electrocardiol. 2018, 51, 1091–1093. [Google Scholar] [CrossRef] [PubMed]
  22. Kornej, J.; Hindricks, G.; Shoemaker, M.B.; Husser, D.; Arya, A.; Sommer, P.; Rolf, S.; Saavedra, P.; Kanagasundram, A.; Patrick Whalen, S. The APPLE score: A novel and simple score for the prediction of rhythm outcomes after catheter ablation of atrial fibrillation. Clin. Res. Cardiol. 2015, 104, 871–876. [Google Scholar] [CrossRef] [PubMed]
  23. Mujović, N.; Marinković, M.; Marković, N.; Shantsila, A.; Lip, G.Y.; Potpara, T.S. Prediction of very late arrhythmia recurrence after radiofrequency catheter ablation of atrial fibrillation: The MB-LATER clinical score. Sci. Rep. 2017, 7, 40828. [Google Scholar] [CrossRef] [PubMed]
  24. Koide, Y.; Yotsukura, M.; Ando, H.; Aoki, S.; Suzuki, T.; Sakata, K.; Ootomo, E.; Yoshino, H. Usefulness of P-Wave Dispersion in Standard Twelve-Lead Electrocardiography to Predict Transition from Paroxysmal to Persistent Atrial Fibrillation. Am. J. Cardiol. 2008, 102, 573–577. [Google Scholar] [CrossRef]
  25. Ogawa, M.; Kumagai, K.; Vakulenko, M.; Yasuda, T.; Siegerman, C.; Garfinkel, A.; Chen, P.S.; Saku, K. Reduction of P-wave duration and successful pulmonary vein isolation in patients with atrial fibrillation. J. Cardiovasc. Electrophysiol. 2007, 18, 931–938. [Google Scholar] [CrossRef]
  26. Okumura, Y.; Watanabe, I.; Ohkubo, K.; Ashino, S.; Kofune, M.; Hashimoto, K.; Shindo, A.; Sugimura, H.; Nakai, T.; Kasamaki, Y. Prediction of the efficacy of pulmonary vein isolation for the treatment of atrial fibrillation by the signal-averaged P-wave duration. Pacing Clin. Electrophysiol. 2007, 30, 304–313. [Google Scholar] [CrossRef]
  27. Van Beeumen, K.; Houben, R.; Tavernier, R.; Ketels, S.; Duytschaever, M. Changes in P-wave area and P-wave duration after circumferential pulmonary vein isolation. Europace 2010, 12, 798–804. [Google Scholar] [CrossRef]
  28. Caldwell, J.; Koppikar, S.; Barake, W.; Redfearn, D.; Michael, K.; Simpson, C.; Hopman, W.; Baranchuk, A. Prolonged P Wave Duration Is Associated With a Need for Substrate Ablation at Redo AF Ablation. Can. J. Cardiol. 2013, 29, S231–S232. [Google Scholar] [CrossRef]
  29. Salah, A.; Zhou, S.; Liu, Q.; Yan, H. P wave indices to predict atrial fibrillation recurrences post pulmonary vein isolation. Arq. Bras. Cardiol. 2013, 101, 519–527. [Google Scholar] [CrossRef]
  30. Blanche, C.; Tran, N.; Rigamonti, F.; Burri, H.; Zimmermann, M. Value of P-wave signal averaging to predict atrial fibrillation recurrences after pulmonary vein isolation. Europace 2013, 15, 198–204. [Google Scholar] [CrossRef]
  31. Mugnai, G.; Chierchia, G.-B.; De Asmundis, C.; Juliá, J.; Conte, G.; Sieira-Moret, J.; Capulzini, L.; Wauters, K.; Rodriguez-Mañero, M.; Ciconte, G. P-wave indices as predictors of atrial fibrillation recurrence after pulmonary vein isolation in normal left atrial size. J. Cardiovasc. Med. 2016, 17, 194–200. [Google Scholar] [CrossRef] [PubMed]
  32. Hu, X.; Jiang, J.; Ma, Y.; Tang, A. Novel P wave indices to predict atrial fibrillation recurrence after radiofrequency ablation for paroxysmal atrial fibrillation. Med. Sci. Monit. Int. Med. J. Exp. Clin. Res. 2016, 22, 2616. [Google Scholar] [CrossRef]
  33. Jadidi, A.; Müller-Edenborn, B.; Chen, J.; Keyl, C.; Weber, R.; Allgeier, J.; Moreno-Weidmann, Z.; Trenk, D.; Neumann, F.-J.; Lehrmann, H. Amplified Sinus P-Wave Duration in Persistent Atrial Fibrillation: Identification of Left Atrial Low-Voltage Substrate and Outcome Prediction After Pulmonary Vein Isolation. JACC Clin. Electrophysiol. 2018, 4, 531–543. [Google Scholar] [CrossRef]
  34. Knecht, S.; Pradella, M.; Reichlin, T.; Mühl, A.; Bossard, M.; Stieltjes, B.; Conen, D.; Bremerich, J.; Osswald, S.; Kühne, M. Left atrial anatomy, atrial fibrillation burden, and P-wave duration—Relationships and predictors for single-procedure success after pulmonary vein isolation. EP Eur. 2018, 20, 271–278. [Google Scholar] [CrossRef]
  35. Ohguchi, S.; Inden, Y.; Yanagisawa, S.; Shigematsu, T.; Yasuda, K.; Katagiri, K.; Oguri, M.; Murohara, T. Long P-wave duration immediately after pulmonary vein isolation on radiofrequency catheter ablation for atrial fibrillation predicts clinical recurrence: Correlation with atrial remodeling in persistent atrial fibrillation. Heart Vessel. 2022, 37, 476–488. [Google Scholar] [CrossRef]
  36. Miao, Y.; Xu, M.; Yang, L.; Zhang, C.; Liu, H.; Shao, X. Investigating the association between P wave duration and atrial fibrillation recurrence after radiofrequency ablation in early persistent atrial fibrillation patients. Int. J. Cardiol. 2022, 351, 48–54. [Google Scholar] [CrossRef] [PubMed]
  37. Huang, J.; Chen, H.; Zhang, Q.; Yang, R.; Peng, S.; Wu, Z.; Liu, N.; Tang, L.; Liu, Z.; Zhou, S. Development and Validation of a Novel Prognostic Tool to Predict Recurrence of Paroxysmal Atrial Fibrillation after the First-Time Catheter Ablation: A Retrospective Cohort Study. Diagnostics 2023, 13, 1207. [Google Scholar] [CrossRef] [PubMed]
  38. Wang, Y.S.; Chen, G.Y.; Li, X.H.; Zhou, X.; Li, Y.G. Prolonged P-wave duration is associated with atrial fibrillation recurrence after radiofrequency catheter ablation: A systematic review and meta-analysis. Int. J. Cardiol. 2017, 227, 355–359. [Google Scholar] [CrossRef]
  39. Chen, Q.; Mohanty, S.; Trivedi, C.; Gianni, C.; Della Rocca, D.G.; Canpolat, U.; Burkhardt, J.D.; Sanchez, J.E.; Hranitzky, P.; Gallinghouse, G.J.; et al. Association between prolonged P wave duration and left atrial scarring in patients with paroxysmal atrial fibrillation. J. Cardiovasc. Electrophysiol. 2019, 30, 1811–1818. [Google Scholar] [CrossRef]
  40. Alcaraz, R.; Martínez, A.; Rieta, J.J. The P Wave Time-Frequency Variability Reflects Atrial Conduction Defects before Paroxysmal Atrial Fibrillation. Ann. Noninvasive Electrocardiol. 2015, 20, 433–445. [Google Scholar] [CrossRef]
  41. Higuchi, S.; Ejima, K.; Shoda, M.; Yamamoto, E.; Iwanami, Y.; Yagishita, D.; Hagiwara, N. Impact of a prolonged interatrial conduction time for predicting the recurrence of atrial fibrillation after circumferential pulmonary vein isolation of persistent atrial fibrillation. Heart Vessel. 2019, 34, 616–624. [Google Scholar] [CrossRef] [PubMed]
  42. Rolf, S.; Kircher, S.; Arya, A.; Eitel, C.; Sommer, P.; Richter, S.; Gaspar, T.; Bollmann, A.; Altmann, D.; Piedra, C. Tailored atrial substrate modification based on low-voltage areas in catheter ablation of atrial fibrillation. Circ. Arrhythmia Electrophysiol. 2014, 7, 825–833. [Google Scholar] [CrossRef] [PubMed]
  43. Pérez-Riera, A.R.; de Abreu, L.C.; Barbosa-Barros, R.; Grindler, J.; Fernandes-Cardoso, A.; Baranchuk, A. P-wave dispersion: An update. Indian Pacing Electrophysiol. J. 2016, 16, 126–133. [Google Scholar] [CrossRef]
  44. Misier, A.R.; Opthof, T.; van Hemel, N.M.; Defauw, J.J.; de Bakker, J.M.; Janse, M.J.; van Capelle, F.J. Increased dispersion of “refractoriness” in patients with idiopathic paroxysmal atrial fibrillation. J. Am. Coll. Cardiol. 1992, 19, 1531–1535. [Google Scholar] [CrossRef] [PubMed]
  45. Baskovski, E.; Altin, A.T.; Candemir, B.; Akyurek, O.; Esenboga, K.; Tutar, E. Relationship between left atrial scar and P wave dispersion in patients undergoing atrial fibrillation catheter ablation. Acta Cardiol. 2022, 77, 586–592. [Google Scholar] [CrossRef]
  46. Skov, M.W.; Ghouse, J.; Kühl, J.T.; Platonov, P.G.; Graff, C.; Fuchs, A.; Rasmussen, P.V.; Pietersen, A.; Nordestgaard, B.G.; Torp-Pedersen, C. Risk prediction of atrial fibrillation based on electrocardiographic interatrial block. J. Am. Heart Assoc. 2018, 7, e008247. [Google Scholar] [CrossRef]
  47. O’Neal, W.T.; Zhang, Z.-M.; Loehr, L.R.; Chen, L.Y.; Alonso, A.; Soliman, E.Z. Electrocardiographic advanced interatrial block and atrial fibrillation risk in the general population. Am. J. Cardiol. 2016, 117, 1755–1759. [Google Scholar] [CrossRef]
  48. Kasser, I.; Kennedy, J.W. The Relationship of Increased Left Atrial Volume and Pressure to Abnormal P Waves on the Electrocardiogram. Circulation 1969, 39, 339–343. [Google Scholar] [CrossRef]
  49. Wolder, L.D.; Graff, C.; Baadsgaard, K.H.; Langgaard, M.L.; Polcwiartek, C.; Lee, C.J.-Y.; Skov, M.W.; Torp-Pedersen, C.; Friedman, D.J.; Atwater, B. Electrocardiographic P terminal force in lead V1, its components, and the association with stroke and atrial fibrillation or flutter. Heart Rhythm 2023, 20, 354–362. [Google Scholar] [CrossRef]
  50. Eranti, A.; Aro Aapo, L.; Kerola, T.; Anttonen, O.; Rissanen Harri, A.; Tikkanen Jani, T.; Junttila, M.J.; Kenttä Tuomas, V.; Knekt, P.; Huikuri Heikki, V. Prevalence and Prognostic Significance of Abnormal P Terminal Force in Lead V1 of the ECG in the General Population. Circ. Arrhythmia Electrophysiol. 2014, 7, 1116–1121. [Google Scholar] [CrossRef]
  51. Janin, S.; Wojcik, M.; Kuniss, M.; Berkowitsch, A.; Erkapic, D.; Zaltsberg, S.; Ecarnot, F.; Hamm, C.W.; Pitschner, H.F.; Neumann, T. Pulmonary vein antrum isolation and terminal part of the P wave. Pacing Clin. Electrophysiol. 2010, 33, 784–789. [Google Scholar] [CrossRef]
  52. Redfearn, D.P.; Skanes, A.C.; Gula, L.J.; Griffith, M.J.; Marshall, H.J.; Stafford, P.J.; Krahn, A.D.; Yee, R.; Klein, G.J. Noninvasive Assessment of Atrial Substrate Change after Wide Area Circumferential Ablation: A Comparison with Segmental Pulmonary Vein Isolation. Ann. Noninvasive Electrocardiol. 2007, 12, 329–337. [Google Scholar] [CrossRef]
  53. Telichowski, A.; Banasiak, W.; Wiech, K.; Zeborowski, J.; Pierog, M.; Ponikowski, P.; Kałka, D.; Lacheta, W.; Fuglewicz, A.; Telichowski, C. The effect of sotalol hydrochloride therapy on atrial signal-averaged ECG in patients with paroxysmal atrial fibrillation. Pol. Merkur. Lek. Organ Pol. Tow. Lek. 1996, 1, 303–309. [Google Scholar]
  54. Themistoclakis, S.; Schweikert, R.A.; Saliba, W.I.; Bonso, A.; Rossillo, A.; Bader, G.; Wazni, O.; Burkhardt, D.J.; Raviele, A.; Natale, A. Clinical predictors and relationship between early and late atrial tachyarrhythmias after pulmonary vein antrum isolation. Heart Rhythm 2008, 5, 679–685. [Google Scholar] [CrossRef]
  55. Tuan, T.C.; Chang, S.L.; Tsao, H.M.; Tai, C.T.; Lin, Y.J.; Hu, Y.F.; Lo, L.W.; Udyavar, A.R.; Chang, C.J.; Tsai, W.C. The impact of age on the electroanatomical characteristics and outcome of catheter ablation in patients with atrial fibrillation. J. Cardiovasc. Electrophysiol. 2010, 21, 966–972. [Google Scholar] [CrossRef] [PubMed]
  56. Vermeersch, G.; Abugattas, J.P.; Varnavas, V.; De Cocker, J.; Schwagten, B.; Sieira, J.; de Asmundis, C.; Chierchia, G.B.; De Greef, Y. Efficacy and safety of the second-generation cryoballoon ablation for the treatment of persistent atrial fibrillation in elderly patients. J. Arrhythmia 2021, 37, 626–634. [Google Scholar] [CrossRef]
  57. Chao, T.-F.; Suenari, K.; Chang, S.-L.; Lin, Y.-J.; Lo, L.-W.; Hu, Y.-F.; Tuan, T.-C.; Tai, C.-T.; Tsao, H.-M.; Li, C.-H.; et al. Atrial Substrate Properties and Outcome of Catheter Ablation in Patients With Paroxysmal Atrial Fibrillation Associated With Diabetes Mellitus or Impaired Fasting Glucose. Am. J. Cardiol. 2010, 106, 1615–1620. [Google Scholar] [CrossRef] [PubMed]
  58. Wang, A.; Truong, T.; Black-Maier, E.; Green, C.; Campbell, K.B.; Barnett, A.S.; Febre, J.; Loring, Z.; Al-Khatib, S.M.; Atwater, B.D.; et al. Catheter ablation of atrial fibrillation in patients with diabetes mellitus. Heart Rhythm O2 2020, 1, 180–188. [Google Scholar] [CrossRef] [PubMed]
  59. Creta, A.; Providência, R.; Adragão, P.; de Asmundis, C.; Chun, J.; Chierchia, G.; Defaye, P.; Schmidt, B.; Anselme, F.; Finlay, M. Impact of type-2 diabetes mellitus on the outcomes of catheter ablation of atrial fibrillation (European observational multicentre study). Am. J. Cardiol. 2020, 125, 901–906. [Google Scholar] [CrossRef]
  60. Chang, S.L.; Tsao, H.M.; Lin, Y.J.; Lo, L.W.; Hu, Y.F.; Tuan, T.C.; Suenari, K.; Tai, C.T.; Li, C.H.; Chao, T.F.; et al. Characteristics and significance of very early recurrence of atrial fibrillation after catheter ablation. J. Cardiovasc. Electrophysiol. 2011, 22, 1193–1198. [Google Scholar] [CrossRef]
  61. Ng, C.Y.; Liu, T.; Shehata, M.; Stevens, S.; Chugh, S.S.; Wang, X. Meta-analysis of obstructive sleep apnea as predictor of atrial fibrillation recurrence after catheter ablation. Am. J. Cardiol. 2011, 108, 47–51. [Google Scholar] [CrossRef]
  62. D’Ascenzo, F.; Corleto, A.; Biondi-Zoccai, G.; Anselmino, M.; Ferraris, F.; di Biase, L.; Natale, A.; Hunter, R.J.; Schilling, R.J.; Miyazaki, S.; et al. Which are the most reliable predictors of recurrence of atrial fibrillation after transcatheter ablation?: A meta-analysis. Int. J. Cardiol. 2013, 167, 1984–1989. [Google Scholar] [CrossRef] [PubMed]
  63. Letsas, K.P.; Efremidis, M.; Giannopoulos, G.; Deftereos, S.; Lioni, L.; Korantzopoulos, P.; Vlachos, K.; Xydonas, S.; Kossyvakis, C.; Sideris, A. CHADS2 and CHA2DS2-VASc scores as predictors of left atrial ablation outcomes for paroxysmal atrial fibrillation. EP Eur. 2013, 16, 202–207. [Google Scholar] [CrossRef]
  64. Li, M.; Liu, T.; Luo, D.; Li, G. Systematic review and meta-analysis of chronic kidney disease as predictor of atrial fibrillation recurrence following catheter ablation. Cardiol. J. 2014, 21, 89–95. [Google Scholar] [CrossRef]
  65. Qiao, Y.; Shi, R.; Hou, B.; Wu, L.; Zheng, L.; Ding, L.; Chen, G.; Zhang, S.; Yao, Y. Impact of alcohol consumption on substrate remodeling and ablation outcome of paroxysmal atrial fibrillation. J. Am. Heart Assoc. 2015, 4, e002349. [Google Scholar] [CrossRef]
  66. Sultan, A.; Lüker, J.; Andresen, D.; Kuck, K.; Hoffmann, E.; Brachmann, J.; Hochadel, M.; Willems, S.; Eckardt, L.; Lewalter, T. Predictors of atrial fibrillation recurrence after catheter ablation: Data from the German Ablation Registry. Sci. Rep. 2017, 7, 16678. [Google Scholar] [CrossRef] [PubMed]
  67. Pallisgaard, J.L.; Gislason, G.H.; Hansen, J.; Johannessen, A.; Torp-Pedersen, C.; Rasmussen, P.V.; Hansen, M.L. Temporal trends in atrial fibrillation recurrence rates after ablation between 2005 and 2014: A nationwide Danish cohort study. Eur. Heart J. 2017, 39, 442–449. [Google Scholar] [CrossRef]
  68. Winkle, R.A.; Mead, R.H.; Engel, G.; Kong, M.H.; Fleming, W.; Salcedo, J.; Patrawala, R.A. Impact of obesity on atrial fibrillation ablation: Patient characteristics, long-term outcomes, and complications. Heart Rhythm 2017, 14, 819–827. [Google Scholar] [CrossRef]
  69. Pranata, R.; Henrina, J.; Yonas, E.; Putra, I.C.; Cahyadi, I.; Lim, M.A.; Munawar, D.A.; Munawar, M. BMI and atrial fibrillation recurrence post catheter ablation: A dose-response meta-analysis. Eur. J. Clin. Investig. 2021, 51, e13499. [Google Scholar] [CrossRef]
  70. Kuck, K.-H.; Brugada, J.; Fürnkranz, A.; Chun, K.J.; Metzner, A.; Ouyang, F.; Schlüter, M.; Elvan, A.; Braegelmann, K.M.; Kueffer, F.J. Impact of female sex on clinical outcomes in the FIRE AND ICE trial of catheter ablation for atrial fibrillation. Circ. Arrhythmia Electrophysiol. 2018, 11, e006204. [Google Scholar] [CrossRef]
  71. Li, J.; Sang, C.; Du, X.; He, L.; Lu, S.; Jiang, C.; Xia, S.; Chang, S.; Zuo, S.; Guo, X. Effectiveness and safety of atrial fibrillation ablation in females. Pacing Clin. Electrophysiol. 2020, 43, 583–592. [Google Scholar] [CrossRef]
  72. Liu, C.-H.; Lo, L.-W.; Chung, F.-P.; Chang, S.-L.; Hu, Y.-F.; Lin, Y.-J.; Huang, S.-C.; Gan, S.-T.; Lin, C.-Y.; Chao, T.-F. The impact of height on recurrence after index catheter ablation of paroxysmal atrial fibrillation. J. Interv. Card. Electrophysiol. 2022, 64, 587–595. [Google Scholar] [CrossRef]
  73. Kim, Y.G.; Han, K.-D.; Choi, J.-I.; Choi, Y.Y.; Choi, H.Y.; Boo, K.Y.; Kim, D.Y.; Lee, K.-N.; Shim, J.; Kim, J.-S.; et al. Non-genetic risk factors for atrial fibrillation are equally important in both young and old age: A nationwide population-based study. Eur. J. Prev. Cardiol. 2020, 28, 666–676. [Google Scholar] [CrossRef]
  74. Chew, D.S.; Black-Maier, E.; Loring, Z.; Noseworthy, P.A.; Packer, D.L.; Exner, D.V.; Mark, D.B.; Piccini, J.P. Diagnosis-to-ablation time and recurrence of atrial fibrillation following catheter ablation: A systematic review and meta-analysis of observational studies. Circ. Arrhythmia Electrophysiol. 2020, 13, e008128. [Google Scholar] [CrossRef] [PubMed]
  75. Wu, Z.; Jiang, C.; Li, J.; Du, J.; Bai, Y.; Guo, X.; Wang, W.; Li, S.; Jiang, C.; Liu, N. Effect of family history of atrial fibrillation on recurrence after atrial fibrillation ablation: A report from the Chinese Atrial Fibrillation Registry Study. J. Cardiovasc. Electrophysiol. 2021, 32, 678–685. [Google Scholar] [CrossRef] [PubMed]
  76. McCready, J.W.; Smedley, T.; Lambiase, P.D.; Ahsan, S.Y.; Segal, O.R.; Rowland, E.; Lowe, M.D.; Chow, A.W. Predictors of recurrence following radiofrequency ablation for persistent atrial fibrillation. Europace 2011, 13, 355–361. [Google Scholar] [CrossRef]
  77. Bergau, L.; Sciacca, V.; Nesapiragasan, V.; Rubarth, K.; Konietschke, F.; Fink, T.; El Hamriti, M.; Imnadze, G.; Dagher, L.; Braun, M. A frozen decade: Ten years outcome of atrial fibrillation ablation using a single shot device for pulmonary vein isolation. J. Cardiovasc. Electrophysiol. 2022, 33, 1383–1390. [Google Scholar] [CrossRef] [PubMed]
  78. Platek, A.E.; Szymanska, A.; Kalaszczynska, I.; Szymanski, F.M.; Sierdzinski, J.; Filipiak, K.J. Usefulness of Visfatin as a Predictor of Atrial Fibrillation Recurrence After Ablation Procedure. Am. J. Cardiol. 2020, 125, 415–419. [Google Scholar] [CrossRef]
  79. Yunpeng, S.; Chen, N.; Wang, Q.; Chengui, Z.; Zhao, J.; Ning, L.; Huang, Y. Blood lipid levels and recurrence of atrial fibrillation after radiofrequency catheter ablation: A prospective study. J. Interv. Card. Electrophysiol. 2020, 57, 221–231. [Google Scholar]
  80. Reyat, J.S.; Chua, W.; Cardoso, V.R.; Witten, A.; Kastner, P.M.; Kabir, S.N.; Sinner, M.F.; Wesselink, R.; Holmes, A.P.; Pavlovic, D. Reduced left atrial cardiomyocyte PITX2 and elevated circulating BMP10 predict atrial fibrillation after ablation. JCI Insight 2020, 5, e139179. [Google Scholar] [CrossRef]
  81. Suehiro, H.; Kiuchi, K.; Fukuzawa, K.; Yoshida, N.; Takami, M.; Watanabe, Y.; Izawa, Y.; Akita, T.; Takemoto, M.; Sakai, J. Circulating intermediate monocytes and atrial structural remodeling associated with atrial fibrillation recurrence after catheter ablation. J. Cardiovasc. Electrophysiol. 2021, 32, 1035–1043. [Google Scholar] [CrossRef]
  82. Wang, Q.; Dang, C.; Liu, H.; Hui, J. Plasma carbohydrate antigen-125 for prediction of atrial fibrillation recurrence after radiofrequency catheter ablation. BMC Cardiovasc. Disord. 2021, 21, 400. [Google Scholar] [CrossRef] [PubMed]
  83. Jiang, H.; Lu, Z.; Lei, H.; Zhao, D.; Yang, B.; Huang, C. Predictors of early recurrence and delayed cure after segmental pulmonary vein isolation for paroxysmal atrial fibrillation without structural heart disease. J. Interv. Card. Electrophysiol. 2006, 15, 157–163. [Google Scholar] [CrossRef] [PubMed]
  84. Wu, J.T.; Long, D.Y.; Dong, J.Z.; Wang, S.L.; Fan, X.W.; Yang, H.T.; Duan, H.Y.; Yan, L.J.; Qian, P.; Yang, C.K. Advanced interatrial block predicts clinical recurrence of atrial fibrillation after catheter ablation. J. Cardiol. 2016, 68, 352–356. [Google Scholar] [CrossRef]
  85. Kanzaki, Y.; Inden, Y.; Ando, M.; Kamikubo, Y.; Ito, T.; Mizutani, Y.; Kato, H.; Fujii, A.; Yanagisawa, S.; Hirai, M. An ECG index of P-Wave force predicts the recurrence of atrial fibrillation after pulmonary vein isolation. Pacing Clin. Electrophysiol. 2016, 39, 1191–1197. [Google Scholar] [CrossRef] [PubMed]
  86. Yanagisawa, S.; Inden, Y.; Okamoto, H.; Fujii, A.; Sakamoto, Y.; Mamiya, K.; Tomomatsu, T.; Shibata, R.; Murohara, T. Electrocardiogram characteristics of P wave associated with successful pulmonary vein isolation in patients with paroxysmal atrial fibrillation: Significance of changes in P-wave duration and notched P wave. Ann. Noninvasive Electrocardiol. 2020, 25, e12712. [Google Scholar] [CrossRef]
  87. Auricchio, A.; Özkartal, T.; Salghetti, F.; Neumann, L.; Pezzuto, S.; Gharaviri, A.; Demarchi, A.; Caputo, M.L.; Regoli, F.; De Asmundis, C. Short P-Wave Duration is a Marker of Higher Rate of Atrial Fibrillation Recurrences after Pulmonary Vein Isolation: New Insights into the Pathophysiological Mechanisms Through Computer Simulations. J. Am. Heart Assoc. 2021, 10, e018572. [Google Scholar] [CrossRef]
  88. Supanekar, N.; Gilge, J.L.; Ahmed, A.; Patel, P.J. Post-ablation P wave characteristics correlate with recurrent atrial fibrillation in the ABCD-AF cohort. J. Interv. Card. Electrophysiol. 2022, 64, 437–442. [Google Scholar] [CrossRef]
Jcdd 11 00277 g001
Figure 1. MatLab screenshots demonstrating P wave annotations. PWD: P wave duration; PWV: P wave amplitude; PTFV1: P wave terminal force in V1.
Figure 1. MatLab screenshots demonstrating P wave annotations. PWD: P wave duration; PWV: P wave amplitude; PTFV1: P wave terminal force in V1.
Jcdd 11 00277 g001
Table 1. Comparison of patient characteristics between successful and failed first-time ablation for paroxysmal atrial fibrillation.
Table 1. Comparison of patient characteristics between successful and failed first-time ablation for paroxysmal atrial fibrillation.
Total (n = 211)Success (n = 154)Failure (n = 57)p-Value
Radiofrequency ablation (%)81 (38%)58 (44%)23 (40%)0.2
Cryoballoon ablation (%)130 (62%)96 (62%)34 (60%)0.76
Male (%)161 (76%)119 (77%)42 (74%)0.47
Age (years)61 ±1.361.1 ± 0.961 ± 1.20.89
Diabetes mellitus (%)28 (13%)21 (14%)7 (12%)0.82
Congestive cardiac failure (%)17 (8%)12 (8%)5 (9%)0.83
Ischaemic heart disease (%)18 (9%)13 (8%)5 (9%)0.58
Cerebrovascular event (%)19 (9%)15 (10%)4 (7%)0.42
Hypertension (%)74 (35%)54 (35%)20 (35%)0.67
Left atrial volume indexed (ml/m2)30 ± 0.730 ± 0.430.3 ± 0.80.71
Body mass index (kg/m2)22.2 ± 1.421.8 ± 0.823.1 ± 1.60.38
Flecainide (%)59 (28%)42 (27%)17 (30%)0.41
Sotalol (%)67 (32%)48 (31%)19 (33%)0.5
On flecainide or sotalol long term (%)72 (34%)39 (25%)33 (55%)<0.001
Time flecainide or sotalol stopped (months) after ablation6.3 ± 0.96.3 ± 0.96.2 ± 50.99
Bold indicates statistical significance.
Table 2. Corrected P wave duration (ms) before first-time successful and failed ablation.
Table 2. Corrected P wave duration (ms) before first-time successful and failed ablation.
Success (n = 154)Failure (n = 57)HR for Recurrence (95% CI)p-Value
I132 ± 1.9145.2 ± 7.22.1 (1.3–4.6)0.02
II139.1 ± 4.2149.8 ± 6.31.7 (1.1–3.9)0.03
III131.1 ± 3140.5 ± 4.81.2 (0.8–1.7)0.06
AVR135.5 ± 2.9140.2 ± 5.31.1 (0.7–1.8)0.33
AVL121.3 ± 9.2149.2 ± 8.24.1 (2.1–7.30<0.001
AVF135.3 ± 4.5147.8 ± 5.91.7 (1.2–4.5)0.039
V1135.3 ± 4.7149 ± 7.11.9 (1.3–4.5)0.029
V2124.1 ± 4.6139.5 ± 8.12.5 (1.6–5.3)0.023
V3128.9 ± 9.8139.3 ± 4.51.3 (0.9–4.1)0.1
V4131.3 ± 3.9145.2 ± 6.92.2 (1.4–5.8)0.042
V5130.6 ± 4.5143.4 ± 6.22 (1.3–7.4)0.034
V6132.1 ± 3149.3 ± 4.73.8 (1.9–4.8)<0.001
HR: hazard ratio; CI: confidence interval. Bold indicates statistical significance.
Table 3. P wave voltage (mV) before first-time successful and failed ablation.
Table 3. P wave voltage (mV) before first-time successful and failed ablation.
Success (n = 154)Failure (n = 57)HR for Recurrence (95% CI)p-Value
I0.24 ± 0.020.14 ± 0.020.7 (0.53–0.95)0.03
II0.26 ± 0.020.09 ± 0.030.45 (0.22–0.65)0.009
III0.18 ± 0.030.1 ± 0.010.76 (0.5–1.4)0.32
|AVR|0.19 ± 0.030.16 ± 0.030.96 (0.9–1.1)0.79
AVL0.19 ± 0.040.05 ± 0.020.58 (0.22–0.89)0.002
AVF0.21 ± 0.010.09 ± 0.030.67 (0.45–0.87)0.023
V10.09 ± 0.040.08 ± 0.020.98 (0.9–1)0.87
V20.16 ± 0.020.15 ± 0.021 (0.9–1)0.87
V30.18 ± 0.020.12 ± 0.040.84 (0.5–1.6)0.59
V40.2 ± 0.020.12 ± 0.020.82 (0.5–1.8)0.39
V50.17 ± 0.030.12 ± 0.020.9 (0.6–1.4)0.48
V60.15 ± 0.020.11 ± 0.020.89 (0.7–1.4)0.79
HR: hazard ratio; CI: confidence interval. Bold indicates statistical significance.
Table 4. P wave dispersion (ms) before first-time successful and failed ablation.
Table 4. P wave dispersion (ms) before first-time successful and failed ablation.
Success (n = 154)Failure (n = 57)HR for Recurrence (95% CI)p-Value
I21.2 ± 2.424.2 ± 4.60.91 (0.64–4.7)0.72
II20.3 ± 4.423.2 ± 7.50.89 (0.78–3.8)0.59
III26.4 ± 2.623.3 ± 2.71.1 (0.42–5.2)0.66
AVR22.4 ± 2.725 ± 4.40.93 (0.48–6.3)0.79
AVL42.7 ± 4.244.2 ± 3.20.96 (0.34–6.2)0.91
AVF24.2 ± 4.228.4 ± 4.20.92 (0.67–3.7)0.51
V125.5 ± 3.228.6 ± 3.90.89 (0.48–4.4)0.75
V234.3 ± 4.733.4 ± 4.91 (0.88–1)0.95
V335.2 ± 2.737.2 ± 3.31 (0.78–1.2)0.91
V434.1 ± 4.636.3 ± 4.20.99 (0.84–1.3)0.92
V534.2 ± 2.837.2 ± 3.80.98 (0.81–1.20.94
V629.1 ± 1.334.9 ± 3.20.95 (0.72–2)0.89
HR: hazard ratio; CI: confidence interval. Bold indicates statistical significance.
Table 5. P wave area (ms·mV) before first-time successful and failed ablation.
Table 5. P wave area (ms·mV) before first-time successful and failed ablation.
Success (n = 154)Failure (n = 57)HR for Recurrence (95% CI)p-Value
I15.8 ± 3.210.2 ± 3.30.55 (0.21–0.76)0.021
II18.1 ± 4.46.7 ± 0.80.48 (0.34–0.87)0.002
III11.8 ± 2.17.0 ± 1.30.96 (0.65–2.6)0.89
|AVR|12.9 ± 3.411.2 ± 2.40.99 (0.78–4.2)0.85
AVL11.5 ± 1.93.7 ± 0.70.65 (0.45–0.96)0.04
AVF14.2 ± 2.26.7 ± 0.90.61 (0.32–0.89)0.04
V16.1 ± 0.96.0 ± 1.51 (0.9–1)0.95
V29.9 ± 2.410.5 ± 0.41 (0.9–1)0.97
V311.6 ± 2.18.4 ± 1.60.95 (0.9–1.2)0.72
V413.1 ± 3.48.7 ± 2.70.92 (0.87–1.4)0.69
V511.1 ± 1.48.6 ± 2.40.94 (0.82–1.3)0.78
V69.9 ± 1.18.2 ± 1.90.9 (0.8–1.4)0.92
HR: hazard ratio; CI: confidence interval. Bold indicates statistical significance.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Antoun, I.; Li, X.; Kotb, A.I.; Vali, Z.; Abdelrazik, A.; Koya, A.; Mavilakandy, A.; Koev, I.; Nizam, A.; Eldeeb, H.; et al. The Role of P Wave Parameters in Predicting Pulmonary Vein Isolation Outcomes for Paroxysmal Atrial Fibrillation: An Observational Cohort Study. J. Cardiovasc. Dev. Dis. 2024, 11, 277. https://doi.org/10.3390/jcdd11090277

AMA Style

Antoun I, Li X, Kotb AI, Vali Z, Abdelrazik A, Koya A, Mavilakandy A, Koev I, Nizam A, Eldeeb H, et al. The Role of P Wave Parameters in Predicting Pulmonary Vein Isolation Outcomes for Paroxysmal Atrial Fibrillation: An Observational Cohort Study. Journal of Cardiovascular Development and Disease. 2024; 11(9):277. https://doi.org/10.3390/jcdd11090277

Chicago/Turabian Style

Antoun, Ibrahim, Xin Li, Ahmed I. Kotb, Zakkariya Vali, Ahmed Abdelrazik, Abdulmalik Koya, Akash Mavilakandy, Ivelin Koev, Ali Nizam, Hany Eldeeb, and et al. 2024. "The Role of P Wave Parameters in Predicting Pulmonary Vein Isolation Outcomes for Paroxysmal Atrial Fibrillation: An Observational Cohort Study" Journal of Cardiovascular Development and Disease 11, no. 9: 277. https://doi.org/10.3390/jcdd11090277

APA Style

Antoun, I., Li, X., Kotb, A. I., Vali, Z., Abdelrazik, A., Koya, A., Mavilakandy, A., Koev, I., Nizam, A., Eldeeb, H., Somani, R., & Ng, A. (2024). The Role of P Wave Parameters in Predicting Pulmonary Vein Isolation Outcomes for Paroxysmal Atrial Fibrillation: An Observational Cohort Study. Journal of Cardiovascular Development and Disease, 11(9), 277. https://doi.org/10.3390/jcdd11090277

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop