Novel non-invasive P wave analysis for the prediction of paroxysmal atrial fibrillation recurrences in patients without structural heart disease

Abstract Background Advanced interatrial block (IAB), prolonged and bimodal P waves in surface ECG inferior leads, is an unrecognized surrogate of atrial dysfunction and a trigger of atrial dysrhythmias, mainly atrial fibrillation (AF). Our aim was to prospectively assess whether advanced IAB in sinus rhythm precedes AF and stroke in elderly outpatients with structural heart disease, a group not previously studied. Methods Prospective observational registry that included outpatients aged ≥70 years with structural heart disease and no previous diagnosis of AF. Patients were divided into three groups according to P-wave characteristics. Results Among 556 individuals, 223 had normal P-wave (40.1%), 196 partial IAB (35.3%), and 137 advanced IAB (24.6%). After a median follow-up of 694 days; 93 patients (16.7%) developed AF, 30 stroke (5.4%), and 34 died (6.1%). Advanced IAB was independently associated with AF (hazard ratio [HR] 2.9, 95% confidence interval [CI] 1.7–5.1, p<0.001), stroke (HR 3.8, 95% CI 1.4–10.7, p=0.010), and AF/stroke (HR 2.6, 95% CI 1.5–4.4, p=0.001). P-wave duration (ms) was independently associated with AF (HR 1.05, 95% CI 1.03–1.07, p<0.001), AF/stroke (HR 1.04, 95% CI 1.02–1.06, p<0.001), and mortality (HR 1.04, 95% CI 1.00–1.08, p=0.021). Conclusions The presence of advanced IAB in sinus rhythm is a risk factor for AF and stroke in an elderly population with structural heart disease and no previous diagnosis of AF. P-wave duration was also associated with all-cause mortality. Figure. Age- and sex-adjusted linear and non-linear association between P-wave duration (msec) and atrial fibrillation (A), stroke (B), and atrial fibrillation or stroke (C) risk. Results of a generalized additive model with spline smoothing functions and 4 degrees of freedom. Figure 1. Kaplan-Meyer curves of survival free of atrial fibrillation (A), stroke (B) and atrial fibrillation or stroke (C) in patients with normal P-wave, partial interatrial block (IAB) and advanced IAB. Funding Acknowledgement Type of funding source: None

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Higher FT4 level within the normal range predicts the outcome of cryoballoon ablation in paroxysmal atrial fibrillation patients without structural heart disease

Annals of Noninvasive Electrocardiology ◽

10.1111/anec.12874 ◽

2021 ◽

Author(s):

Yan Pei ◽

Shaojie Xu ◽

Haotian Yang ◽

Zhongyuan Ren ◽

Weilun Meng ◽

...

Keyword(s):

Atrial Fibrillation ◽

Heart Disease ◽

Paroxysmal Atrial Fibrillation ◽

Structural Heart Disease ◽

Cryoballoon Ablation ◽

Normal Range

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Beat-to-Beat P-Wave Analysis Outperforms Conventional P-Wave Indices in Identifying Patients with a History of Paroxysmal Atrial Fibrillation during Sinus Rhythm

Diagnostics ◽

10.3390/diagnostics11091694 ◽

2021 ◽

Vol 11 (9) ◽

pp. 1694

Author(s):

Dimitrios Tachmatzidis ◽

Dimitrios Filos ◽

Ioanna Chouvarda ◽

Anastasios Tsarouchas ◽

Dimitrios Mouselimis ◽

...

Keyword(s):

Atrial Fibrillation ◽

Sinus Rhythm ◽

Paroxysmal Atrial Fibrillation ◽

Univariate Analysis ◽

Multivariate Logistic Regression Analysis ◽

P Wave ◽

P Value ◽

Wave Analysis ◽

P Waves ◽

History Of

Early identification of patients at risk for paroxysmal atrial fibrillation (PAF) is essential to attain optimal treatment and a favorable prognosis. We compared the performance of a beat-to-beat (B2B) P-wave analysis with that of standard P-wave indices (SPWIs) in identifying patients prone to PAF. To this end, 12-lead ECG and 10 min vectorcardiogram (VCG) recordings were obtained from 33 consecutive, antiarrhythmic therapy naïve patients, with a short history of low burden PAF, and from 56 age- and sex-matched individuals with no AF history. For both groups, SPWIs were calculated, while the VCG recordings were analyzed on a B2B basis, and the P-waves were classified to a primary or secondary morphology. Wavelet transform was used to further analyze P-wave signals of main morphology. Univariate analysis revealed that none of the SPWIs performed acceptably in PAF detection, while five B2B features reached an AUC above 0.7. Moreover, multivariate logistic regression analysis was used to develop two classifiers—one based on B2B analysis derived features and one using only SPWIs. The B2B classifier was found to be superior to SPWIs classifier; B2B AUC: 0.849 (0.754–0.917) vs. SPWIs AUC: 0.721 (0.613–0.813), p value: 0.041. Therefore, in the studied population, the proposed B2B P-wave analysis outperforms SPWIs in detecting patients with PAF while in sinus rhythm. This can be used in further clinical trials regarding the prognosis of such patients.

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