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Europace Advance Access originally published online on May 15, 2007
Europace 2007 9(8):601-607; doi:10.1093/europace/eum054
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© The European Society of Cardiology 2007. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

ATRIAL FIBRILLATION

Prediction of atrial fibrillation in patients with cardiac dysfunctions{dagger}

P wave signal-averaged ECG and chemoreflexsensitivity in atrial fibrillation

Marco Budeus1,*, Marcus Hennersdorf2, Oliver Felix2, Klaus Reimert2, Christian Perings3, Heinrich Wieneke1, Raimund Erbel1 and Stefan Sack1

1 Department of Cardiology, West-German Heart Centre, University of Duisburg-Essen, Hufeland Street 55, Essen 45122, Germany; 2 Department of Cardiology, Pneumology, and Angiology, Medical Clinic and Policlinic B Heinrich-Heine-University, Duesseldorf, Germany; 3 Department of Cardiology and Angiology, University Hospital Herne, Ruhr-University Bochum, Herne, Germany

Manuscript submitted 7 November 2006. Accepted after revision 5 March 2007.

* Corresponding author. Tel: +49 02017234801. E-mail address: marco.budeus{at}uk-essen.de


   Abstract
Top
 Abstract
Introduction
 Methods
 Echocardiography
 Results
 Discussion
 Chemoreflexsensitivity
 Limitations
 Conclusions
 References
 
Aims Atrial fibrillation (AF) is a common arrhythmia in advanced heart failure. The occurrence of AF increases the risk of death and hospitalization for patients with heart failure. The results of different studies indicated that patients with paroxysmal AF have a longer filtered P wave duration (FPD), a lower root mean square voltage of the last 20 ms of the P wave (RMS 20), and a lower chemoreflexsensitivity (CHRS). Our study bases on these observations in order to examine the methods for predicting AF in patients with a left ventricular ejection fraction below 40% without a prior documentation of AF.

Methods and results The ratio between the difference of RR intervals in ECG and venous pO2 before and after 5-min oxygen inhalation was measured (ms/mmHg) in order to determine the CHRS. A P wave signal-averaged ECG was performed for the measurement of FPD and RMS 20. The measurements were only performed in 94 patients with sinus rhythm. AF occurred during the mean follow-up of 39.9 months in 24 patients (26%). There were no significant differences concerning age, heart diseases, sex, ejection fraction, heart rate, or the use of drugs. The FPD (130.3 ± 4.2 vs. 118.9 ± 12.4 ms, P < 0.0001) was significantly longer and the RMS 20 (3.03 ± 0.95 vs. 3.83 ± 1.58 µV, P = 0.02) was significantly lower in patients with AF than in sinus rhythm. The CHRS did not differ significantly between both groups (3.57 ± 1.49 vs. 3.48 ± 1.62 ms/mmHg, P = 0.81). The {chi}2 test showed that the threshold of FPD≥125 ms and RMS 20 ≤3.3 µV revealed the best predictive value for AF. A stepwise logistic regression analysis of all variables identified the threshold of FPD≥125 ms and RMS 20 ≤3.3 µV (OR 18.71; 95% CI, 4.85–72.16, P < 0.0001) as independent predictors for AF.

Conclusions In summary, our data show that the results of a P wave signal-averaged ECG can predict the risk for new onset of AF in patients with heart failure. The value of signal-averaged FPD is probably the result of reflecting the intra-atrial conduction delay, which is a pathophysiological condition for AF. The CHRS is not a suitable method for predicting AF.

Key Words: Atrial fibrillation, Neurovegetative imbalance, P wave signal-averaged ECG, Chemoreflexsensitivity, Heart failure


   Introduction
Top
 Abstract
 Introduction
Methods
 Echocardiography
 Results
 Discussion
 Chemoreflexsensitivity
 Limitations
 Conclusions
 References
 
Heart failure is an important risk factor for atrial fibrillation (AF) and predisposes for thrombembolism.1Go–3Go The onset of AF in patients with heart failure is associated with a poorer clinical and haemodynamic outcome.2Go–5Go Patients with heart failure and AF have a higher morbidity and mortality than patients with sinus rhythm.2Go–5Go The restoration of sinus rhythm in patients with heart failure shows a beneficial effect on mortality in comparison with the rate control of AF.5Go Therefore, the identification of patients with heart failure at risk for AF is of clinical relevance.

The atrial electrophysiology in patients with heart failure is modulated by the autonomic function and an atrial dilatation.6Go–8Go The autonomic nervous system is an important factor in the initiation of atrial arrhythmias and can have influenced the atrial refractory period9Go and was characterized by the chemoreflexsensitivity (CHRS).10Go Recently, other investigators11Go–14Go and we10Go,15Go,16Go used a P wave signal-averaged ECG (P-SAECG) or CHRS to assess the risk of AF in different clinical situations. The consensus of these studies are a longer filtered P wave duration (FPD), a lower root mean square voltage of the last 20 ms of the P wave (RMS 20), and a lower CHRS in patients with paroxysmal AF, a recurrence of AF after electrical cardioversion, or a new onset of AF after coronary bypass grafting than in patients with sinus rhythm. But all these studies include fewer patients with a cardiac dysfunction. It is unclear whether the values of P-SAECG and CHRS can predict the new onset of AF in patients with heart failure.

The aim of the investigation was the comparison of the predictive value of clinical and study variables for a new onset of AF in patients with heart failure. These variables include P-SAECG, CHRS, demographic data, NYHA classification, and echocardiographic measurements.


   Methods
Top
 Abstract
 Introduction
 Methods
Echocardiography
 Results
 Discussion
 Chemoreflexsensitivity
 Limitations
 Conclusions
 References
 
Between March 2000 and March 2001, 101 patients with heart failure at least NYHA II and an ejection fraction (EF) ≤40% without previous symptoms of AF like tachycardia, bradycardia, palpitations or dizziness, or complications of AF like stroke or transitory ischaemic attack were enrolled and followed until August 2003. The EF was measured by echocardiography. There had to be a continuous sinus rhythm without a documentation of AF at least in four 24 h-Holter ECGs before inclusion into our study. We excluded patients receiving amiodarone or class I antiarrhythmic therapy because of possible interactions with P-SAECG.17Go–19Go In addition, patients with a history of ventricular arrhythmias were also excluded because of a lower CHRS.20Go Furthermore, we excluded patients with chronic pulmonary diseases, sleep apnoea syndrome, permanent, or paroxysmal atrial fibrillation. All patients have had antiarrhythmic drugs withdrawn at least five half-lives before the measurements.

The primary physicians, who took care of the patients, were blinded to the results of the P-SAECG and CHRS, which did not influence therapeutic decisions. The use of drugs after including in the study was left to the discretion of the primary physicians. Patients were evaluated every month by ECG and 24 h-Holter ECG (Marquette Holter recorder 8500 with five leads, Marquette Electronic Inc., Milwaukee, WI, USA) or were evaluated in case of signs of AF by an ECG and 24 h-Holter ECG during the follow-up period. Demographic data, medications, and past medical history were gathered by patient interview and review of their medical record. The institutional review board approved the study and patients gave written, informed consent of the study.

Study endpoints
The primary endpoint of our study was the onset of AF. The occurrence of AF had to be documented by an ECG or a 24 h-Holter ECG and AF was defined as an electrocardiographically confirmed episode of AF for more than 10 min.10Go The secondary endpoints were death or hospitalization due to any reason.

Acquisition and analysis of the P wave signal-averaged ECG
We measured the P wave triggered P-SAECG recording from an X, Y, and Z lead system (Predictor, Kaiser Medizintechnik, Germany) using the time-domain analysis10Go,15Go,16Go at the study entry of all patients. The P wave was retained as a trigger of the averaging process and the signals were digitized at a frequency of 1000 samples/s with 16-bit accuracy. After eliminating all supraventricular and ventricular extrasystoles signals from each lead, the signals were amplified and filtered between 40 and 250 Hz using a bidirectional filter. P waves were recorded until a noise endpoint of 0.5 µV was achieved in the PQ interval. For every measurement at least 450 beats were used to complete the signal averaging with a mean average of 506.4 ± 17.7 beats. The P wave complexes of filtered X, Y, and Z leads were combined to a vector magnitude of {surd}(X2+Y2+Z2). The onset and the offset of the P wave vector magnitude were manually defined. The FPD of the vector magnitude was defined as the interval between the onset and the offset of selected points and the RMS 20 was measured in the vector magnitude. We retrospectively defined the threshold as a combination of FPD and RMS 20 similar to our former studies.10Go,15Go,16Go

Analysis of CHRS
The analysis of CHRS is described in detail in the former publications.10Go,15Go,16Go Patients were placed in a supine position in a quiet room to reach a haemodynamic homeostasis and a cannula was positioned into a cubital vein for later blood sampling. We analysed the venous partial pressure of oxygen (pO2) and the mean of 10 consecutive RR intervals of a surface ECG before and after the inhalation of 5 L O2/min through a nose mask for a period of 5 min. The CHRS was calculated by the difference in RR intervals and pO2 before and after O2 inhalation. A pathological CHRS was predefined as a CHRS ≤3.0 ms/mmHg.10Go,15Go,16Go


   Echocardiography
Top
 Abstract
 Introduction
 Methods
 Echocardiography
Results
 Discussion
 Chemoreflexsensitivity
 Limitations
 Conclusions
 References
 
A M-mode and a two-dimensional echocardiography (Model SSH-160 A, Toshiba Corp., Japan) was performed on all patients in the left lateral supine position in order to determine the left atrial size, the left ventricular diameter, and the EF. The left atrial size was measured as the distance from the leading edge of the posterior aortic wall to the leading edge of the posterior left atrial wall at the end systole. Biplane LVEF was measured in apical views by tracing the endocardial borders at the end-diastole and the end-systole for a minimum of five cardiac cycles.21Go The digital workstation calculated the LVEF.

Statistics
We performed a full data set analysis for all outcomes without imputation of missing values. All data are presented as mean ± SD for continuous variables and as percentages for categorical variables. Discrepancies in proportions were evaluated for statistical significance using the {chi}2 or Fisher's exact test. Student's t-test was used comparing continuous variables. The Mann–Whitney U test was used for variables with non-normal distribution. All statistical tests were two-tailed. The diagnostic cut-off value for continuous parameters was calculated by means of receiver-operating characteristic (ROC) curves. The {chi}2 test was used for the evaluation of cut-off values. A multivariate Cox regression analysis was performed on variables regarded as significant predictors (P < 0.1) with a univariate analysis. For all variables with at least a moderate level of association we estimated the individual ORs with CIs. The Kaplan–Meier analysis with a log-rank test was used to compare the onset of AF with CHRS and P-SAECG. A P-value < 0.05 was considered as significant. The statistical package that we used was SPSS 12.0 for Windows.


   Results
Top
 Abstract
 Introduction
 Methods
 Echocardiography
 Results
Discussion
 Chemoreflexsensitivity
 Limitations
 Conclusions
 References
 
Seven patients had to be excluded because of missing evaluation. During a follow-up of 39.9 ± 8.2 months, AF was documented in 24 patients (26%). The patients were divided into two groups according to the onset of AF during the follow-up. Group I consisted of 24 patients with AF and group II included 70 patients with sinus rhythm. The clinical characteristics were similar between patients with AF and sinus rhythm with exception of a larger left atrial size (43.2 ± 3.5 vs. 41.1 ± 3.7 mm, P = 0.018) and a trend to a reduced LVEF (26.6 ± 8.2 vs. 29.7 ± 7.7%, P = 0.091) in patients with AF than in sinus rhythm (Table 1). AF increased NYHA classification (2.0 ± 0.5 vs. 2.3 ± 0.6, P = 0.02) and was associated with a hospitalization in nine patients. AF was observed in four patients after the notation of palpitations, in two patients after the notation of dizziness and in nine patients by pure chance in the ECG.


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  		Table 1 Clinical details of patients

 
Follow-up
During the mean follow-up of 39.9 months, 10 patients died due to worsening heart failure in our hospital (Figure 1). Five patients of each group died but this did not achieve statistical significance (P = 0.07). Hospitalization of any reason (Figure 2) was significantly different (P = 0.04) between patients [14 (58%) patients] with AF and patients [24 (34%) patients] with sinus rhythm.


Figure 1
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  		Figure 1 Kaplan–Meier analysis for event-free survival curves for the endpoint of death due to progressive heart failure (P = 0.07). Filled square represents patients with sinus rhythm and filled triangle represents patients with atrial fibrillation.

 


Figure 2
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  		Figure 2 Kaplan–Meier analysis for event-free survival curves for the endpoint of hospitalization of any reason (P = 0.04). Filled square represents patients with sinus rhythm and filled triangle represents patients with atrial fibrillation.

 
AF was electrical cardioverted in nine patients because of a deterioration of heart failure at the first onset of AF and because of atrial tachyarrhythmias in four patients. Sinus rhythm was restored spontaneously of the remaining 11 patients.

A stroke occurred in three patients (13%) with AF and in two patients with sinus rhythm (3%) (P = 0.08).

P wave signal-averaged ECG
The FPD was significantly longer (130.3 ± 4.2 vs. 118.9 ± 12.4 ms, P < 0.0001) and the RMS 20 (3.03 ± 0.95 vs. 3.83 ± 1.58 µV, P = 0.02) was significantly lower in patients with new documented AF than in patients with sinus rhythm. The ROC curve showed in combination with {chi}2 test that an FPD ≥125 ms and RMS 20 ≤3.3 µV revealed the best predictive value for AF (Table 2). These parameters in combination were defined as the threshold of P-SAECG measurement. Figure 3 shows two original tracings of the P-SAECG of representative patients with and without AF. The incidence of this threshold was significantly higher in patients with a new documented AF than in patients with sinus rhythm [19/24 (79%) vs. 16/68 (23%) patients, P < 0.0001].


Figure 3
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  		Figure 3 Original tracings of a patient with atrial fibrillation (A) and sinus rhythm (B).

 


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  		Table 2 Predictive values of the measurements of P-SAECG and echocardiography

 
Chemoreflexsensitivity
The RR intervals (870.9 ± 115.6 vs. 903.0 ± 118.4, P < 0.0001) and the venous pO2 (35.9 ± 11.9 vs. 51.7 ± 20.4 mmHg, P < 0.0001) of all patients significantly increased after a 5-min inhalation of oxygen. The baseline values were not significantly different between both groups (Table 3). The CHRS was similar between patients with and without AF (3.57 ± 1.49 vs. 3.48 ± 1.62 ms/mmHg). A pathological CHRS did also not show a statistical significance between patients with (13 patients) and without (29 patients) the onset of AF (Table 3). In addition, the ROC curve did not reveal a significant threshold for the prediction of AF.


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  		Table 3 Values of CHRS.

 
Prediction of atrial fibrillation
ROC curve analysis showed that a threshold of the left atrial size was ≥44 mm (P = 0.067) and that a threshold of the EF was ≤20% (P = 0.008) for the prediction of AF. The multivariate stepwise regression analysis found that FPD ≥125 ms combined with RMS 20 ≤3.3 µV and EF ≤20% were independent variables for the onset of AF (Table 4). Figure 4 shows the event-free rate curves depending on FPD ≥125 ms and RMS 20 ≤3.3 µV.


Figure 4
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  		Figure 4 Kaplan–Meier analysis for event-free curves for the endpoint of the occurrence of atrial fibrillation (P < 0.0001). Filled square represents patients with FPD ≥125 ms and RMS 20 ≤3.3 µV and filled triangle represents patients without FPD ≥125 ms and RMS 20 ≤3.3 µV.

 


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  		Table 4 Univariate and multivariate predictors of atrial fibrillation

 

   Discussion
Top
 Abstract
 Introduction
 Methods
 Echocardiography
 Results
 Discussion
Chemoreflexsensitivity
 Limitations
 Conclusions
 References
 
In the present study 26% of patients with heart failure showed a new onset of AF during a mean follow-up of 39.9 months. The occurrence of AF was associated with a significant deterioration of heart failure. The hospitalization was significantly higher in patients with AF when compared with patients with sinus rhythm. In our study, the threshold of FPD ≥125 ms and RMS 20 ≤3.3 µV as well as a LVEF ≤20% has been determined as predictors for the onset of AF.

P wave signal-averaged ECG
The values of P wave signal-averaged ECG were able to predict the onset of AF in different clinical settings like recurrence of AF after electrical cardioversion or a new onset of AF after coronary bypass grafting.10Go–16Go In the recent study the threshold was FPD ≥125 ms and RMS 20 ≤3.3 µV, which was a powerful predictor for AF. Yamada et al.22Go also found in a former study a longer FPD (147 ± 8 vs. 137 ± 11 ms, P < 0.005) and a lower RMS 20 (1.9 ± 0.2 vs. 2.8 ± 1.3 µV) in 10 (13%) patients with AF and 65 (87%) patients with sinus rhythm.22Go The mean follow-up (21 months) was shorter in the study of Yamada et al. in comparison with our study with a follow-up of 39.9 months. This time, difference might explain the higher incidence of patients of AF in our study. In addition, our patients had a lower LVEF in comparison with the patients in the study of Yamada et al. with a LVEF of 30% in patients with and without AF.22Go In their study the threshold was defined as an FPD ≥132 ms and RMS 20 ≤2.3 µV and achieved a specificity of 69%, a sensitivity of 90%, a positive predictive value of 31%, a negative predictive value of 98%, and an accuracy of 72%.22Go Their threshold was predefined as a result of the 90th percentile of measurements of 132 healthy persons without heart failure22Go in contrast to our threshold, which was calculated retrospectively.

The consensus of the study of Yamada et al. and our study however, has a longer FPD and a lower RMS 20 among patients with a new onset of AF and the predictive value of AF with P-SAECG in patients with heart failure. The FPD reflected an intra-atrial conduction delay, which was observed in former studies and which was an important risk factor for the onset of AF.9Go,23Go,24Go Thus, risk stratification could be performed with P-SAECG in patients with heart failure for an aggressive approach for maintenance of sinus rhythm.

Atrial fibrillation in patients with heart failure
AF is an important factor of morbidity and mortality in patients with heart failure.2Go–5Go We observed a higher rate of hospitalization in patients with AF than with sinus rhythm. This poorer prognosis was also observed in other studies.1Go,2Go,22Go The combination of AF and heart failure caused a vicious circle with a worsening of heart failure and easier initiation of AF.2Go,22Go Therefore, patients with heart failure at risk of AF should be monitored more frequently and should possibly have a more aggressive approach to the treatment of heart failure in order to break through the vicious circle.

Patients with heart failure showed an intra-atrial conduction delay,6Go which was an important risk factor for induction of AF.25Go,26Go The predictive value of signal-averaged FPD of patients with AF is probably the result of reflecting the intra-atrial conduction delay by a longer FPD.11Go,16Go,23Go Therefore, the P-SAECG could be used for risk stratification in patients with heart failure to identify high-risk patients for the onset of AF.

The maintenance of sinus rhythm caused a reduction of mortality in patients with heart failure when compared with the rate control of AF.5Go The Framingham study reported that heart failure was the most powerful independent precursor of AF with an approximately six-fold risk.1Go In addition, heart failure increased the risk of recurrence of AF after cardioversion.27Go The association between AF and heart failure was well documented with a consensus of a poorer prognosis of patients with heart failure and AF.


   Chemoreflexsensitivity
Top
 Abstract
 Introduction
 Methods
 Echocardiography
 Results
 Discussion
 Chemoreflexsensitivity
Limitations
 Conclusions
 References
 
The results of CHRS were surprisingly similar between patients with AF and sinus rhythm. In the former studies a significantly lower CHRS was observed in patients with paroxysmal AF, a recurrence after cardioversion, or a new onset of AF after coronary bypass grafting.10Go,15Go,16Go Due to the fact that the LVEF was similar in both groups might explain the unavailable prediction of AF with CHRS in patients with heart failure because of the correlation between CRHS and LVEF.20Go


   Limitations
Top
 Abstract
 Introduction
 Methods
 Echocardiography
 Results
 Discussion
 Chemoreflexsensitivity
 Limitations
Conclusions
 References
 
A difficulty was the documentation of AF because of a high number of asymptomatic episodes of AF.28Go Therefore, our patients could have had asymptomatic non-detected episodes of AF, which might have influenced our results. In this study, we evaluated stable outpatients at enrolment. The results of our study should not be generalized to inpatients with severe heart failure. The positive predictive value of our threshold (55%) was still low in our study. A further prospective study with a larger patient population is needed to verify the threshold of FPD ≥125 ms and RMS 20 ≤3.3 µV as predictors of AF.


   Conclusions
Top
 Abstract
 Introduction
 Methods
 Echocardiography
 Results
 Discussion
 Chemoreflexsensitivity
 Limitations
 Conclusions
References
 
The results of our study show that the occurrence of AF in patients with heart failure can be predicted by P-SAECG and a LVEF ≤20%. The CHRS is not a suitable method for predicting AF. In addition, the value of signal-averaged FPD is probably the result of reflecting the intra-atrial conduction delay, which is a pathophysiological condition for the onset of AF.


   Footnotes
 
{dagger} This study was presented in part as a poster at Heart Rhythm, 26th Annual Scientific Sessions, May 4–7, 2005, New Orleans, LA, USA. Back


   References
Top
 Abstract
 Introduction
 Methods
 Echocardiography
 Results
 Discussion
 Chemoreflexsensitivity
 Limitations
 Conclusions
 References
 
[1] Benjamin EJ, Levy D, Vaziri SM, DAgostino RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study. JAMA (1994) 271:840–4.[Abstract/Free Full Text]

[2] Middlekauff HR, Stevenson WG, Stvenson LW. Prognostic significance of atrial fibrillation in advanced heart failure: a study of 390 patients. Circulation (1991) 84:40–8.[Abstract/Free Full Text]

[3] Pozzoli M, Cioffi G, Traversi E. Predictors of primary atrial fibrillation and concomitant and hemodynamic changes in patients with chronic heart failure: a prospective study in 344 patients with baseline sinus rhythm. J Am Coll Cardiol (1998) 32:197–204.[Abstract/Free Full Text]

[4] Naccarelli GV, Hynes BJ, Wolbrette DL, Bhatta L, Khan M, Samii S, Luck JC. Atrial fibrillation in heart failure: prognostic significance and management. J Cardiovasc Electrophysiol (2003) 14(suppl.):281–6.[CrossRef][Web of Science][Medline]

[5] Ökcun B, Yigor Z, Arat A, Kücükoglu MS. Comparison of rate and rhythm control in patients with atrial fibrillation and nonischemic heart failure. Jpn Heart J (2004) 45:591–601.[CrossRef][Medline]

[6] Sanders P, Morton SB, Davidson NC, Spence SJ, Vohra JK, Sparks PB, Kalman JM. Electrical remodeling of the atria in congestive heart failure. Circulation (2003) 108:1461–18.[Abstract/Free Full Text]

[7] Klein LS, Miles WM, Zipes DP. Effect of atrioventricular interval during pacing or reciprocating tachycardia on atrial size, pressure and refractory period: contraction–excitation feedback in the human atrium. Circulation (1990) 82:60–8.[Abstract/Free Full Text]

[8] Pinto YM, Buikema JH, van Gilst WH. Hypertensive tissue renin–angiotensin system in cardiovascular dysfunction: experimental evidence and clinical hypotheses. Clin Exp Hypertens (1995) 14:441–68.

[9] Zipes DP, Mihliek MJ, Robbins GT. Effects of selective vagal or stellate ganglion on atrial refractoriness. Cardiovasc Res (1974) 8:647–55.[Web of Science][Medline]

[10] Budeus M, Gramsch-Zabel H, Hennersdorf M, Röhlen S, Schnitzler S, Felix O, Reimer K, Feindt P, Gams E, Perings C. Predicting of atrial fibrillation after coronary bypass grafting: the role of chemoreflexsensitivity and P wave signal averaged ECG. Int J Cardiol (2005) 10:317–24.

[11] Fukunami M, Yamada T, Ohmori M, Kumagai K, Umemoto K, Sakei A, Kondoh N, Minamino T, Hoki N. Detection of patients at risk for paroxysmal atrial fibrillation during sinus rhythm by P wave triggered signal averaged electrocardiogram. Circulation (1991) 83:162–9.[Abstract/Free Full Text]

[12] Zaman AG, Archbold RA, Helft G, Paul EA, Curzen NP, Mills PG. Atrial fibrillation after coronary artery bypass surgery. A model of preoperative risk stratification. Circulation (2000) 101:1403–8.[Abstract/Free Full Text]

[13] Abe Y, Fukunami M, Yamada T, Ohmori M, Shimonagata T, Kumagai K, Kim J, Sanada S, Hori M, Hoki N. Prediction of transition to chronic atrial fibrillation in patients with paroxysmal atrial fibrillation by signal averaged electrocardiography. A prospective study. Circulation (1997) 96:2612–16.[Abstract/Free Full Text]

[14] Aytemir K, Aksoyek S, Yildirir A, Ozer N, Oto A. Prediction of atrial fibrillation recurrence after cardioversion by P wave signal averaged electrocardiogram. Int J Cardiol (1999) 70:15–21.[CrossRef][Web of Science][Medline]

[15] Budeus M, Wieneke H, Erbel R, Sack S, Perings C. Long-term outcome after cardioversion of atrial fibrillation: prediction of recurrence with P wave signal averaged ECG and chemoreflexsensitivity. Int J Cardiol (2006) 112:308–15.[CrossRef][Web of Science][Medline]

[16] Budeus M, Hennersdorf M, Wieneke H, Sack S, Erbel R, Perings C. P wave signal averaged ECG and chemoreflexsensitivity in paroxysmal atrial fibrillation. Int J Cardiol (2005) 100:317–24.[CrossRef][Web of Science][Medline]

[17] Aspromonte N, Auruti A, Ceci V. Efficacy of class Ic antiarrhythmic drugs predicted by P wave signal averaged ECG in patients with paroxysmal atrial fibrillation. J Amb Monit (1994) 7:115–9.

[18] Banasiak W, Telichowski A, Anker S, Fuglewicz A, Kalka D, Molenda W, Reczuch K, Adamus J, Coats AJS, Ponikowski P. Effects of amiodarone on the P-wave triggered signal-averaged electrocardiogram in patients with paroxysmal atrial fibrillation and coronary artery disease. Am J Cardiol (1999) 83:112–4.[Web of Science][Medline]

[19] Budeus M, Hennersdorf M, Perings Ch. The effect of antiarrhythmic medication on the variables of P wave signal averaged ECG among paroxysmal atrial fibrillation. Z Kardiol (2003) 92(suppl.):8.

[20] Hennersdorf MG, Perings Ch, Niebch V, Hillebrandt S Vester EG, Strauer BE. Chemoreflexsensitivity in patients with survived sudden cardiac arrest and prior myocardial infarction. PACE (2000) 23:457–62.[Medline]

[21] St John Sutton M, Otterstat JE, Plappert T, Parker A, Sekarski D, Keane MG, Poole-Wilson P, Lubsen K. Quantitation of left ventricular volumes and ejection fraction in post-infarction patients from biplane and single plane two-dimensional echocardiograms. Eur Heart J (1998) 19:808–16.[Abstract/Free Full Text]

[22] Yamada T, Fukunami M, Shimonagata T, Kumagai K, Ogiat H, Asano Y, Hirata A, Hori M, Hoki N. Prediction of paroxysmal atrial fibrillation in patients with congestive heart failure: a prospective study. J Am Coll Cardiol (2000) 35:405–13.[Abstract/Free Full Text]

[23] Raitt MH, Kusumoto W, Giraud GD, McAnulty JH. Electrophysiologic predictors of the recurrence of persistent atrial fibrillation within 30 days of cardioversion. Am J Cardiol (2004) 93:107–10.[CrossRef][Web of Science][Medline]

[24] Soylu M, Demir AD, Özedmir Ö, Soylu Ö, Topaloglu S, Kunt A, Sasmaz A, Korkmaz S, Tasdemir O. Increased dispersion of refractoriness in patients with atrial fibrillation in the early postoperative period after coronary artery bypass grafting. J Cardiovasc Electrophysiol (2003) 14:28–31.[CrossRef][Web of Science][Medline]

[25] Moe GK. On the multiple wavelet hypotheses of atrial fibrillation. Arch Int Pharmacodyn (1962) 140:183–8.

[26] Cosio FG, Palacios J, Vidal JM, Cocina EG, Gomez-Sanchez MA, Tamargo L. Electrophysiological studies in atrial fibrillation. Slow conduction of premature impulses: a possible manifestation of the background for reentry. Am J Cardiol (1983) 51:122–30.[CrossRef][Web of Science][Medline]

[27] Van Gelder IC, Crijns HJ, Van Gilst WH, Verwer R, Lie KI. Prediction of uneventful cardioversion and maintenance of sinus rhythm from direct-current electrical cardioversion of chronic atrial fibrillation and flutter. Am J Cardiol (1991) 68:41–6.[Web of Science][Medline]

[28] Israel CW, Grönefeld G, Ehrlich JR, Li YG, Hohnloser SH. Long-term risk of recurrent atrial fibrillation as documented by implantable monitoring device. J Am Coll Cardiol (2004) 43:47–52.[Abstract/Free Full Text]


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