Predictors Of Paroxysmal Atrial Fibrillation: From Electrophysiology, Echocardiography To Biomarkers

 

Chun-Song Hu¹, Chang-Sheng Ma² and Da-Yi Hu³ …

 

1. Department of Cardiology, Medical College of Nanchang University, Nanchang 330006, China;

2. Department of Cardiology, Capital Medical University, Beijing 100000, China;

3. Department of Cardiology, People’s Hospital of Peking University, Beijing 100044, China. heart@gw-icc.org

 

Summary

 

Paroxysmal atrial fibrillation(PAF) is a common problem in clinical and a

high risk factor to our cardiovascular and cerebrovascular system. Therefore, its prediction is more important than ever due to the high morbidity of hypertension and coronary heart disease. In this article, authors summarized predictors of PAF with an object table which from electrophysiology such as signal-averaged ECG - P ware duration (SAECG-PWD or PWD-PII) and P-ware dispersion (Pd), echocardiography such as left atrial diameter (LAD) and left ventricular ejection fraction (LVEF), to biomarkers “ABC”, which are Albumin or atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP) and C-reactive protein (CRP) or carbohydrate antigen 125 (CA 125, pending). Definitely, these predictors are helpful to clinical staffs to predict PAF in their practical work. However, ideal predictors should meet not only such “golden criteria”: objective, reliable, noninvasive, simple and easy to measure, available and cheap, but also seek their diversity. Therefore, to develop a new method which combined ECG or ECHO with biomarkers “ABC”such as BNP will help us to predict PAF more accurately. Of course, it’s scientific value needs to confirm by more patients’ data in our future work.

 

Keywords: Paroxysmal atrial fibrillation, predictors, electrophysiology, echocardiography, biomarkers

 

 

As we all known, paroxysmal atrial fibrillation(PAF) is a common problem in clinical and a high risk factor to our cardiovascular and cerebrovascular system. Therefore, it’s very important for clinical staffs to predict PAF. The aims of prediction of PAF are to decrease cardiovascular and cerebrovascular events such as vascular embolisms, acute myocardial infarction(AMI) or acute coronary syndrome(ACS), heart failure, and stroke, so as to decrease related mortality and morbidity. Ideal predictors should meet not only such “golden criteria”: objective, reliable, noninvasive, simple and easy to measure, available and cheap, but also should seek their diversity which makes different professional technicians such as doctors, nurses and experimental technicians can predict PAF, especially in patients with hypertension because there are about 1 billion cases in the world. Thus, we need different tools and indexes as predictors of PAF to meet different medical conditions.

 

At current stage, people already knew that prevention is the best therapy, especially to cardiovascular and cerebrovascular diseases. PAF’s prevention is more important than ever for the reason of avoiding of its complications. Recent a decade, the prediction of PAF developed rapidly from several fields with the development of modern diagnostic techniques. Current literatures showed that predictors of PAF includes not only parameters of electrocardiography (ECG) and echocardiography, but also biomarkers as well as patients’ information such as gender, age and AF history(see PAF.Table 1), which showed different levels or degrees from lower to moderate or higher sensitivity and specificity. Of course, each of these tools and indexes has its advantages and disadvantages, and our attention focuses on the predictor’s sensitivity, specificity, positive and negative rates. ECG indexes such as P wave duration(PWD) and P-wave disparity(Pd) are good clinical parameters for the prediction of PAF due to their high sensitive and specificity, objective, reliable, and simple and cheap. P-wave dispersion can also independently predict delayed cure. However, it needs to know the knowledge of ECG, and professional technicians to measure and analyze them. Echocardiography indexes such as left atrial diameter(LAD), left ventricular function and left ventricular mass(LVM) are also useful parameters, but this kind of instruments needs to operate and measure accurately by skilled professionals. Biomarkers developed recently, such as serum Albumin, ANP, BNP, and CRP, are digital parameters and promising predictors due to their high sensitivity and specificity.

 

Presently, new ECHO indexes such as E/Va, E/Vp, LVM and novel biomarkers such

as ANP, BNP and CRP, are still being underestated as indexes for PAF prediction, and

we expect more clinical data to confirm their scientific value which including the

sensitivity and specificity. Therefore, it’s better to use ECG indexes that we often used

such as PWD and Pd as controls. So far, no authors in fact can answer when PAF will

occur, that is to say, the accurate time of PAF occurrence is still unknown. Prediction

is to prevent and treat in time, so we expect simple, reliable, cheap and high

sensitivity and specificity indexes will help us to do better than ever to control and

decrease PAF related cardio- and cerebrovascular events, such as stroke and AMI.

In future, more work for PAF’s prediction are waiting for us and our study. On the one hand, how to develop better predictors by several tools such as ECG, ECHO and biomarkers; On the other hand, synthetic methods which based combined parameters are probably more accurate and promising for prediction of PAF. To develop a new method which combined ECHO or ECG with biomarkers such as BNP will help us to predict PAF more accurately. Of course, it’s scientific value need to confirm by more patients’ data in our clinical work. Absolutely, by these predictors and methods, especially indexes of higher sensitivity and specificity, we believe that PAF will be controlled and decreased greatly by primary and secondary prevention with ACEI, ASA and anti-arrhythmia drugs, and PAF’s complications and CVEs such as AMI or ACS, heart failure and stroke will also decrease greatly.

 

Acknowledgements

 

No funding was received. Authors thanked greatly experts for critical review. This manuscript was finished in December, 2006.

 

 

References

 

1. He YM, Yang XJ, Hui J, Jiang TB, Song JP, Liu ZH, Jiang WP. Low serum albumin levels in patients with paroxysmal atrial fibrillation: what does it mean? Acta Cardiol. 2006 Jun;61(3):333-7. 

2. Yamada T, Murakami Y, Okada T, Okamoto M, Shimizu T, Toyama J, Yoshida Y, Tsuboi N, Ito T, Muto M, Kondo T, Inden Y, Hirai M, Murohara T. Plasma atrial natriuretic Peptide and brain natriuretic Peptide levels after radiofrequency catheter ablation of atrial fibrillation. Am J Cardiol. 2006 Jun 15;97(12):1741-4. 

 

3. Li J, Wang L. B-type natriuretic peptide levels in patients with paroxysmal lone atrial fibrillation. Heart Vessels. 2006; 21(3):137-40.

4. Dernellis J, Panaretou M. Effect of C-reactive protein reduction on paroxysmal atrial fibrillation. Am Heart J. 2005 Nov;150(5):1064.

 

5. Michalkiewicz D, Dziuk M, Kaminski G, Olszewski R, Cholewa M, Cwetsch A, Markuszewski L. Detection of patients at risk for paroxysmal atrial fibrillation (PAF) by signal averaged P wave, standard ECG and echocardiography. Pol Merkur Lekarski. 2006 Jan;20(115):69-72

6. Aytemir K, Amasyali B, Abali G, Kose S, Kilic A, Onalan O, Tokgozoglu L, Kabakci G, Ozkutlu H, Nazli N, Isik E, Oto A. The signal-averaged P-wave duration is longer in hypertensive patients with history of paroxysmal atrial fibrillation as compared to those without. Int J Cardiol. 2005 Aug 3;103(1):37-40.

7.  Maia IG, Cruz Filho F, Sa R, Alves PA. High-resolution P-wave electrocardiogram in patients with a history of paroxysmal atrial fibrillation. Arq Bras Cardiol. 1995 Apr;64(4):311-3.

8. Aytemir K, Amasyali B, Kose S, Kilic A, Abali G, Oto A, Isik E. Maximum P-wave duration and P-wave dispersion predict recurrence of paroxysmal atrial fibrillation in patients with Wolff-Parkinson-White syndrome after successful radiofrequency catheter ablation. J Interv Card Electrophysiol. 2004 Aug;11(1):21-7. 

9. Yigit Z, Akdur H, Ersanli M, Okcun B, Guven O. The effect of exercise to P wave dispersion and its evaluation as a predictor of atrial fibrillation. Ann Noninvasive Electrocardiol. 2003 Oct;8(4):308-12. 

10. Ozer N, Aytemir K, Atalar E, Sade E, Aksoyek S, Ovunc K, Acyl T, Nazly N, Ozmen F, Oto A, Kes S. P wave dispersion in hypertensive patients with paroxysmal atrial fibrillation. Pacing Clin Electrophysiol. 2000 Nov; 23(11 Pt 2):1859-62. 

11. Hiraki T, Ikeda H, Yoshida T, Inage T, Ohe M, Ohtsubo H, Matsumoto M, Hamada T, Kubara I, Imaizumi T. P wave signal-averaged electrocardiography predicts recurrence of paroxysmal atrial fibrillation in patients with Wolff-Parkinson-White syndrome who underwent successful catheter ablation: a prospective study. J Cardiovasc Electrophysiol. 2002 Oct;13(10):1003-8. 

12. Abe R, Nishida T. The criteria for the prediction of paroxysmal atrial fibrillation by time domain analysis of the P wave-triggered signal-averaged electrocardiogram. Nippon Rinsho. 1995 Feb;53(2):496-502.

13. Thong T, McNames J, Aboy M, Goldstein B. Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes. IEEE Trans Biomed Eng. 2004 Apr;51(4):561-9. 

14. Ishimoto N, Ito M, Kinoshita M. Signal-averaged P-wave abnormalities and atrial size in patients with and without idiopathic paroxysmal atrial fibrillation. Am Heart J. 2000 Apr;139(4):684-9. 

15. Dilaveris PE, Gialafos EJ, Chrissos D, Andrikopoulos GK, Richter DJ, Lazaki E,

Gialafos JE. Detection of hypertensive patients at risk for paroxysmal atrial fibrillation during sinus rhythm by computer-assisted P wave analysis. J Hypertens. 1999 Oct;17(10):1463-70. 

16. Dilaveris PE, Gialafos EJ, Sideris SK, Theopistou AM, Andrikopoulos GK, Kyriakidis M, Gialafos JE, Toutouzas PK. Simple electrocardiographic markers for the prediction of paroxysmal idiopathic atrial fibrillation. Am Heart J. 1998 May;135(5 Pt 1):733-8.

17.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(3):157-63.

18. Lee SH, Tai CT, Hsieh MH, Tsao HM, Lin YJ, Chang SL, Huang JL, Lee KT, Chen YJ, Cheng JJ, Chen SA. Predictors of non-pulmonary vein ectopic beats initiating paroxysmal atrial fibrillation: implication for catheter ablation. J Am Coll Cardiol. 2005 Sep 20;46(6):1054-9. 

19.Rotter M, Jais P, Garrigue S, Sanders P, Hocini M, Hsu LF, Takahashi Y, Rostock T, Sacher F, Clementy J, Haissaguerre M. Clinical predictors of noninducibility of sustained atrial fibrillation after pulmonary vein isolation. J Cardiovasc Electrophysiol. 2005;16(12):1298-303.

20. Antonelli D, Peres D, Freedberg NA, Feldman A, Rosenfeld T. Incidence of postdischarge symptomatic paroxysmal atrial fibrillation in patients who underwent coronary artery bypass graft: long-term follow-up. Pacing Clin Electrophysiol. 2004 Mar;27(3):365-7. 

21.Gerstenfeld EP, Sauer W, Callans DJ, Dixit S, Lin D, Russo AM, Beldner S,McKernan M, Marchlinski FE. Predictors of success after selective pulmonary vein isolation of arrhythmogenic pulmonary veins for treatment of atrial fibrillation. Heart Rhythm. 2006;3(2):165-70.

 

22.Hemels ME, van den Berg MP, Ranchor AV, van Sonderen EL, van Gelder IC, van Veldhuisen DJ.Predictors of non-pharmacological intervention in patients with paroxysmal atrial fibrillation: Value of neuroticism. Int J Cardiol. 2006;111(1):75-9.

 

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