ATS
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Ann Thorac Surg 2009;88:802-807. doi:10.1016/j.athoracsur.2009.04.021
© 2009 The Society of Thoracic Surgeons
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Personal Folders
Right arrow Download to citation manager
Right arrow Author home page(s):
Anthony J. Tortolani
Leonard Y. Lee
Right arrow Permission Requests
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Tavakol, M.
Right arrow Articles by Heitner, J. F.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Tavakol, M.
Right arrow Articles by Heitner, J. F.
Related Collections
Right arrow Electrophysiology - arrhythmias
Right arrowRelated Article

Original Articles: Adult Cardiac

Utility of Brain Natriuretic Peptide as a Predictor of Atrial Fibrillation After Cardiac Operations

Morteza Tavakol, MS, MDa,*, Kashif Z. Hassan, MDa, Raushan K. Abdula, MDa, William Briggs, HSb, Charles E. Oribabor, MDc, Anthony J. Tortolani, MDc,d, Terrence J. Sacchi, MDa, Leonard Y. Lee, MDc,d, John F. Heitner, MDa

a Division of Cardiology, Department of Medicine, New York Methodist Hospital, Brooklyn, New York
b Department of Statistics, New York Methodist Hospital, Brooklyn, New York
c Department of Cardiothoracic Surgery, New York Methodist Hospital, Brooklyn, New York
d Department of Cardiothoracic Surgery, Weill Medical College of Cornell University, New York, New York

Accepted for publication April 6, 2009.

* Address correspondence to Dr Tavakol, Research Fellow, New York Methodist Hospital, Department of Cardiology, Division of Medicine, 506 6th St, 2nd Floor, Division of Cardiology, Brooklyn, NY 11215 (Email: motavakol{at}yahoo.com).


   Abstract
Top
 Abstract
Introduction
 Material and Methods
 Results
 Comment
 References
 
Background: Atrial fibrillation (AF) occurs frequently after coronary bypass grafting and valve operations. Brain natriuretic peptide (BNP) has been shown to predict recurrence of AF in congestive heart failure. It is a potential biomarker for preoperative risk stratification for development of AF in at-risk patients.

Methods: A total of 398 consecutive patients were prospectively evaluated for new-onset AF after heart operations. Patients with a history of AF and presence of permanent pacemaker were excluded. BNP levels were measured before and immediately after the operation.

Results: AF occurred in 20%. AF was more likely to develop in patients who were older, who underwent valve operations, had a lower ejection fraction, and a larger left atrial size. Preoperative exposure to statins (62% vs 43%, p < 0.01) and angiotensin inhibitors (60% vs 45%, p = 0.02) was more common in patients without AF. BNP values were insignificantly higher preoperatively (361 vs 302 mg/dL, p = 0.3) and postoperatively (312 vs. 229 mg/dL, p = 0.15) in patients with AF. Multivariate logistic analysis showed that older age (odds ratio [OR], 3.1, 95% confidence interval [CI], 1.7 to 5.6), lower ejection fraction (OR, 2.0; 95% CI, 1.2 to 3.3), larger left atrial size (OR, 3.1; 95% CI, 1.9 to 4.9), and nonuse of angiotensin inhibitors (OR, 2.3; 95% CI, 1.1 to 4.8) were independently associated with AF.

Conclusions: This study does not support use of BNP for prediction of AF. Age, low ejection fraction, large left atrial size, and nonuse of angiotensin blocking agents were found to be significant predictors of AF development.


   Introduction
Top
 Abstract
 Introduction
Material and Methods
 Results
 Comment
 References
 
Atrial fibrillation (AF) is a relatively common complication after coronary artery bypass grafting (CABG) and valve operations, with a reported incidence of about 30% [1, 2]. Its onset in this critical period has been associated with increasing heart failure, myocardial infarction, stroke, and death. As a result, the occurrence of AF requires intensive care with additional need for treatments leading to longer hospital stays and an increased economic burden [3–5].

Recognizing the patient population that will most likely develop AF has become crucial because new studies have highlighted reliable medical prophylaxis strategies for its prevention. Recent trials with antiarrhythmic medications [6], β-blockers [7], statins [8, 9], and corticosteroids [10, 11] have been shown to consistently decrease the incidence of postoperative AF. Generalized prophylactic treatment of all patients, however, is not without its own risk because these medications have significant side effects [11]. Identifying risk factors and biochemical markers that can reliably predict the subset of patients most likely to develop AF has thus become an intense focus of study.

Male gender, older age, congestive heart failure (CHF), increased left atrial size, and specific surgical procedures such as mitral valve repair, are only a few of the conditions associated with increased incidence of AF [2, 4, 12, 13]. This association is weak and relatively inconsistent at accurately predicting AF. As a result, recent efforts have focused on the utility of biochemical markers as predictors of AF.

The addition of a specific serum marker to existing preoperative risk stratification could provide a timely, cost-effective method to delineate patient populations at greatest risk for developing AF and thus warrant the risk of exposure to antiarrhythmic therapy. Brain natriuretic peptide (BNP) is one such potential biomarker that has been shown to rise with the onset of AF and decrease with the restoration of sinus rhythm [14–16]. It can accurately predict the recurrence of AF and rehospitalization in patients with CHF [17], and therefore, may potentially be useful in preoperative risk stratification for AF. Currently, conflicting data have been reported about the prognostic strength of BNP in postoperative AF [18, 19]. This study addresses the utility of BNP as biochemical marker for development of AF and compares it with previously described risk factors in a cohort of patients undergoing CABG and valve operations.


   Material and Methods
Top
 Abstract
 Introduction
 Material and Methods
Results
 Comment
 References
 
This study was approved by the hospital Institutional Review Board. Owing to the retrospective nature of the study, patient consent was waived with permission of the chairmen of surgery and the chairperson of the Institutional Review Board. All data were stripped of patient identifiers.

Patients
We retrospectively evaluated all patients undergoing valve, CABG, or valve and CABG operations from July 2005 through December 2006. A total of 398 consecutive patients were evaluated, and 70 were excluded from analysis because of incomplete data in 33, presence of a permanent pacemaker in 5, or prior AF documented from history or recorded preoperatively in 32. Sepsis was excluded in all patients.

The final data set consisted of 328 adult patients in sinus rhythm undergoing CABG and valve procedures. A comprehensive evaluation was obtained on each patient, including detailed history, physical examination, electrocardiogram (ECG), 2-dimensional (2D) echocardiogram, and medications received before and after the operation. BNP levels were assessed from venous blood samples collected on the morning before the operation and within 1 hour after cardiopulmonary bypass. Postoperative renal function was assessed prospectively to account for the effect of renal insufficiency on BNP levels, with chronic kidney disease defined as creatinine clearance of less than 30 mL/min calculated by the Cockcroft-Gault formula.

Anesthesia and surgical management were conducted according to institution protocols. Briefly, induction of general anesthesia consisted of a combination of thiopental, midazolam, or etomidate, and maintenance with isoflurane, pancuronium, and fentanyl. Anticoagulation consisted of 400 U/kg of unfractionated heparin. At the conclusion of cardiopulmonary bypass, anticoagulation was reversed with 250 mg of protamine, with an additional 50 mg administered in the following 10 minutes in the presence of ongoing bleeding.

Preoperative prophylaxis with amiodarone was administered according to institution protocol to any patient aged older than 70 years, an ejection fraction (EF) of less than 0.30 based on preoperative echocardiogram, hypertrophic obstructive cardiomyopathy, and those undergoing valve operations or aneurysm repairs. Patients with new-onset postoperative AF were treated with amiodarone when hemodynamically stable.

Postoperative anticoagulation with heparin and warfarin was based on an individual risk factors and events (age, risk factors, bleeding status, chest tube drainage) at the discretion of the intensivist and surgeon.

All patients were admitted to the cardiothoracic intensive care unit where they were placed on continuous cardiac monitoring preoperatively and until hospital discharge. They were assessed for the development of AF of any duration before the operation and at any time in the postoperative period on physician assessment of telemetry records with confirmation by 12-lead ECG recording. Transient AF of short duration, without confirmation by ECG, was not included as an occurrence of AF. A 12-lead ECG was obtained daily, and when necessary to confirm rhythm abnormalities noted on telemetry. New AF was defined as an irregular ventricular rhythm without P waves. Transthoracic and transesophageal 2D echocardiograms were performed on all patients within 2 weeks preoperatively and during the postoperative hospital stay. EF was calculated by the Teichholz method, and size of the left atrium was measured in the parasternal long axis view. Blood samples were analyzed for BNP using a fluorescence immunoassay kit (Bayer-Siemens, Deerfield, IL).

Statistical Analysis
Graphic exploratory analysis was performed to ensure that the data would meet the assumptions of the standard statistical models that followed. To predict AF, logistic regression models were built controlling for all available variables. We found that log transformation of preoperative and postoperative BNP brought it in line with standard assumptions; thus, all results of BNP that follow used log values (except in Fig 1). BNP also demonstrated a nonlinear relationship with AF, which was accounted for in the logistic regression models by the use of fourth-order restricted cubic splines [20]. Results are presented as odds ratios (OR) with their 95% confidence interval (CI) estimates. All model effects were estimated for each variable by holding all the remaining variables in the model fixed at their median value, and then calculating the change in the odds of the prediction as the target variable changed from its first to third quartile (Harrell). All analysis was done using the R statistical software platform [21].


Figure 1
View larger version (22K):
[in this window]
[in a new window]

  		Fig 1. Comparison of (nonlog-transformed) brain naturietic peptide (BNP) values (A) before and (B) after value operation or coronary artery bypass grafting (CABG) in patients in whom atrial fibrillation (AFIB) did (black bars) or did not (gray bars) develop. (C) Change in BNP values before (black bars) and after (gray bars) procedures based on whether atrial fibrillation developed (AFIB) or did not develop (No AFIB) after a valve (V) or CABG (C) procedure. Data are presented with the standard deviation.

 

   Results
Top
 Abstract
 Introduction
 Material and Methods
 Results
Comment
 References
 
The baseline characteristics of the study patients are summarized in Table 1. Three patients underwent off-pump operations, and only 3 patients required an emergency procedure. Of the 33 patients excluded due to lack of laboratory or echocardiographic data, AF developed in 8 (24%). AF occurred in 20% of the population. Patients who presented with AF were on average 6 years older, more likely to be women, and had a higher incidence of valve operations. They were also more likely to have lower EF and larger left atrial size on preoperative 2D echocardiograms. Patients who did not present with AF were more likely to have received statins (163 [63%] no AF vs 29 [43%] AF, p < 0.01) and angiotensin converting enzyme inhibitors (ACE) or angiotensin receptor blockers (ARB; 156 [60%] no AF vs 30 [45%] AF; p = 0.02).


View this table:
[in this window]
[in a new window]

  		Table 1 Patient Demographics
 
There was a trend toward higher BNP values before and immediately after the operation in the AF group (361 ± 387 vs 302 ± 541 mg/dL no AF, p = 0.3). Subgroup analysis by type of procedure failed to show a specific trend, with high variation in BNP levels particularly in patients undergoing valve operations (Fig 1A and B). We also assessed differences in BNP values before and after the operation to determine if a significant association existed between the change in BNP between the groups. BNP values declined postoperatively across all groups, without relation to development of AF (p = 0.7; Fig 1C).

As a result of high variation in BNP with often extremely large values, BNP levels were log-transformed to reduce the extremes and create a more normal distribution. The preoperative mean log-BNP was 5.4 in the AF group and 4.7 in the non-AF group 7 (p = 0.001). The mean postoperative log-BNP was 5.3 in the AF group and 4.6 in the no-AF group (p < 0.001). After controlling for other variables, the difference was no longer significant (preoperative log-BNP: OR, 0.9; 95% CI, 0.34 to 2.4; postoperative log-BNP: OR, 1.8; 95% CI, 0.5 to 6).

Multivariate logistic regression models were also constructed to identify independent association with development of AF (Fig 2). Older age (OR, 3.1; 95% CI, 1.7 to 5.6), lower preoperative EF (OR, 2.0; 95% CI, 1.2 to 3.3), large left atrial size (OR, 3.1; 95% CI, 1.9 to 4.9), and nonuse of ACE/ARB (OR, 2.3; 95% CI, 1.1 to 4.8) were independently associated risk factors for development of AF (Fig 3). Other factors not independently related to AF development were female gender and nonuse of statins.


Figure 2
View larger version (36K):
[in this window]
[in a new window]

  		Fig 2. Scatter-plot overlayed with a logistic regression model showing relationship between increased probability of developing atrial fibrillation (Afib; y-axis) with (A) increasing age, (B) decreased ejection fraction (EF), and (D) larger left atrial (LA) size. (C) A possible biphasic relationship exists for preoperative brain naturietic peptide (BNP) and occurrence of atrial fibrillation.

 

Figure 3
View larger version (12K):
[in this window]
[in a new window]

  		Fig 3. Model shows the odds ratios of developing atrial fibrillation. The risk factors of increasing age, left atrial (LA) size, nonuse of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin-receptor blockers (ARBs), and decreased ejection fraction are significantly associated with onset of AF. Higher preoperative and postoperative log-transformed brain naturietic peptide (BNP) levels do not significantly increase the odds of developing AF. Data are presented with the 95% confidence intervals.

 

   Comment
Top
 Abstract
 Introduction
 Material and Methods
 Results
 Comment
References
 
This large study examined BNP levels as a predictive tool for developing postoperative AF in patients undergoing valve operations or CABG. BNP levels varied widely across the studied patient population and were a not reliable predictor of AF. Although BNP levels were slightly more elevated in the AF population, we could not identify a consistent reliable association between BNP values and the risk of postoperative AF. Our study confirmed previously described risk factors of older age, larger left atrial size, and low EF as independent predictors of AF. We also report an independent association with nonuse of ACE/ARBs and new-onset postoperative AF.

The incidence of postoperative AF has been reported from 17% to 60% after cardiac operations, with most studies reporting its occurrence in approximately 30% of this population [3, 4, 19]. In the crucial period after the operation, the occurrence of this arrhythmia at such an alarmingly high rate carries significant concerns regarding hospital outcome and utilization of hospital resources. Worsening heart failure, perioperative myocardial infarction, stroke, bowel ischemia, renal failure, reintubation, and an increased 30-day mortality rate are only some of the postoperative events that have been attributed to the occurrence of AF [2, 3, 22]. Postoperative stroke and transient ischemic attacks have repeatedly been observed after the onset of AF, with a reported incidence of 1% to 4% and a twofold increase in risk compared with patients without AF [22–25]. AF patients remain in intensive care twice as long as other patients and have a twofold to fourfold increase in the number of readmissions to the intensive care unit [4, 24]. In a study of 570 consecutive CABG patients, Arnaki and colleagues [3] showed that the mean length of hospital stay postoperatively was 15.3 days for patients with AF compared with 9.3 days for those who remained in sinus rhythm. The adjusted length of stay attributed to AF was 5 days, corresponding to roughly a $10,000 increase in hospital charges.

Prevention of AF after CABG is an attainable goal, and many randomized trials have recently evaluated the effectiveness of pharmacologic interventions for prevention of AF. A recent meta-analysis of 52 randomized trials comparing effects of pharmacologic interventions showed that β-blockers, sotalol, and amiodarone were all effective at lowering the incidence of AF and length of stay [23]. Patients receiving combination therapy with amiodarone and metoprolol have a reduction in frequency of AF by nearly 30% compared with placebo [6]. Previous trials with ACE and ARBs have shown reduced incidence of both new-onset and recurrent AF [26, 27]. Application of these findings to patients undergoing CABG and valve operations produced a nonsignificant 29% reduction in the incidence of postoperative AF [28]. Statins have also been effective preventing new onset AF in patients with coronary artery disease as well as those undergoing CABG [8, 29]. Such findings have been replicated in our cohort.

Most recently, intravenous corticosteroids in the perioperative setting decreased the incidence of AF [10, 11]. One such study using perioperative methylprednisolone showed a decrease in the occurrence of AF but no change in intensive care length of stay. Patients treated with steroids had a significantly higher number of major and minor postoperative complications attributable to the effects of steroids [10]. Prophylactic use of these medications in an entire cohort is also costly. Mahoney and colleagues [30] estimated that prophylactic use of amiodarone for their entire population would have had a minimal change in the mean in-hospital cost for the number of arrhythmias averted. Prophylactic therapy was cost effective for only 5% of valve patients with a predicted risk of AF exceeding 45%. They concluded that the cost-effectiveness of prophylactic amiodarone varies according to the predicted risk of AF [30]. It appears, then, that consideration of prophylactic treatment would be best directed to the population at highest risk for developing AF.

Specific patient characteristics, medical history, and surgical practices have been reported over the years as associated with AF [3,4, 12]. Multivariate risk indexes for preoperative risk assessment have combined a number of these factors in attempts to accurately predict the onset of AF [23, 31]; however, the ability to effectively predict postoperative complications, hospital stay, and mortality remains modest. As a result, recent research has turned to use of biomarkers as a means of providing an efficient cost-effective tool for assessing risk for AF. The hypothesis that biomarkers can predict AF was recently tested in a study that measured levels of 21 biomarkers immediately after separation from cardiopulmonary bypass. In 67 patients with postoperative AF, plasma activator inhibitor 1 was an independent predictor of AF, especially in the younger patient population [32].

Elevated BNP is a proven marker of cardiac failure and dysfunction and has been reported to have predictive capability in specific scenarios. In a study of 98 male veterans, receiver operating curve analysis of BNP showed that values exceeding 385 pg/mL had high specificity and accuracy for predicting postoperative complications, hospital stay, and 1 year mortality after heart operations. Arrhythmias were a documented complication, but the actual number of patients with AF was not reported [18]. Looking at 185 patients who underwent cardiac procedures, Wazni and colleagues [19] noted that preoperative plasma BNP levels were higher in patients who developed AF (615 vs 444 pg/mL). After adjustment for other risk factors, BNP in the highest quartile was shown to be a strong independent predictor of AF. It was recommended that these patients would be good candidates for prophylactic therapy [19]. Interestingly, this study of biomarkers found that N-terminal pro-BNP was significantly elevated in AF population, but was not shown to be an independent predictor, similar to the results of our study on BNP.

One limitation of our study was the high variability of BNP levels. This can be explained by severe congestive heart failure or by conditions that could have produced a false elevation. False-positive results have been shown to occur from chronic kidney disease, hyperthyroidism, sepsis, or severe anemia; however, there was no significant preponderance of any of these factors in the cohorts with or without AF in our study.

We recognize that preoperative exposure to amiodarone in the prespecified at-risk population likely decreased the incidence of new onset postoperative AF in the 34% of patients who received amiodarone without developing AF. Previous studies have shown that preoperative oral amiodarone significantly reduces the onset of postoperative AF in patients undergoing complex cardiac procedures, an absolute reduction of 28% [33]. This could create a potential type II error on analysis of BNP values postoperatively.

Our study included patients with postoperative AF of any duration. The duration of AF was sufficiently prolonged and recurrent to be confirmed by 12-lead ECG, thus transient episodes of AF would have been excluded. To our knowledge, there are no published studies on the cutoff duration where AF has clinical impact. It is possible, however, that BNP levels will be unaffected in patients with paroxysmal AF of brief duration compared with patients with persistent postoperative AF. We were unable to delineate this association from available data. We are reassured by reports of large, retrospective studies including patients with AF of any duration that have shown greater incidence of strokes, decrease in-hospital death, and 4 to 5 year survival rates that are similar to studies excluding patients with AF exceeding 5 to 10 minutes' duration [34].

In conclusion, the current study suggests that the risk of AF is significantly higher in older patients with low EF and increased left atrial size. Preoperative treatment with statins, ACE inhibitors, or ARBs may prove to be a safe, effective means of medical prophylaxis in patients undergoing CABG and valve operations. BNP was not a reliable predictor of AF. As evidence emerges about new biomarkers and their utility, future trials are needed to determine the utility of targeted prophylactic medical therapy in prevention of AF based on the available risk factors and biomarkers.


   References
Top
 Abstract
 Introduction
 Material and Methods
 Results
 Comment
 References
 

  1. Ommen SR, Odell JA, Stanton MS. Atrial arrhythmias after cardiothoracic surgery N Engl J Med 1997;336:1429-1434.[Medline]
  2. Almassi GH, Schowalter T, Nicolsi AC, et al. Atrial fibrillation after cardiac surgery. A major morbid event?. Ann Surg 1997;226:501-513.[Medline]
  3. Aranki SF, Shaw DP, Adams DH, et al. Predictors of atrial fibrillation after coronary artery surgery: current trends and impact on hospital resources Circulation 1996;94:390-397.[Abstract/Free Full Text]
  4. Matthew JP, Parks R, Savino JS, et al. Atrial fibrillation following coronary artery bypass graft surgery: predictors, outcomes, and resource utilization JAMA 1996;276:300-306.[Abstract/Free Full Text]
  5. Kim MH, Deeb GM, Morady F, et al. Effect of postoperative atrial fibrillation on length of stay after cardiac surgery. The postoperative atrial fibrillation in cardiac surgery study PACS. Am J Cardiol 2001;87:881-885.[Medline]
  6. Auer J, Weber T, Berent R, et al. A comparison between oral antiarrhythmic drugs in the prevention of atrial fibrillation after cardiac surgery: the pilot study of prevention of postoperative atrial fibrillation (SPPAF), a randomized, placebo-controlled trial Am Heart J 2004;147:636-643.[Medline]
  7. Halonen J, Hakala T, Auvinen T, et al. Intravenous administration of metoprolol is more effective than oral administration in the prevention of atrial fibrillation after cardiac surgery Circulation 2006;114:I 1-I 14.[Medline]
  8. Marin F, Pascual DA, Roldan V, et al. Statins and postoperative risk of atrial fibrillation following coronary artery bypass grafting Am J Cardiol 2006;97:55-60.[Medline]
  9. Patti G, Chello M, Candura D, et al. Randomized trial of atorvastatin for reduction of postoperative atrial fibrillation in patients undergoing cardiac surgery. Results of the ARMYDA-3 (atorvastatin for reduction of myocardial dysrhythmia after cardiac surgery) study. Circulation 2006;114:1455-1461.[Abstract/Free Full Text]
  10. Prasongsukran K, Abel JG, Jamieson WRE, et al. The effects of steroids on the occurrence of postoperative atrial fibrillation after coronary artery bypass grafting surgery J Thorac Cardiovasc Surg 2005;130:93-98.[Abstract/Free Full Text]
  11. Halonen J, Halonen P, Jarvinen O, et al. Corticosteroids for the prevention of atrial fibrillation after cardiac surgery: a randomized controlled trial JAMA 2007;297:1562-1567.[Abstract/Free Full Text]
  12. Borzak S, Tisdale JE, Amin NB, et al. Atrial fibrillation after bypass surgery. Does the arrhythmia or the characteristics of the patients prolong hospital stay?. Chest 1998;113:1489-1491.[Abstract/Free Full Text]
  13. Hakala T, Hedman A, Turpeinen A, Kettunen R, Vuolteenaho O, Hippelainen M. Prediction of atrial fibrillation after coronary artery bypass grafting by measuring atrial peptide levels and preoperative atrial dimensions Eur J Cardiothorac Surg 2002;22:939-943.[Abstract/Free Full Text]
  14. Jourdain P, Bellorini M, Funck F, et al. Short-term effects of sinus rhythm restoration in patients with lone atrial fibrillation: a hormonal study Eur J Heart Fail 2002;4:263-267.[Abstract/Free Full Text]
  15. Ohta Y, Shimada T, Yoshitomi H, et al. Drop in plasma brain natriuretic peptide levels after successful direct current cardioversion in chronic atrial fibrillation Can J Cardiol 2001;17:415-420.[Medline]
  16. Albage A, Kenneback G, van der Linden J, Berglund H. Improved neurohormonal markers of ventricular function after restoring sinus rhythm by the maze procedure Ann Thorac Surg 2003;75:790-795.[Abstract/Free Full Text]
  17. Mabuchi N, Tsutamoto T, Maeda K, Kinoshita M. Plasma cardiac natriuretic peptides as biochemical markers of recurrence of atrila fibrillation in patients with mild congestive heart failure Jpn Circ J 2000;64:765-771.[Medline]
  18. Hutfless R, Kazanegra R, Madani M, et al. Utility of B-type natriuretic peptide in predicting postoperative complications and outcomes in patients undergoing heart surgery J Am Coll Cardiol 2004;43:1873-1879.[Abstract/Free Full Text]
  19. Wazni OM, Martin DO, Marouche NF, et al. Plasma B-type natriuretic peptide levels predict postoperative atrial fibrillation in patients undergoing cardiac surgery Circulation 2004;110:124-127.[Abstract/Free Full Text]
  20. Harrell F. Regression modeling strategiesNew York: Springer; 2001. pp. 600.
  21. R Development Core Team R: a language and environment for statistical computingVienna, Austria: R Foundation for Statistical Computing; 2008http://www.R-project.org 2008Accessed: Apr 28, 2009.
  22. Lahtinen J, Biancari F, Salmela E, et al. Postoperative atrial fibrillation is a major cause of stroke after on-pump coronary artery bypass surgery Ann Thorac Surg 2004;77:1241-1244.[Abstract/Free Full Text]
  23. Crystal E, Connolly S, Sleik K, Ginger TJ, Yusuf S. Interventions on prevention of postoperative atrial fibrillation in patients undergoing heart surgery Circulation 2002;106:75-80.[Abstract/Free Full Text]
  24. Hakala T, Pitkänen O, Hippeläinen M. Feasibility of predicting the risk of atrial fibrillation after coronary artery bypass surgery with logistic regression model Scand J Surg 2002;91:339-344.[Medline]
  25. Taylor GJ, Malik SA, Colliver JA, et al. Usefulness of atrial fibrillation as a predictor of stroke after isolated coronary artery bypass grafting Am J Cardiol 1987;60:905-907.[Medline]
  26. Birnie DH, Gollob M, Healey JS. Clinical trials, the rennin angiotensin system and atrial fibrillation Curr Opin Cardiol 2006;24:368-375.
  27. Wachtell K, Lehto M, Gerdts E, et al. Angiotensin II receptor blockade reduces new-onset atrial fibrillation and subsequent stroke compared to atenolol: the Losartan Intervention For End Point Reduction in Hypertension (LIFE) study J Am Coll Cardiol 2005;45:712-719.[Abstract/Free Full Text]
  28. White CM, Kluger J, Lertsburapa K, Faheem O, Coleman CI. Effect of preoperative angiotensin converting enzyme inhibitor or angiotensin receptor blocker use on the frequency of atrial fibrillation after cardiac surgery: a cohort study from the atrial fibrillation suppression trials II and III Eur J Cardiothorac Surg 2007;31:817-820.[Abstract/Free Full Text]
  29. Young-Xu Y, Jabbour S, Goldberg R, et al. Usefulness of statin drugs in protecting against atrial fibrillation in patients with coronary artery disease Am J Cardiol 2003;92:1379-1383.[Medline]
  30. Mahoney EM, Thompson TD, Veledar E, Williams J, Weintraub WS. Cost-effectiveness of targeting patients undergoing cardiac surgery for therapy with intravenous amiodarone to prevent atrial fibrillation J Am Coll Cardiol 2002;40:737-745.[Abstract/Free Full Text]
  31. Zaman A, Archbold A, Helft G, Paul EA, Curzen NP, Mills PG. Atrial fibrillation after coronary artery bypass graft surgery Circulation 2000;101:1403-1408.[Abstract/Free Full Text]
  32. Pretorius M, Donahue BS, Yu C, et al. Plasminogen activator inhibitor-1 as a predictor of postoperative atrial fibrillation after cardiopulmonary bypass Circulation 2007;116(suppl I):I-1-I-7.[Abstract/Free Full Text]
  33. Daoud EG, Strickberger SA, Man C, et al. Preoperative amiodarone as prophylaxis against atrial fibrillation after heart surgery N Engl J Med 1997;337:1785-1791.[Medline]
  34. Villareal RP, Hariharan R, Liu BC, et al. Postoperative atrial fibrillation and mortality after coronary artery bypass surgery J Am Coll Cardiol 2004;43:742-748.[Abstract/Free Full Text]

Related Article

Invited Commentary
Stuart P. Thomas
Ann. Thorac. Surg. 2009 88: 807-808. [Extract] [Full Text] [PDF]



This article has been cited by other articles:


Home page
 Eur J Cardiothorac SurgHome page
E. Litton and K. M. Ho
The use of pre-operative brain natriuretic peptides as a predictor of adverse outcomes after cardiac surgery: a systematic review and meta-analysis
Eur J Cardiothorac Surg, October 20, 2011; (2011) ezr007v1.
[Abstract] [Full Text] [PDF]

Home page
 Eur J Cardiothorac SurgHome page
Y. Shingu, S. Kubota, S. Wakasa, N. Ebuoka, D. Mori, T. Ooka, T. Tachibana, and Y. Matsui
Left-ventricular electromechanical delay is prolonged in patients with postoperative atrial fibrillation
Eur J Cardiothorac Surg, May 1, 2011; 39(5): 684 - 688.
[Abstract] [Full Text] [PDF]

Home page
 Ann. Thorac. Surg.Home page
S. P. Thomas
Invited Commentary
Ann. Thorac. Surg., September 1, 2009; 88(3): 807 - 808.
[Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Personal Folders
Right arrow Download to citation manager
Right arrow Author home page(s):
Anthony J. Tortolani
Leonard Y. Lee
Right arrow Permission Requests
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Tavakol, M.
Right arrow Articles by Heitner, J. F.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Tavakol, M.
Right arrow Articles by Heitner, J. F.
Related Collections
Right arrow Electrophysiology - arrhythmias
Right arrowRelated Article

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
ANN THORAC SURG ASIAN CARDIOVASC THORAC ANN EUR J CARDIOTHORAC SURG
J THORAC CARDIOVASC SURG ICVTS ALL CTSNet JOURNALS