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INVITED COMMENTARY  
Year : 2014  |  Volume : 17  |  Issue : 3  |  Page : 187-190
Prediction of postoperative atrial fibrillation after cardiac surgery: Light at the end of the tunnel?


Department of Cardiac Surgery, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India

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Date of Web Publication3-Jul-2014
 

How to cite this article:
Varma PK. Prediction of postoperative atrial fibrillation after cardiac surgery: Light at the end of the tunnel?. Ann Card Anaesth 2014;17:187-90

How to cite this URL:
Varma PK. Prediction of postoperative atrial fibrillation after cardiac surgery: Light at the end of the tunnel?. Ann Card Anaesth [serial online] 2014 [cited 2019 Dec 7];17:187-90. Available from: http://www.annals.in/text.asp?2014/17/3/187/135845


Atrial fibrillation (AF) was first described by Sir William Harvey in 17 th century who observed chaotic motion of the atria in animals. The electrocardiography findings of AF were described in 1909 by Sir Thomas Lewis as "irregular or fibrillatory waves and irregular ventricular response". Postoperative AF (POAF) occurs in up to 40% of patients after cardiac surgery, usually between the 2 nd and 4 th postoperative day. Several factors contribute to the development of POAF. They include operative trauma, rise in atrial pressure due to postoperative ventricular stunning, increase of atrial electrical susceptibility from rapid return of temperature after cardioplegic arrest, atrial distension by fluid overload, chemical stimulation during infusion of inotropic drugs, reflex sympathetic activation, and pericardial or respiratory complications. [1] The most consistent predictor for the development of POAF is advanced age. [1] Advanced age is associated with degenerative and inflammatory modifications in atrial anatomy (dilation, fibrosis), which alters electrophysiological properties of atria, namely; shortness of effective refractory period, dispersion of refractoriness and conduction, abnormal automaticity, and anisotropic conduction, which predisposes to AF. [2] Other risk factors, include previous history of AF, male gender, left ventricular dysfunction, left atrial enlargement, valvular heart surgery, chronic obstructive pulmonary disease, chronic renal failure, diabetes mellitus, obesity, and rheumatic heart disease. [2] POAF is associated with a higher incidence of early complications, such as congestive heart failure, renal dysfunction, infections, and neurocognitive impairment and three-fold higher risk for stroke. [2] In addition, POAF lengthen the hospital stay by 4.9 days, with an extra cost of $10,000-$11,500/patient in USA. [3] The extra cost-related to this postoperative complication is estimated at approximately $2 billion/year. [2] Thus, identification of preventive strategies to decrease the incidence of POAF has clinical and economic relevance.

Different treatment modalities have been proposed to reduce AF after cardiac surgery; [4] in randomized trials, pretreatment with b-blockers, and amiodarone, was associated with risk reduction, whereas studies on other preventive drug therapies (calcium antagonists, class I antiarrhythmic agents, magnesium, digoxin, and glucose-insulin-potassium solutions) have yielded inconclusive results. [5] Observational studies have suggested a possible protective role of angiotensin-converting enzyme inhibitors, potassium supplementation, and nonsteroidal antiinflammatory drugs, but no randomized data are available on these agents. Accordingly, no pharmacological pretreatment (apart from b-blockers) has changed current clinical practice and despite relevant improvements in surgical techniques, the frequency of POAF appears to be increasing, owing to the increasing numbers of elderly patients. [5] Statins seems to have a promising role in prevention of postoperative AF. In Atorvastatin for Reduction of Myocardial Dysrhythmia After cardiac surgery-3 trial, treatment with atorvastatin 40 mg/day, initiated 1 week before elective cardiac surgery and continued in the postoperative period, significantly decreased POAF and length of hospital stay. [5]

Routine pharmacological AF prophylaxes could expose 60-80% of patients to the side-effects of antiarrhythmic drugs, with unnecessary drug-related costs and side-effects. [6] Hence it is important to identify patients at risk for POAF for better counseling of patients, effective resource utilization and for formulating an aggressive perioperative management strategy. Many scoring systems were developed for prediction of POAF. Zaman et al. [7] studying 326 elective isolated coronary artery bypass grafting (CABG) patients showed that P wave duration >155 ms, age, and male sex were able to predict POAF in 59% of patients. Amar et al. [8] found that 4 preoperative and postoperative variables were independently associated with AF development in patients undergoing isolated CABG. Mathew et al. [9] in a prospective multicenter observational study of 4657 CABG patients, obtained a final risk model with three AF risk classes (low, medium, and high risk) based on 17 preoperative, intraoperative, and postoperative variables. From the Society of Thoracic Surgeons Database, Magee et al. [10] included 14 preoperative, intraoperative, and postoperative variables for prediction of POAF. However, all of these prediction models provided controversial results, [6] revealing important limitations, and limiting their widespread adoption in the clinical practice. Recently, an additive score model (POAF) score was developed from 17,262 patients from three European centers to address many of the limitations of previous models. However, the accuracy remained only moderate with area under receiver operating characteristic (ROC) curve of 0.65 reflecting the complex and multifactorial nature of this arrhythmia. [6]

Dr. James Cox hypothesized that POAF develops due to non-uniformity of the distribution of local atrial refractory periods (the so-called "dispersion of refractoriness"). [11] When a wave-front passes through a given site in the atrium, there is a period of time afterward when that atrial site cannot be stimulated again. This period is called the "refractory period". Every site in the atrium has its own refractory period (local refractory period). Regions with short refractory period allow propagation of impulse leading to POAF. Both experimental and clinical studies have provided strong evidence that atrial ischemia is the primary stimulus that triggers the development of POAF in patients with atrial "dispersion of refractoriness". Therefore, the optimal prevention of POAF in cardiac surgical patients will likely require a combination of decreasing their vulnerability by pharmacologic means and removing the culprit stimulus by avoiding intraoperative atrial ischemia. Any prophylactic regimen that addresses only one of these approaches is likely to fail. [11] Ascione et al. [12] reported that the incidence of AF after CABG was significantly decreased, from 45% in patients operated under cardiopulmonary bypass (CPB) to only 11% in those operated without CPB, although this finding was challenged by others. In another study, [13] the authors document a significant reduction in postoperative AF, from 28% in hearts protected with cardioplegia to 9% in those operated on using short periods of ischemia (i.e. intermittent ischemia). Both these studies point to inadequate atrial protection using cardioplegic arrest as probably the trigger mechanism for POAF.

The CHADS2 acronym was derived from the individual stroke risk factors in patients with AF: Congestive heart failure, hypertension, age >75 years, diabetes mellitus, and prior stroke or TIA. Two points were given for prior stroke or TIA (hence, the subscript "2"), and one point was assigned for each of the other factors. The point system was designed to simplify the determination of stroke risk in general practice and whether or not treatment is required with anticoagulation therapy or antiplatelet therapy. [14] To complement the CHADS2 score, by the inclusion of additional risk factors, the CHA2DS2-VASc score was proposed. [15] These risk factors include age 65-74, female gender and vascular disease. In the CHA2DS2-VASc score, "age 75 and above" also has extra weight, with two points. The CHA2DS2-VASc score has been used in the new European Society of Cardiology guidelines for the management of AF. [16]

Every risk factor in CHADS2 and CHA2DS2-VASc scores is linked to the ventricular remodeling, left ventricular diastolic function, and left atrial enlargement that may increase the propensity to develop POAF. Two earlier studies examined the role of these scoring systems for prediction of POAF. POAF rates progressively increased from 6% to 44% with increasing CHA2DS2-VASc score from 0 to 3, in one study. [17] In another study, [18] examining 550 patients undergoing CABG, POAF occurred in 31.6% of patients and the high-score group (>3) had a 2.3-fold increased odds of developing AF versus the medium-score group (P < 0.0001). These studies seem to support the use of this simple scoring system for prediction of POAF, although both these studies have significant limitation in small sample size, in its retrospective nature and nonhomogeneous group of patients. In this issue of Annals of Cardiac Anaesthesia, Borde et al. [19] used CHA2DS2-VASc score to predict POAF in isolated CABG. They found a very low incidence of POAF in their group of patients - 13% versus 20-40% reported from other studies. This is hypothesis generating finding-Is the incidence of POAF really low in Indian patients or is it artefactual due to absence of diligent telemetric monitoring? In one study conducted in 70 centers across continents, [9] the incidence of POAF after CABG surgery and prior to hospital discharge was 32.3% (1503/4657). This incidence was similar among patients in the United States (33.7%), Canada (36.6%), Europe (34.0%), United Kingdom (31.6%), and the Middle East (41.6%), but the incidence was lower in South America (17.4%) and Asia (15.7%) (P < 0.001). The real incidence of POAF in Indian population may be lower than in other countries. Although the authors of the present study identified some factors that may have contributed to lower incidence of POAF, the younger age and lower body mass index of the patients are probably more pertinent reasons. The most important predictors of POAF occurrence in this study was CHA2DS2-VASc score and inotrope usage. The area under ROC curve was 0.87 showing excellent discrimination to predict POAF. Is CHA2DS2-VASc scoring the answer to the problem of POAF prediction? All the three studies point to that direction. However, only a large prospective multi-centric trial can give a definite answer. Then if proved right, it can guide the clinicians to effective POAF prophylaxis strategy; namely b-Blockers and statins for low risk group and amiodarone for high risk group. It may also necessitate the need for prophylactic left atrial appendage ligation during cardiac surgery in patients with high risk of developing POAF. [6]

 
   References Top

1.Hogue CW Jr, Creswell LL, Gutterman DD, Fleisher LA, American College of Chest Physicians. Epidemiology, mechanisms, and risks: American College of Chest Physicians guidelines for the prevention and management of postoperative atrial fibrillation after cardiac surgery. Chest 2005;128:9S-16.  Back to cited text no. 1
    
2.Echahidi N, Pibarot P, O′Hara G, Mathieu P. Mechanisms, prevention, and treatment of atrial fibrillation after cardiac surgery. J Am Coll Cardiol 2008 26;51:793-801.  Back to cited text no. 2
    
3.Aranki SF, Shaw DP, Adams DH, Rizzo RJ, Couper GS, VanderVliet M, et al. Predictors of atrial fibrillation after coronary artery surgery. Current trends and impact on hospital resources. Circulation 1996;94:390-7.  Back to cited text no. 3
    
4.Nair SG. Atrial fibrillation after cardiac surgery. Ann Card Anaesth 2010;13:196-205.  Back to cited text no. 4
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5.Patti G, Chello M, Candura D, Pasceri V, D′Ambrosio A, Covino E, 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;114:1455-61.  Back to cited text no. 5
    
6.Mariscalco G, Biancari F, Zanobini M, Cottini M, Piffaretti G, Saccocci M, et al. Bedside tool for predicting the risk of postoperative atrial fibrillation after cardiac surgery: The POAF score. J Am Heart Assoc 2014;3:e000752.  Back to cited text no. 6
    
7.Zaman AG, Archbold RA, Helft G, Paul EA, Curzen NP, Mills PG. Atrial fibrillation after coronary artery bypass surgery: A model for preoperative risk stratification. Circulation 2000;101:1403-8.  Back to cited text no. 7
    
8.Amar D, Shi W, Hogue CW Jr, Zhang H, Passman RS, Thomas B, et al. Clinical prediction rule for atrial fibrillation after coronary artery bypass grafting. J Am Coll Cardiol 2004;44:1248-53.  Back to cited text no. 8
    
9.Mathew JP, Fontes ML, Tudor IC, Ramsay J, Duke P, Mazer CD, et al. A multicenter risk index for atrial fibrillation after cardiac surgery. JAMA 2004;291:1720-9.  Back to cited text no. 9
    
10.Magee MJ, Herbert MA, Dewey TM, Edgerton JR, Ryan WH, Prince S, et al. Atrial fibrillation after coronary artery bypass grafting surgery: Development of a predictive risk algorithm. Ann Thorac Surg 2007;83:1707-12.  Back to cited text no. 10
    
11.Cox JL. A perspective of postoperative atrial fibrillation in cardiac operations. Ann Thorac Surg 1993;56:405-9.  Back to cited text no. 11
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12.Ascione R, Caputo M, Calori G, Lloyd CT, Underwood MJ, Angelini GD. Predictors of atrial fibrillation after conventional and beating heart coronary surgery: A prospective, randomized study. Circulation 2000;102:1530-5.  Back to cited text no. 12
    
13.Loubani M, Hickey MS, Spyt TJ, Galiñanes M. Residual atrial fibrillation and clinical consequences following postoperative supraventricular arrhythmias. Int J Cardiol 2000;74:125-32.  Back to cited text no. 13
    
14.Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford MJ. Validation of clinical classification schemes for predicting stroke: Results from the National Registry of Atrial Fibrillation. JAMA 2001;285:2864-70.  Back to cited text no. 14
    
15.Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: The euro heart survey on atrial fibrillation. Chest 2010;137:263-72.  Back to cited text no. 15
    
16.European Heart Rhythm Association, European Association for Cardio-Thoracic Surgery, Camm AJ, Kirchhof P, Lip GY, Schotten U, et al. Guidelines for the management of atrial fibrillation: The Task Force for the Management of Atrial Fibrillation of the European Society of Cardiology (ESC). Eur Heart J 2010;31:2369-429.  Back to cited text no. 16
    
17.Chua SK, Shyu KG, Lu MJ, Lien LM, Lin CH, Chao HH, et al. Clinical utility of CHADS2 and CHA2DS2-VASc scoring systems for predicting postoperative atrial fibrillation after cardiac surgery. J Thorac Cardiovasc Surg 2013;146:919-26.e1.  Back to cited text no. 17
    
18.Baker WL, Coleman CI, White CM, Kluger J. Use of preoperative CHA2 DS2 -VASc score to predict the risk of atrial fibrillation after cardiothoracic surgery: A nested case-control study from the Atrial Fibrillation Suppression Trials (AFIST) I, II, and III. Pharmacotherapy 2013;33:489-95.  Back to cited text no. 18
    
19.Borde D, Gandhe U, Hargave N, Pandey K, Mathew M, Joshi S. Prediction of postoperative atrial fibrillation after coronary artery bypass grafting surgery: Is CHA 2 DS 2 -VASc score useful? Ann Card Anaesth 2014;17:182-7.  Back to cited text no. 19
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Correspondence Address:
Praveen Kerala Varma
Department of Cardiac Surgery, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum - 695 011, Kerala
India
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Source of Support: None, Conflict of Interest: None


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