Abstract
Objectives
Patients with postoperative atrial fibrillation (POAF) have increased risk of both short- and long-term mortality and morbidity; therefore, prediction of POAF is crucial in the preoperative period of the patients undergoing coronary artery bypass graft surgery. Electrocardiography (ECG) is the simplest and cost-effective tool in the preoperative workup of the patients for the prediction of POAF. A newly defined ECG parameter P wave peak time (PWPT) has been shown as a marker of atrial fibrillation development in non-surgical patients and we investigated its role in patients undergoing cardiac surgery.
Method
A total of 327 patients undergoing isolated or combined cardiac surgery were involved and the primary endpoint was defined as the development of POAF. The study population was divided into two groups based on the presence or absence of POAF. Groups were compared for both standard P wave parameters and for PWPT on surface ECG. The predictors of POAF were assessed by multivariate regression analysis.
Results
The frequency of POAF was 20.4% (n = 67). P wave peak time in leads D2 (65.1 ± 11.8 vs 57.2 ± 10, p < 0.01) and V1 (57.8 ± 18 vs 44.8 ± 12.3, p < 0.01) were longer in patients with POAF. In multivariate regression analysis, PWPT in leads DII and V1 were independent predictors of POAF (OR: 1.11, 95%CI: 1.02–1.21, p = 0.01, OR: 1.06, 95%CI: 1.00–1.13, p = 0.03 respectively).
Conclusion
PWPT in leads DII and V1 can predict the development of POAF in patients undergoing cardiac surgery.
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Introduction
Atrial fibrillation (AF) is a common complication after cardiac surgery. The incidence of postoperative atrial fibrillation (POAF) varies between 25 and 50% depending on the differences in definitions, type of surgery, and mode of detection [1]. Unfortunately, improvements in surgical techniques or prophylactic treatments have not changed the frequency of POAF over decades [2] and POAF continues to be the cause of increased morbidity, mortality, and health care costs [3]. Furthermore, patients with POAF have increased risk for later atrial fibrillation development when compared with patients in sinus rhythm after surgery [4].
Atrial cardiomyopathy serves as a substrate for AF and includes structural and electrophysiological abnormalities of the atrium [5]. PR interval, P wave duration, P wave terminal force (PWTF), or other morphologic P wave parameters reflect underlying atrial remodeling and are associated with increased risk of AF in both surgical and non-surgical patients [6, 7]. A new ECG parameter, P wave peak time (PWPT), represents the prolonged intra-atrial and interatrial conduction time and recent data have shown a relationship with the development of AF [8].
Timely identification of patients at risk for developing AF preoperatively can facilitate implementing prophylactic treatments and consequently reduce the incidence of complications associated with AF. In this regard, our aim was to evaluate the predictive power of PWPT for the development of AF in patients undergoing cardiac surgery.
Methods
Study design
After approval by the local ethics committee, patients with no previous diagnosis of AF, undergoing urgent or elective CABG with or without heart valve replacement/repair between June 2019 and January 2020, were included in this study. The primary outcome was the development of POAF due to CABG surgery. Patients with metabolic disorders, patients with electrolyte disturbances, patients using antiarrhythmic medications, or patients with pacemakers were excluded from the study. Surgical closure of left atrial appendage or surgical ablation was considered exclusion criteria. Patients in whom preoperative sinus rhythm ECG were not accessible or not high enough quality to interpret were excluded from the study.
Procedures were performed by two experienced operators with median sternotomy and standard surgical techniques. Use of internal mammarian artery graft (LIMA), intra-aortic balloon pump (IABP), and proceeding with off-pump surgery were left to discretion of the primary operator performing the procedures. Combined surgery was defined as any additional procedure combined with coronary artery bypass graft surgery mainly valve replacement or repair. All patients were under 100 mg aspirin therapy at the day of surgery. Angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARB), β-blockers, and statin therapy were continued to the day of the surgery. Patients underwent two-dimensional and Doppler echocardiographic evaluation before surgery by an experienced cardiologist using Vivid-6 (General Electric Company, Milwaukee, WI).
All ECG recordings were obtained within 30 days before surgery and the most recent ECG was analyzed. AF was characterized with unidentifiable P waves and irregular RR intervals in the surface ECG. POAF was defined as the arrhythmia which persisted more than ≥ 10 min and was self-terminated or required electrical/medical cardioversion [7]. All patients were monitored continuously during their time in the intensive care unit, and then, ECGs were performed daily and additionally when they had reported symptoms. AF detected after hospital discharge did not undertaken consideration.
ECG analysis
Each patient’s records were taken using the standard 12 derivation surface ECG with a 10 mm/mV calibration and 25 mm/s sliding rate. All ECGs were downloaded in JPEG format from the hospital database and then uploaded to the EP Calipers software program. After magnifying the images adequately, all measurements were calculated by two cardiologists. Average of the values was used for comparison.
P wave parameters such as P wave maximum duration, P wave dispersion, PR interval, P wave terminal force, and recently defined PWPT were used in our study. The definitions of these parameters were as follows: (1) PR duration was defined as the time period between the onset of the P wave and the onset of the QRS complex, (2) P wave maximum duration was measured from the beginning to the end of the P wave in all 12 leads on the surface ECG and the longest one acquired, (3) P wave dispersion was defined as the time difference in milliseconds (msc) between the longest and the shortest P wave duration in any of the standard ECG leads, (4) PWPT was measured from the beginning of the P wave deflection to the peak of the P wave in leads DII and V1. PWPT was defined as the time period between the starting point of the positive deflection and the top of the negative deflection when P waves were biphasic in lead V1. Negative waves which were ≥ 0.1 Mv in lead V1 accepted as biphasic and measurements were performed only in these patients, (5) P wave terminal force (PWTF) was calculated by multiplying the depth and the duration of the terminal negative component of the P wave in lead V1 and abnormal PWTF was defined as PWTF ≥ 40 mm X msc. Examples of PWPT measurements are shown in Fig. 1. The QRS duration was defined as the interval from the beginning of the QRS complex to the J point, and the longest duration was recorded. QT interval was the interval beginning from the QRS complex to the end of the T wave on the surface ECG and corrected QT was calculated by Bazett formula. ST segment depression ≥ 1 mm in at least two contiguous leads was included regarding ST segment deviation.
Statistics
Patients were separated into two groups according to the presence of POAF. All data were presented as a mean ± standard deviation (SD) for variables with normal distribution or a median [inter-quantile range] for variables with non-normal distribution. Categorical variables were reported as numbers and percentages. Continuous variables were checked for the normal distribution assumption using the Kolmogorov–Smirnov statistics. Categorical variables were tested by Pearson’s χ2 test and Fisher’s exact test. Differences between POAF ( +) and POAF (-) groups were evaluated using the Mann–Whitney U test or the Student t-test, when appropriate. Univariable and multivariable binary logistic regression analyses were performed to investigate the independent correlates of POAF. As the result of the univariable regression analyses, variables which have p values < 0.10 were included in the multivariable regression analyses. Receiver operating curves were generated to define AUC and cutoff values of P wave indices for POAF. p values were two-sided and values < 0.05 were considered statistically significant. The ROC curves of the P wave indices were compared using MEDCALC software program (Softwarebvba 13, Ostend, Belgium). All statistical studies were carried out using Statistical Package for Social Sciences software (SPSS 22.0 for Windows, SPSS Inc., Chicago, IL).
Results
A total of 412 records were reviewed. In twenty-nine records, the rhythm was AF. Fifty patients did not have preoperative ECG and two patients underwent concomitant maze procedure. An additional 4 preoperative ECGs showed pace rhythm. After this exclusion, the study protocol was consisted of 327 subjects (Fig. 2).
Patients without previous AF diagnosis who underwent cardiac surgery entered the study (mean age = 61.5 ± 8.7, 64% men). POAF was seen in 67 patients (20.4%). Patients with POAF were older (68.1 ± 7.2 vs 59.8 ± 8.2, p < 0.01) and were less frequently on beta blocker therapy (25.4% vs 63.5%, p < 0.01). A total of 38 patients underwent combined surgery, where 20 of them had aortic valve surgery and the remaining patients had mitral valve surgery. POAF patients had higher frequency of combined surgery (22.4% vs 8.8%, p = 0.02) and larger LA diameters (40.6 ± 6.4 vs 36.2 ± 6.2, p < 0.01) compared with patients without POAF. Length of hospital stay after surgery was significantly longer (8 [2.0] vs 7 [2.0], p < 0.01) in patients who developed POAF. Baseline demographic, clinical, operative, and laboratory findings are provided in Tables 1 and 2.
ECG parameters other than P wave indices were similar between the groups as shown in Table 3. P wave peak time in leads D2 (65.1 ± 11.8 vs 57.2 ± 10 p < 0.01) and V1 (57.8 ± 18 vs 44.8 ± 12.3 p < 0.01) were longer in patients with POAF. POAF patients had longer PR duration (171 ± 29.7 vs 157.8 ± 29.3, p = 0.01) and P wave dispersion (51.4 ± 18.3 vs 45.3 ± 16.3, p < 0.01) when compared with patients without POAF. Abnormal PWTF in lead V1 was more frequent in POAF patients (44.7% vs 37.3%, p = 0.03).
In multivariate regression analysis, age (OR: 1.14, 95%CI: 1.01–1.29, p = 0.03), LA diameter (OR: 1.35, 95%CI: 1.10–1.67, p < 0.01), PWPTD2 (OR: 1.11, 95%CI: 1.02–1.21, p = 0.01), PWPTV1 (OR: 1.06, 95%CI: 1.00–1.13, p = 0.03), PWTFV1 > 40 mm x msc (OR: 1.06, 95%CI: 1.00–1.11) were found to be independent predictors of POAF (Table 4).
We had also checked tolerance and variance inflation factor (VIF) for all parameters included in the regression model in order to prevent multicollinearity. According to the multicollinearity statistic, the tolerance values were > 0.1 and VIF values were < 10 for all parameters. Therefore, we determined that there was no multicollinearity between each of the variables in the regression model.
In ROC analysis, PWPTD2 ≥ 60.5 msc predicted POAF development with a sensitivity of 75% and a specificity of 69% (AUC: 0.71, p < 0.01) and PWPTV1 ≥ 45.5 msc predicted POAF development with a sensitivity of 73% and a specificity of 56% (AUC: 0.70, p < 0.01). These data are demonstrated in Fig. 3.
Occurrence of AF was highest in the second postoperative day (52%) and 85% of incident AF occurred during the first 3 days. Seven patients required direct current cardioversion and 47 patients received amiodarone therapy to convert to sinus rhythm. The remaining events were self-terminated or controlled with rate-lowering drugs only.
Discussion
To our knowledge, the present study is the first to assess the role of the PWPT in predicting the POAF in patients undergoing coronary artery bypass grafting (CABG). The main new finding of the present study was that PWPTD2 and PWPTV1 were independent predictors of POAF. Age, LA diameter, and PWTFV1 > 40 mm X msc were additional independent predictors of POAF. In addition, PWPTD2 ≥ 60.5 msc had a sensitivity of 75% and specificity of 69% with an AUC of 0.71 and PWPTV1 ≥ 45.5 msc had a sensitivity of 73% and a specificity of 56% with an AUC of 0.70 for predicting POAF.
In the past, atrial fibrillation after cardiac surgery was believed to be a benign arrhythmia presumably as a consequence of its self-limiting feature with a median duration of 48 h; however, recent studies and meta-analyses have shown a clear association between POAF and increased short-term mortality and morbidity [3, 9, 10]. Ghurram et al. have shown that ventilator hours, length of ICU stay, and length of hospital stay were significantly increased in patients who developed POAF after off-pump CABG [11]. Furthermore, POAF was associated with an increased risk of long-term mortality and stroke [12,13,14,15,16,17]. After understanding the adverse outcomes of POAF, it has become more important to identify the patients most vulnerable to AF following cardiac surgery. For this purpose, the researchers have recently focused on predictive indicators of POAF which may be briefly classified into three main categories as follows: clinical variables, the ECG and echocardiographic parameters. The preoperative ECG is probably the most useful and easily performed diagnostic technique available for the prediction of POAF.
Dispersion of atrial refractoriness is essential for induction of atrial arrhythmias. Many previous clinical studies have suggested that atrial fibrillation was closely associated with an atrial structural substrate which might be a source for dispersion of atrial refractoriness [18, 19]. In patients with POAF, atrial ischemia is obviously a major contributor to the development of atrial substrate. Several perioperative factors such as volume overload, electrolyte disturbances, and hypoxemia have been associated with POAF in many previous studies [20, 21]. In addition, different surgical techniques have also been associated with the development of POAF [22,23,24]. On the other hand, multiple preoperative risk factors lead to left atrial structural changes and increase the likelihood of development of POAF. In a previous meta-analysis with a total number of 36,834 subjects, older age, increased LA diameter, lower EF, COPD, hypertension, MI, and diabetes were associated with increased POAF incidence [25].
The P wave on the ECG represents atrial depolarization and P wave abnormalities are associated with left atrial structural changes and conduction abnormalities. For this reason, preoperative ECG recordings, especially simple P wave changes indicative of LA abnormality, have been subjected to many previous studies to determine the predictors of POAF. P wave dispersion caused by inhomogeneous atrial conduction was identified as an independent predictor for the development of POAF [26]. P wave amplitudes in lead aVR and lead V1 have been described as powerful predictors of POAF in a previous study [27]. Furthermore, in another study, three preoperative ECG characteristics were associated independently with POAF: premature atrial contraction, p wave frontal axis greater than 55°, and p wave index > 27 msc [28]. Besides these, a new scoring system has been proposed by Hayıroğlu and colleagues for the prediction of in-hospital and long-term AF development after ischemic stroke “morphology-voltage-P wave duration (MVP)” which reflects the prolonged inter- and intra-atrial conduction time as PWPT [29]. As a difference from these previous studies, for the first time in the literature, abnormal PWTF in lead V1 and PWPT in leads D2 and V1 have been found to be independent predictors of POAF in our study.
Recent studies have shown that PWPT is clearly associated with paroxysmal AF in both acute ischemic stroke patients [30] and the unselected population [8]. Yıldırım et al. have also found PWTF, a marker of a subclinical structural cardiac disease leading to left atrial volume overload, as an independent predictor of paroxysmal AF in the same unselected population [8]. It has been reported that PWPT was associated with the severity of CAD in patients with non-ST segment elevation myocardial infarction [31]. Çağdaş et al. have found that preprocedural PWPTD2 was an independent predictor of no-reflow [32]. Burak et al. have also suggested that PWPT in the lead DII may be an independent predictor of increased LVEDP among hypertensive patients [33].
PWPT, an easily obtainable and novel ECG parameter, represents the time taken for excitation spreading from sinoatrial node to the maximal summation of positive deflection from both atria. Prolonged P wave duration, indicating atrial conduction delay, is a potent precursor of atrial fibrillation. Atrial conduction delay and slowing of depolarization may prolong P wave duration and P wave reaches its maximum amplitude (PWPT) significantly later as a consequence of prolongation of P wave duration. Atrial ischemia and left atrial overload may even more deteriorate atrial depolarization and facilitate the development of POAF. Based on this information, we hypothesized that increased preoperative PWPT would be associated with POAF and our results have confirmed this assumption.
Conclusion
In conclusion, POAF is significantly associated with both short- and long-term adverse outcomes in patients undergoing CABG. The identification of patients at risk for POAF would be helpful to guide prophylactic therapy. Therefore, many researchers have focused on the prediction of POAF by using easily obtained and low-cost tools. Our study demonstrated that PWPTD2 and PWPTV1 are feasible and clinically applicable ECG parameters to predict POAF in patients treated with CABG. Further research is needed with a larger sample size to evaluate the role of PWPT as an independent predictor of POAF after cardiac surgery.
Limitations
This current study has several limitations. ECG recordings were taken daily after discharge from ICU where all patients were monitored continuously. Also, we were not able to perform rhythm Holter monitoring for AF detection. Due to these, possible brief episodes of AF might have been overlooked which can change the exact number of POAF patients. Additionally, we excluded AF patients based on preoperative ECG and medical history; however, we were not able to analyze paroxysmal episodes of AF before hospital admission which may interfere with our results. We were not able to evaluate the impact of several operative features for the development of POAF because of missing data. Finally, our study has the limitations of a single-center retrospective study with a small sample size.
References
D’Agostino RS, Jacobs JP, Badhwar V et al (2018) The Society of Thoracic Surgeons adult cardiac surgery database: 2018 update on outcomes and quality. Ann Thorac Surg 105(1):15–23. https://doi.org/10.1016/j.athoracsur.2017.10.035
Greenberg JW, Lancaster TS (2017) Schuessler RB and Melby SJ Postoperative atrial fibrillation following cardiac surgery: a persistent complication. Eur J Cardiothorac Surg 52(4):665–672. https://doi.org/10.1093/ejcts/ezx039
LaPar DJ, Speir AM, Crosby IK et al (2014) Postoperative atrial fibrillation significantly increases mortality, hospital readmission, and hospital costs. Ann Thorac Surg 98(2):527–533. https://doi.org/10.1016/j.athoracsur.2014.03.039
Ahlsson A, Fengsrud E, Bodin L, Englund A (2010) Postoperative atrial fibrillation in patients undergoing aortocoronary bypass surgery carries an eightfold risk of future atrial fibrillation and a doubled cardiovascular mortality. Eur J Cardiothorac Surg 37:1353–1359
Goette A, Kalman JM, Aguinaga L et al (2017) EHRA/HRS/APHRS/SOLAECE expert consensus on atrial cardiomyopathies: definition, characterization, and clinical implication. Heart Rhythm 14:e3-40. https://doi.org/10.1016/j.hrthm.2016.05.028
German DM, Kabir MM, Dewland TA et al (2016) Atrial fibrillation predictors: importance of the electrocardiogram. Ann Noninvasive Electrocardiol 21(1):20–29. https://doi.org/10.1111/anec.12321
Wong JK, Lobato RL, Pinesett A, Maxwell BG (2014) Mora-Mangano CT, Perez MV P-wave characteristics on routine preoperative electrocardiogram improve prediction of new-onset postoperative atrial fibrillation in cardiac surgery. J Cardiothorac Vasc Anesth 28(6):1497–1504. https://doi.org/10.1053/j.jvca.2014.04.034. Epub 2014 Sep 26
Yıldırım E, Günay N, Bayam E et al (2019) Relationship between paroxysmal atrial fibrillation and a novel electrocardiographic parameter P wave peak time. J Electrocardiol 57:81–86. https://doi.org/10.1016/j.jelectrocard.2019.09.006
Villareal RP, Hariharan R, Liu BC et al (2004) Postoperative atrial fibrillation and mortality after coronary artery bypass surgery. J Am Coll Cardiol 43:742–748
Stamou SC, Dangas G, Hill PC et al (2000) Atrial fibrillation after beating heart surgery. Am J Cardiol 86:64–67
Ghurram A, Krishna N, Bhaskaran R et al (2020) Patients who develop post-operative atrial fibrillation have reduced survival after off-pump coronary artery bypass grafting. Indian J Thorac Cardiovasc Surg 36(1):6–13
Kosmidou I, Stone GW (2018) New-onset atrial fibrillation after PCI and CABG for left main disease: insights from the EXCEL trial and additional studies. Curr Opin Cardiol 33:660–664
Kaw R, Hernandez AV, Masood I et al (2011) Short- and long-term mortality associated with new-onset atrial fibrillation after coronary artery bypass grafting: a systematic review and meta-analysis. J Thorac Cardiovasc Surg 141:1305–1312
Phan K, Ha HS, Phan S et al (2015) New-onset atrial fibrillation following coronary bypass surgery predicts long-term mortality: a systematic review and meta-analysis. Eur J Cardiothorac Surg 48:817–824
El-Chami MF, Kilgo P, Thourani V et al (2010) New-onset atrial fibrillation predicts long-term mortality after coronary artery bypass graft. J Am Coll Cardiol 55:1370–1376
Gialdini G, Nearing K, Bhave PD et al (2014) Perioperative atrial fibrillation and the long-term risk of ischemic stroke. JAMA 312:616–622
Gudbjartsson T, Helgadottir S, Sigurdsson MI et al (2020) New-onset postoperative atrial fibrillation after heart surgery. Acta Anaesthesiol Scand 64(2):145–155
Mahnkopf C, Badger TJ, Burgon NS et al (2010) Evaluation of the left atrial substrate in patients with lone atrial fibrillation using delayed-enhanced MRI: implications for disease progression and response to catheter ablation. Heart Rhythm 7(10):1475–1481
Corradi D, Callegari S, Benussi S et al (2005) Myocyte changes and their left atrial distribution in patients with chronic atrial fibrillation related to mitral valve disease. Hum Pathol 36:1080–1089
Aglio LS, Stanford GG, Maddi R et al (1991) Hypomagnesemia is common following cardiac surgery. J Cardiothorac Vasc Anesth 5:201–208
Wahr JA, Parks R, Boisvert D et al (1999) Preoperative serum potassium levels and perioperative outcomes in cardiac surgery patients. Multicenter study of Perioperative Ischemia Research Group. JAMA 281:2203–2210
Wijeysundera DN, Beattie WS, Djaiani G et al (2005) Off-pump coronary artery surgery for reducing mortality and morbidity: meta-analysis of randomized and observational studies. J Am Coll Cardiol 46(5):872–882
Creswell LL, Schuessler RB, Rosenbloom M (1993) Cox JL Hazards of postoperative atrial arrhythmias. Ann Thorac Surg 56(3):539–549
Zaman AG, Archbold RA, Helft G et al (2000) Mills PG Atrial fibrillation after coronary artery bypass surgery: a model for preoperative risk stratification. Circulation 101(12):1403–1408
Yamashita K, Hu N, Ranjan R et al (2019) Clinical risk factors for post-operative atrial fibrillation among patients after cardiac surgery. Thorac Cardiovasc Surg 67(2):107–116
Jazi MH, Amirpour A, Zavvar R et al (2012) Predictive value of P-wave duration and dispersion in post coronary artery bypass surgery atrial fibrillation. ARYA Atheroscler. 8(2):59–62
Rader F, Costantini O, Jarrett C et al (2011) Quantitative electrocardiography for predicting postoperative atrial fibrillation after cardiac surgery. J Electrocardiol 44(6):761–767
Wong JK, Lobato RL, Pinesett A et al (2014) P-wave characteristics on routine preoperative electrocardiogram improve prediction of new-onset postoperative atrial fibrillation in cardiac surgery. J Cardiothorac Vasc Anesth 28(6):1497–1504
Hayıroğlu MI, Cinar T, Selçuk M et al (2021) The significance of the morphology-voltage-P-wave duration (MVP) ECG score for prediction of in-hospital and long-term atrial fibrillation in ischemic stroke. J Electrocardiol 69:44–50. https://doi.org/10.1016/j.jelectrocard.2021.09.006
Öz A, Cinar T, Güler CK et al (2020) Novel electrocardiography parameter for paroxysmal atrial fibrillation in acute ischemic stroke patients: P wave peak time. Postgrad Med J 96(1140):584–588
Burak C, Yesin M, Tanık VO et al (2019) Prolonged P wave peak time is associated with the severity of coronary artery disease in patients with non-ST segment elevation myocardial infarction. J Electrocardiol Jul-Aug 55:138–143
Çağdaş M, Karakoyun S, Rencüzoğulları İ et al (2017) P wave peak time; a novel electrocardiographic parameter in the assessment of coronary no-reflow. J Electrocardiol 50(5):584–590
Burak C, Çağdaş M, Rencüzoğulları I et al (2019) Association of P wave peak time with left ventricular end-diastolic pressure in patients with hypertension. J Clin Hypertens (Greenwich) 21(5):608–615
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Zengin, A., Karataş, M.B., Çanga, Y. et al. A novel electrocardiographic parameter for the prediction of atrial fibrillation after coronary artery bypass graft surgery “P wave peak time”. Ir J Med Sci 191, 2579–2585 (2022). https://doi.org/10.1007/s11845-021-02894-8
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DOI: https://doi.org/10.1007/s11845-021-02894-8