Value of the signal-averaged P wave analysis in predicting atrial fibrillation after cardiac surgery

Journal of Electrocardiology Vol. 30 Supplement

Value of the Signal-Averaged P Wave Analysis in Predicting Atrial Fibrillation After Cardiac Surgery

Jacqueline E. Tamis, MD, and Jonathan S. Steinberg, MD

Abstract: Atrial fibrillation (AF) is the most common sustained arrhythmia occurring after cardiac surgery. Beside important implications regarding patient recovery, AF has been shown to substantially lengthen hospital stay-our recent study found a 3-day prolongation after adjusting for all other significant factors. Identification of those at highest risk of AF by clinical or noninvasive characteristics may be a useful strategy for targeted prophylactic therapy. Our data have shown that prolonged atrial conduction as assessed by analysis of the P wave duration from the signal-averaged electrocardiogram (SAECG) imparts a four fold increase in risk for postoperative AE independently of other measured variables. In addition, abnormal conduction was present on the preoperative P wave ECG (P-SAECG), implying a preexisting substrate that is triggered by surgery. The use of combination abnormal noninvasive variables (eg, abnormal P-SAECG and low left ventricular ejection fraction) can identify groups with a 50% risk of AE which is nine times as high as w h e n both tests are normal. Thus, the P-SAECG is a useful and accurate predictor of AF after cardiac surgery. K e y words: atrial fibrillation, P wave signal-averaged ECG, cardiac surgery.

risk for developing postoperative AF can be identified. Many clinical analyses have been performed in an attempt to determine which baseline, intraoperative, and postoperative variables predict AF after cardiac surgery. Unfortunately, variability in results and poor predictive accuracy have limited these efforts. Older age is the variable that has most consistently been shown to predict postoperative AF (2,4,5,16,27), however, the lack of specificity has limited its usefulness. Recently, abnormal atrial conduction, defined by a prolonged P wave duration on the P wave signal-averaged electrocardiogram (P-SAECG), has been shown to accurately predict AF after cardiac surgery (1,28-31) with more acceptable sensitivity and specificity. This article reviews the current literature focused on the usefulness of the P-SAECG in predicting AF after cardiac surgery and attempts to explain possible underlying mechanisms for the success of this predictive tool.

Atrial fibrillation (AF) is the most common sustained arrhythmia seen after cardiac surgery, occurring in approximately 20% to 40% of patients (1-5). The occurrence of AF after cardiac surgery can result in increased morbidity and prolonged postoperative hospital stay (2-7). Extensive research has focused on the managemerit of the postoperative patient in an effort to limit the occurrence of AF after cardiac surgery (7-26). Aggressive attempts at universal prophylaxis, however, may not be warranted if a subgroup of patients who are at higher

From the Arrhythmia Service, Division of Cardiology, St. Luke'sRoosevelt Hospital Center and Columbia University College of Physicians and Surgeons, New York, New Fork.

Reprint requests: Jonathan S. Steinberg, MD, Chief, Division of Cardiology, St. Luke's-Roosevelt HospitaI Center, 1111 Amsterdam Avenue New York, NY 10025 ©1998 Churchill Livingstone ® 0022-0736/300S-001455.00/0

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Signal-Averaged P Wave Predicts Atrial Fibrillation

Background The SAECG was first introduced nearly two decades ago. The advantage of the SAECG over the standard electrocardiogram (ECG) is its ability to record low-level electrical signals through the use of special acquisition, amplification, and signal processing devices. The ability of the SAECG to detect low-amplitude signals enables one to identify patients with delayed myocardial conduction, a prerequisite for reentrant ventricular arrhythmias. Its clinical use has evolved over the years, and the SAFCG has proved to be an important tool for identifying patients at risk for arrhythmic events (32-36) and for assessing patients with unexplained syncope (37,38) or nonsustained ventricular tachycardia (39-41). Although the mechanisms of AF are not entirely understood, m a n y studies have supported the hypothesis that AF results from multiple reentrant circuits, which necessitate areas of delayed conduction to initiate and maintain the rhythm (42-44) similar to the delayed conduction required for ventricular reentrant arrhythmias. In 1988, Engel et al. (45) attempted to identify patients at risk for atrial arrhythmias by averaging filtered P waves. However, their work failed to identify a group of patients with higher events. This was believed to be a result of the method in which they recorded successive P waves used for signal-averaging: they used the QRS complex as a trigger, which resulted in variability in PR intervals and failure to exclude any ectopic atrial beats. Later work incorporating P wave-triggered signal-averaging systems (46) or variations in conventional QRS complex triggered signal-averaging software (47,48) has permitted identification of patients with underlying atrial conduction abnormalities who are at risk for developing AE

Methods The acquisition and analysis of the P-SAECG has previously been described in detail (49) and will be briefly reviewed here. The P-SAECG should be obtained from a motionless patient in the supine position in a quiet room, free from any electrical interference. The PSAECG incorporates three bipolar orthogonal leads referred to as the X, Y, and Z leads, an a r r a n g e m e n t identical to that used for the acquisition of the standard SAECG. The X electrodes are placed in the left and right midaxillary line in the fourth intercostal space; the Y electrodes are placed in the left m i d d a v i c u l a r Iine at the level of the a b d o m e n (usually near the lilac crest) and just below the clavicle (or in the suprasternaI notch); the positive Z electrode is placed in the midclavicular line (or just to the left of the sternum) in the fourth intercostal space; and the negative Z electrode is placed on the back at the reflection of the Z+ electrode. The vector direction for this system is leftward, inferior, and anterior.

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Each of the X, Y, and Z signals is directed to Iow-noise biophysical amplifiers and then through a bandpass filter. Our P-SAECG software recognizes signals in the 0.05-300 Hz frequency range. Signals are then passed through an A/D converter, with a precision of 12 or 16 bits, and the incoming waveforms are digitized at a sampling frequency of 1,000-2,000 Hz. As the P-SAECG is being acquired, the computer continuously analyzes each incoming signal. In commercially available systems, the QRS complex is used as the trigger for the averaging process. In order to expose the P wave and the PR interval, the fiducial point must be shifted to the extreme right of the 300-ms window. While systems cannot be altered with respect to triggering, they can be programmed to modify the window, thereby allowing for appropriate P wave analysis. The sinus P wave is used as a template and manually selected by the operator. In our laboratory, P waves are chosen only if they match the template with a 99% correlation coefficient. The P wave complexes are continuously collected until a noise level below 0.3 gV within the TP segment is achieved. Once these high-quality low-noise signals are obtained, they are directed through a high-pass filter; our system incorporates a least-squares filter with a w i n d o w width of 100 ms, resulting in a cutoff frequency of 29 Hz. The filtered signals are then amplified, and the resultant X, Y, and Z signals are combined into a vector magnitude by the formula (X2 + y2 + Z2)i/2. The P wave onset and offset are manually determined and indicated with a cursor. Some systems incorporate a quantitative design that determine onset and offset of the averaged waveform once a relative voltage has been reached (29). In any case, the filtered P wave duration is defined as the time difference between the onset and offset of the waveform. Based on results from earlier work, we define an abnormal P-SAECG as a filtered P wave duration of over 140 ms (28). Figure 1 is an example of a vector magnitude of the filtered P wave. Although the P-SAECG is generally defined by duration of the waveform, some studies have incorporated the root-meansquare (rms) voltage of the terminal 10, 20, 30, and 40 ms of the P-SAECG (25,46,48,50). Results have been variable, and this method is not universally applied. Unfortunately, the methods of acquisition and analysis, as well as the interpretation of the P-SAECG, are not standardized. Variations in software, filters, and filtering frequency (or window width) may have an effect on clinical data correlations, offering different results in similar patient populations. If the results of clinical studies dictate future practice, then standardization of acquisition and analysis is of great importance. Therefore, we assessed the ability of various filters and different filter frequencies to identify patients at risk for paroxysmal AF (50). Fifteen patients with a history of AF were compared with fifteen age and disease-matched control subjects. The optimal AF prediction was obtained using a leastsquares fit filter (odds ratio 26, P = .005) and a bandwidth filter frequency of 29-250 Hz (odds ratio 26, P = .005).

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Pathophysiology of Postoperative Atrial Fibrillation According to Moe's multiple wavelet hypothesis (43), AF is considered to be a result of multiple reentrant circuits, which give rise to wavelets of electrical activity throughout the atria. Inhomogeneous refractoriness, shortened refractory periods, and slow conduction can all contribute to the development of this reentrant arrhythmia. This theory, which was proposed over 20 years ago, has been strongly supported by experimental studies performed by Allessie et al. (44). Canine electrophysiologic studies have further illustrated that variability in atrial refractory period and conduction are associated with a higher incidence of AF after cardiac surgery (51). The ability to correlate the P-SAECG with the development of postoperative AF demonstrates that an underlying atrial conduction abnormality is likely present in patients who develop this arrhythmia after cardiac surgery. Although AF occurring after cardiac surgery may be associated with intrinsic atrial abnormalities similar to those seen in patients with idiopathic or chronic AE multiple factors probably contribute to the pathogenesis of this arrhythmia. Since the majority of patients develop AF within 72 hours of surgery, it is likely that factors related to the surgery act as triggers in vulnerable individuals. Increased adrenergic tone in the postoperative period, which is exacerbated by a heightened sensitivity to catecholamines due to beta-blocker withdrawal,

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has been proposed as a potential mechanism for the development of postoperative AF (9,52,53). The occurrence of atrial infarction/ischemia during surgery as a result of inhomogeneous cardioplegia (%54-56) has also been postulated as a an underlying mechanism. Atriotomy, postoperative pericarditis (3), and atrial enlargement (53) possibly resulting from hemodynamic changes in the postoperative period, may also contribute to the development of AF after cardiac surgery.

Use of the P Wave Signal-Averaged ECG for Predicting Atrial Fibrillation After Cardiac Surgery Since the majority of patients who develop postoperative AF probably have an underlying substrate, certain electrophysiologic measurements may distinguish this group. As the presence of delayed atrial conduction may facilitate the reentrant mechanism, detection of this delayed conduction may help identify vulnerable patients. Buxton and Josephson (30} were the first to demonstrate that delayed atrial conduction was associated with AF after cardiac surgery, as assessed by the P wave duration on the I2-]ead ECG. They examined 99 patients undergoing coronary artery bypass surgery of w h o m 51 were followed prospectively and 48 were retrospectively identified. Delayed atrial conduction was assessed by the standard 12-lead ECG using the following measurements: (I) the longest P wave duration measured on the standard limb lead; (2) the total average P wave duration, defined as the difference between the earliest P

Signal-Averaged P Wave Predicts Atrial Fibrillation wave onset and the latest P wave offset, obtained from three simultaneously recorded limb leads; and (3) the isoelectric interval, defined as the difference between the longest P wave duration and the total P wave duration. Of the 99 patients, 29 developed postoperative AF and/or atrial flutter. The total P wave duration and the isoelectric interval were both significantly more prolonged in patients who developed postoperative AF and/or atrial flutter than patients who did not (P < .001 for each analysis), although substantial overlap of these measurements limited their clinical application. The combination of an isoelectric interval over l0 ms and a total P wave duration over 110 ms resulted in a sensitivity of 66% and a specificity of 70% for predicting postoperative AF. Despite these provocative findings, the results reported by Buxton and Josephson have never been duplicated, and future research continued to emphasize the value of clinical variables for predicting AF after cardiac surgery. The introduction of the P-SAECG, however, facilitated even greater accuracy of measurement of atrial conduction and reexploration of the ability to predict atrial arrhythmias after cardiac surgery. Our group prospectively examined 130 consecutive patients referred for nonemergent cardiac surgery in order to determine whether the P-SAECG was a useful tool for identifying vulnerable individuals (28). Patients with a prior history of AF and patients taking class I or III antiarrhythmic agents were excluded from the analysis. Only those patients who demonstrated sinus rhythm on the preoperative ECG were included. All patients had P-SAECGs recorded prior to cardiac surgery according to the methods previously described. The patients were followed after cardiac surgery for the development of AE defined as any episode lasting longer than 30 minutes. Of the 130 patients, 33 (25%) developed AF on an average of 2.3 + 2.4 days after surgery. Univariate prediaors for the development of AF induded the presence of left ventricular hypertrophy on the ECG (P < .05), the value of the lower left ventricular ejection fraction (P < .01), and the P-SAECG. The P-SAECG (filtered P wave) duration w a s 152 +_ 18 ms for patients who developed AE compared with 139 +_ 17 Ins in the group of patients who remained in sinus rhythm (P < .001). A P-SAECG duration of over 140 ms predicted AF after cardiac surgery with a sensitivity of 77%, a specificity of 55%, a positive predictive accuracy of 37%, and a negative predictive accuracy of 87% (Fig. 2). Moreover, logistic regression analysis demonstrated that a PSAECG duration of over 140 ms was the only variable postoperative AF. Patients with an abnormal P wave duration on SAECG had a 3.9-fold increased likelihood of developing postoperative AF (P < .001 ). Similar results were later seen in a smaller study performed by Klein et al., who reported on 54 consecutive patients undergoing isolated coronary artery bypass grafting. Patients with a prior history of AF or who were undergoing valvular surgery were excluded from the analysis. All patients had a P wave-triggered P-SAECG prior to surgery. They were followed after cardiac surgery for the development of AE defined as an episode lasting for over 1 hour. Sixteen patients (36%) devel-

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oped postoperative AF. Patients who developed atrial flutter, supraventricular tachycardia, or ventricular fibrillation were excluded from the analysis. Atrial fibrillation generally occurred between day 2 and day 4 after surgery. The percentage of patients with left atrial enlargement on the 12-lead ECG was significantly higher in patients who developed AF (P < .04). Otherwise, there were no significant differences in baseline or intraoperative variables between the two groups. The m e a n P-SAECG duration was 144 4-_16 ms in the non-AF group and 163 _+ 19 ms in the AF group (P < .001). A PSAECG duration of 155 ms or longer predicted postoperative AF with a sensitivity of 69%, a specificity of 79%, a positive predictive value of 65%, and a negative predictive value of 82% (P < .005). Since postoperative AF likely necessitates both an intrinsic abnormality and an external stimulus, the combination of clinical and electrophysiologic variables may yield stronger results. In another study (1), our group sought to define a subset of patients at higher risk for developing this arrhythmia by incorporating both the PSAECG and baseline, intraoperative, and postoperative variables. A total of 272 patients were enrolled in this prospective analysis which used the same design as our earlier study (28). Older age (P < .01), lower left ventricular ejection fraction (P < .01) prolonged P wave duration on the P-SAECG (P < 0.01), valvular surgery (P < .01), and preoperative use of digoxin (P < .01) were all associated with a higher incidence of postoperative AF. Multivariate analysis demonstrated that only a P-SAECG duration longer than 140 ms (odds ratio 3.1, 95% confidence interval 1.37-6.82, P < .01) and a left ventricular ejection fraction of less than 40% (odds ratio 2.8, 95% confidence interval 1.32-5.82, P < .01) predicted postoperative AF. The presence of both variables imparted a 50% chance for developing this arrhythmia, and a ninefold greater likelihood for developing AF than those

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Journal of Electrocardiology Vol. 30 Supplement 10 9 8 7 6 5 4 3

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patients with normal results seen on both tests (Fig. 3). This study has provided us with a useful clinical algorithm which can be used for risk stratification of patients and targeting of prophylactic therapy.

Does the P Wave Signal-Averaged ECG Contribute Information Independently of Other Clinical Data? The P-Wave Signal-Averaged Versus the Standard 12-Lead ECG Although the P-SAECG appears to be a valuable n o n i n vasive tool, some researchers have argued that there is no advantage to the P-SAECG over the standard-12 iead ECG for predicting postoperative AF (57,58). Since the availability of this machine is not widespread and additional resources are required to operate and interpret the results, the unique contribution of the P-SAECG needs to be ascertained. Frost et al. (27) compared the predictive accuracy of the P-SAECG with that of the standard 12-1ead ECG, using the parameters described by Buxton and Josephson (30), for 189 consecutive patients referred for elective CABG. Signal averaging was performed with use of QRS complex-triggered ECG software with a P wave template. The total filtered P wave duration and the rms of the terminal 10, 20, and 30 ms were recorded. Patients were monitored for the occurrence of "clinically significant" AF within 5 days of surgery. Forty-two patients (22%) developed AF and/or atrial flutter. Older patients (P < .001), heavier patients (P =

.05), and patients with hypertension (P = .04) were more likely to develop AF after cardiac surgery. Patients who developed AF and/or atrial flutter had a longer total P wave duration on the standard ECG than patients who remained in sinus rhythm (129 _+ 12 ms vs 124 _+ 12 ms, P = .01). Interestingly, the duration of the signal-averaged P wave did not differ significantly among the two groups, nor did the rms voltage. After controlling for other potentially confounding variables, only age (odds ratio 4.46; 95% confidence interval 1.05-1.13) and body weight (odds ratio, 3.8i: 95% confidence interval 1.71-8.46) significantly predicted the development of AF and/or atrial flutter after coronary artery bypass grafting. In this study neither the P-SAECG nor the P wave duration on the standard 12-lead ECG predicted AF and/or atrial flutter after surgery. These findings clearly conflict with data seen in prior investigations (1,28-30) and likely reflect differences in study design: the endpoint for AF defined in this study as an episode of "clinically significant AF occurring within 5 days of surgery" was ambiguous, and the time during which patients were monitored for arrhythmias was substantially shorter than the standard time for a cardiac surgery patient. (Telemetry was continued only for 16-24 hours after surgery.) Since postoperative AF is often self-limiting and patients are frequently asymptomatic, this study design may have resulted in exclusion of a substantial n u m b e r of patients with postoperative AF. In a subsequent study by Stafford et aI. (31), I37 patients referred for nonemergent coronary artery bypass grafting were examined. Clinical variables, P-SAECG, and total P wave duration and isoelectric interval on a standard ECG were recorded. Neither total P wave duration nor isoelectric interval on the ECG was associated with postoperative AE Moreoever, stepwise logistic regression analysis demonstrated that the P-SAECG was the only predictor of postoperative AE with a positive predictive accuracy of 41% and a negative predictive accuracy of 87%. The predictive accuracy of the PSAECG reported in this study is consistent with data previously described and clearly demonstrates teat the P-SAECG is superior to criteria obtained from the 12lead ECG for identifying patients at higher risk of developing postoperative AF.

The P Wave Signal-Averaged ECG Versus Atrial Dimensions Experimental studies looking at the electrophysiologic effects of surgically induced atrial enlargement in dogs have implied that abnormalities in atrial conduction that predispose patients to post-operative AF result from atrial enlargement (59}. Several clinical trials have supported these findings by demonstrating that left atrial enlargement predicts the occurrence of AF after cardiac surgery (29,60). If a prolonged P-SAECG reflects delayed atrial conduction resulting from atrial enlargement, then the P-SAECG should correlate with such dimensions. We therefore, examined whether the P-SAECG correlated

Signal-Averaged P Wave Predicts Atrial Fibrillation with atrial dimensions measured on echocardiogram (61). We reviewed M-mode and two-dimensional echocardiographic parameters performed prior to cardiac surgery in 12 patients with an abnormal P-SAECG and 11 patients with a normal P-SAECG. There were no significant differences between the two groups in left and right atrial dimensions and left atrial area. Moreover, linear regression analysis failed to demonstrate any correlation between atrial size and P-SAECG duration. These results imply that abnormalities in the P-SAECG are not due to atrial enlargement. Similar results were later reported in a large prospective study by Stafford et al. (31)

The P Wave Signal-Averaged ECG Versus Age Prior work has demonstrated that the duration of the P wave measured manually from the surface ECG correIates with intra-atrial conduction time (62). In a similar mechanism, the P-SAECG likely reflects delayed atrial conduction. Since increases in atrial conduction are believed to occur with age, the association of postoperative AF with increasing age may be a result of these changes. Interestingly, in our earlier work we found that age was not an independent predictor of postoperative AF once atrial conduction, as assessed by the P-SAECG, was included in the analysis (1). In another study that looked at the relationship between clinical variables and P-SAECG duration (58), investigators demonstrated a weak correlation between age and P-SAECG (r = .20, P < .05). However, this patient sample was limited to older patients referred for coronary artery-bypass grafting, and a continuous correlation spanning all age groups was not made.

Using the P Wave Signal-Averaged ECG to Identify High-Risk Patients for Aggressive Preventive Therapy Identification of patients at risk for developing AF aJter cardiac surgery can be advantageous if subsequent attempts are undertaken to modify these risks in an effort to decrease morbidity and decrease postoperative length of hospital stay. Although the incidence of postoperative AF is relatively high, it occurs in a minority of patients. Prophylactic therapy administered for the prevention of AF may be risky or expensive or may require increased use of hospital resources; hence efforts at universal prophylaxis may not be cost effective. The PSAECG allows identification of a subset of patients who may have a predisposition for developing postoperative AF so that preventive efforts can be focused, Beta-blockers are the most effective therapy for preventing AF after cardiac surgery. Earlier studies have demonstrated that beta-blockers decreased the incidence of postoperative AF by at least 50% (7-9,12,14). Other studies that have looked at the use of digitoxin (10,11,17,18,24-26),

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antiodarone (19), and calcium channel blocking agents (20,21) have had varied results. Unfortunately, many patients develop AF after cardiac surgery despite appropriate treatment with beta-adrenergic blocking agents, and alternative therapeutic options are currently being explored. The use of the P-SAECG to guide prophylactic therapy in this population of patients remains unproven. We are currently using the P-SAECG for this purpose: patients referred for coronary artery bypass grafting who have an abnormal P-SAECG are randomized to receive early intravenous beta-blocking agents or standard oral beta-blocker therapy after surgery.

Conclusions Atrial fibrillation is common after cardiac surgery and likely results from an underlying abnormality in intraatrial conduction, which is triggered by external factors related to the surgery. The P-SAECG is the strongest predictor of postoperative AF and presumably reflects intrinsic changes in atrial conduction, which are independent of atrial size. Future work will determine whether targeting vulnerable patients for prophylactic therapy through the routine use of the P-SAECG effectively decreases the occurrence of this intractable postoperative arrhythmia.

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Signal-Averaged P Wave Predicts Atrial Fibrillation

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