Steven Swiryn

Practice Standards for Electrocardiographic Monitoring in Hospital Settings: An American Heart Association Scientific Statement From the Councils on Cardiovascular Nursing, Clinical Cardiology, and Cardiovascular Disease in the Young: Endorsed by the International Society of Computerized Electrocardiology and the American Association of Critical-Care Nurses

The goals of electrocardiographic (ECG) monitoring in hospital settings have expanded from simple heart rate and basic rhythm determination to the diagnosis of complex arrhythmias, myocardial ischemia, and prolonged QT interval. Whereas computerized arrhythmia analysis is automatic in cardiac monitoring systems, computerized ST-segment ischemia analysis is available only in newer-generation monitors, and computerized QT-interval monitoring is currently unavailable. Even in hospitals with ST-monitoring capability, ischemia monitoring is vastly underutilized by healthcare professionals. Moreover, because no computerized analysis is available for QT monitoring, healthcare professionals must determine when it is appropriate to manually measure QT intervals (eg, when a patient is started on a potentially proarrhythmic drug). The purpose of the present review is to provide ‘best practices’ for hospital ECG monitoring. Randomized clinical trials in this area are almost nonexistent; therefore, expert opinions are based upon clinical experience and related research in the field of electrocardiography. This consensus document encompasses all areas of hospital cardiac monitoring in both children and adults. The emphasis is on information clinicians need to know to monitor patients safely and effectively. Recommendations are made with regard to indications, timeframes, and strategies to improve the diagnostic accuracy of cardiac arrhythmia, ischemia, and QT-interval monitoring. Currently available ECG lead systems are described, and recommendations related to staffing, training, and methods to improve quality are provided.

The coherence spectrum. A quantitative discriminator of fibrillatory and nonfibrillatory cardiac rhythms.

Previous work has suggested that a comparison of electrograms from two or more sites may best differentiate fibrillatory from nonfibrillatory rhythms. The coherence spectrum is a measure by which two signals may be compared quantitatively in the frequency domain. In the present study, the coherence spectrum was used to quantify the relation between spectral components of electrograms from two sites in either the atrium or ventricle during both fibrillatory and nonfibrillatory rhythms. Bipolar recordings of 35 rhythms from 20 patients were analyzed for coherence in the 1-59 Hz band. The 17 nonfibrillatory rhythms were sinus rhythm (six), paroxysmal supraventricular tachycardia (two), atrial flutter (four), and monomorphic ventricular tachycardia (five). The 18 fibrillatory rhythms were atrial fibrillation (12) and ventricular fibrillation (six). Nonfibrillatory rhythms exhibited moderate-to-high levels of coherence throughout the 1-59 Hz band, with peaks concentrated at the rhythms fundamental frequency and its harmonics. Fibrillatory rhythms exhibited little coherence throughout the 1-59 Hz band, and harmonics were not evident. The mean magnitude-squared coherence (scale of 0 to 1) for the 1-59 Hz band ranged from 0.22 to 0.86 (mean +/- SD, 0.52 +/- 0.19) for nonfibrillatory rhythms and from 0.042 to 0.12 (0.067 +/- 0.021) for fibrillatory rhythms. Separation of fibrillatory and nonfibrillatory rhythms was possible whether signals were recorded by floating or fixed-electrode configurations. These findings indicate that comparison of two electrograms with magnitude-squared coherence measurements differentiates fibrillatory from nonfibrillatory rhythms. A recognition algorithm based on coherence spectra may provide a major variations in lead configuration.(ABSTRACT TRUNCATED AT 250 WORDS)

Torsade de pointes due to quinidine: Observations in 31 patients

We performed a mail solicitation and obtained the records of 31 patients with documented torsade de pointes (TDP) due to quinidine. All 31 patients had heart disease: ischemic = 11 patients (36%), rheumatic = five patients (16%), hypertensive = four patients (13%), cardiomyopathic = four patients (13%), other = seven patients (22%). Quinidine was administered to these patients for the following reasons: atrial fibrillation or flutter = 22 patients (71%), ventricular premature beats = six patients (19%), ventricular or supraventricular tachycardia = three patients (10%). The 31 patients were receiving quinidine, 650 to 2400 (mean 1097) mg/day, and 14 patients had serum quinidine levels of 1.4 to 10.6 (mean 3.7) micrograms/ml. TDP occurred within 1 week of initiation of quinidine therapy in 23 (74%) of the patients. Twenty-eight (90%) of the 31 patients were receiving digoxin, and 5 (24%) of 21 patients had hypokalemia at the time of TDP. Off of quinidine therapy, corrected QT (QTc) intervals in 24 patients ranged from 390 to 580 (mean 470) msec and were prolonged in 17 patients (71%). On quinidine therapy, QTc intervals in 23 patients ranged from 390 to 630 (mean 510) msec and were prolonged in 21 patients (91%). In summary, patients with TDP due to quinidine usually had heart disease complicated by atrial fibrillation, were receiving digoxin, and were receiving moderate dosages of quinidine for less than 1 week prior to TDP. Approximately two thirds of patients with TDP due to quinidine had long QT intervals while off of quinidine.

Diagnosis of atrial fibrillation from surface electrocardiograms based on computer-detected atrial activity☆

A computerized method to detect atrial fibrillatory activity on the surface electrocardiogram is presented. After ventricular activity was canceled by creating a remainder electrocardiogram, significant differences were found in the percent power of the remainder electrocardiograms for a group of rhythms with atrial fibrillation (mean +/- SD; lead V1, 47.4 +/- 29.7%; lead II, 39.4 +/- 26.8%) and a control group (irregular rhythms or rhythms without readily detectable P waves; lead V1, 17.6 +/- 14.6%; lead II, 19.2 +/- 13.9%) for both leads (p less than 0.0001). A discrimination algorithm that classified a rhythm as atrial fibrillation if the percent power was greater than 32% and if noncoupled P waves were not present had a specificity of 90.0% and a sensitivity of 69.7% for the training set and a specificity of 87.8% and a sensitivity of 68.3% for the test set. In addition, the algorithm correctly detected all 66 of the 66 sinus rhythms tested. The algorithm produced good results that may be incorporated into arrhythmia interpretation systems to improve their specificity.

Evidence for transient linking of atrial excitation during atrial fibrillation in humans.

BackgroundAtrial fibrillation is usually thought of as a “random” pattern of circulating wavelets. However, local atrial activation should be influenced by the constant anatomy and receding tail of refractoriness from the previous activation. The general tendency for wave fronts to follow paths of previous excitation has been termed “linking.” We examined intra-atrial electrograms recorded during atrial fibrillation for evidence of linking. Methods and ResultsTwo minutes of atrial fibrillation were recorded in 15 patients with an orthogonal catheter. We have previously demonstrated that this catheter can be used to detect changes in the direction of local atrial activation. A mean vector was calculated for each electrogram. The similarity of the direction of the vectors from two consecutive electrograms can be quantified on a scale of 1 to −1 by calculating the cosine (cos) of the smallest angle (&thetas;) between them. Two vectors pointing in the same or opposite directions then have cos(&thetas;) = 1 or −1, respectively. For the entire group of patients, mean cos(&thetas;) was significantly greater than 0 (mean, 0.36; p < 0.001). In nine of 15 patients, there were groups of six or more consecutive beats (total, 44 groups; range, six to 14 beats per group) in which the direction of activation of each beat was within 30° of the previous beat. The likelihood of one group of six or 14 consecutive similar beats occurring by chance in any one patient in 1 minute is < 0.05 and < 0.0000001, respectively. There was a significant correlation (r = 0.90) between the amount of linking during the first and second minutes of atrial fibrillation in each patient. ConclusionsTransient similarities in the direction of wavelet propagation in the majority of patients with atrial fibrillation is consistent with the presence of transient linking. To our knowledge, this is the first direct evidence that atrial activation during atrial fibrillation in humans is not entirely random.

Significance of the HV interval in 517 patients with chronic bifascicular block.

In January 1975, we reported results of a prospective follow-up study (mean 538 +/- 42 days) of 119 patients with chronic bifascicular block (BFB), and concluded that BFB patients with normal and prolonged HV (NHV and PHV) had a similar incidence of atrioventricular (AV) block and mortality. In this report, we update these findings in 517 patients with a follow-up of 21 days to 9.8 years (mean 3.4 +/- 0.2 years). Three hundred nineteen patients (61%) had NHV and 198 (39%) had PHV (greater than 55 msec). The NHV and PHV groups were similar in regard to age (NHV vs PHV, 61 +/- 1 vs 62 +/- 1 years) and sex (80% male, 20% female vs 82% male and 18% female). The following were more common (p less than 0.05) in patients with PHV (percent of patients with finding in NHV vs PHV groups): angina (18% vs 27%), congestive failure (27% vs 42%), cardiomegaly (48% vs 66%), New York Heart Association functional class II-IV (34% vs 56%), premature ventricular complexes (20% vs 29%), and organic heart disease (OHD) (75% vs...

Significance of block distal to the His bundle induced by atrial pacing in patients with chronic bifascicular block.

SUMMARYTwenty-one of 496 (4%) patients with chronic bifascicular block, studied and followed prospectively, had block distal to the His bundle (BDH) induced by atrial pacing during initial electrophysiologic studies. In six, BDH was noted during pacing-induced atrioventricular (AV) nodal Wenckebach periods (at paced rates of 150–190 beats/min), with BDH in the short HH cycles after the AV nodal blocked P (long cycle). The AH interval was normal in all six patients and HV was normal in four. None of the six patients has developed AV block during a mean follow-up of 5.33 ± 0.48 years.In 15 patients, pacing-induced BDH was noted during intact AV nodal conduction (paced rate of 80–200 beats/min). The AH interval was prolonged in one, and HV was prolonged in 10 of the 15 patients. During a mean follow-up of 3.4 ± 0.59 years, seven of these patients developed AV block, one had treadmill-provoked AV block, and two died suddenly (major morbid event in 10 of 15 patients).In conclusion, BDH induced by atrial pacing is an infrequent finding in patients with bifascicular block, and can be a functional as well as a pathologic response. The latter is associated with a high risk of major morbid events (AV block and sudden death).

Atrial fibrillation and waveform characterization

The surface electrocardiogram (ECG) is a convenient, cost effective, and noninvasive tool for the study of atrial fibrillation (AF). It can be used to examine the hypothesized mechanisms of AF as well as to quantify and assess the effect of electrophysiological remodeling and the effectiveness of treatment on different types of AF. Time domain methods can be used to characterize the signal in the surface ECG. The authors described observations that can be obtained directly from the signal, such as the general characteristics of AF in the surface ECG and the ventricular response to AF. A discussion on commonly used methods to characterize atrial activity is also presented. These methods include cancellation techniques, vector analysis, and autocorrelation. Observations show that combining time and frequency domain methods provides a more thorough understanding of the characteristics of the atrial activity in the surface ECG. Whether the study of atrial activity in the surface ECG can be used to distinctively distinguish between different mechanisms of AF is not yet known, but further investigation can improve our understanding of these mechanisms and help with the management of this common arrhythmia

Procainamide-lnduced polymorphous ventricular tachycardia

Seven cases of procainamide-induced polymorphous ventricular tachycardia are presented. In four patients, polymorphous ventricular tachycardia appeared after intravenous administration of 200 to 400 mg of procainamide for the treatment of sustained ventricular tachycardia. In the remaining three patients, procainamide was administered orally for treatment of chronic premature ventricular contractions or atrial flutter. These patients had Q-T prolongation and recurrent syncope due to polymorphous ventricular tachycardia. In four patients, the arrhythmia was rapidly diagnosed and treated with disappearance of further episodes of the arrhythmia. In two patients, the arrhythmia degenerated into irreversible ventricular fibrillation and both patients died. In the seventh patient, a permanent ventricular pacemaker was inserted and, despite continuation of procainamide therapy, polymorphous ventricular tachycardia did not reoccur. These seven cases demonstrate that procainamide can produce an acquired prolonged Q-T syndrome with polymorphous ventricular tachycardia.

Computer detection of atrioventricular dissociation from surface electrocardiograms during wide QRS complex tachycardias.

Differentiation of wide QRS complex tachycardias on surface electrocardiograms is difficult for physicians and computers due in part to their inability to identify atrial activity, specifically atrioventricular (AV) dissociation. We studied 20 examples of AV associated rhythms and 17 examples of AV dissociated ventricular tachycardia. We applied an algorithm consisting of subtraction of a mean beat from each individual beat in leads II and V1 to generate remainder electrocardiograms. The remainder electrocardiograms were visually inspected for the presence of P wave candidates and then autocorrelated. AV dissociated P wave candidates were evident on visual inspection of remainder electrocardiograms in none of 20 AV associated and 15 of 17 AV dissociated rhythms. Atrial cycle length and the presence of AV dissociation were automatically detected by applying a peak selection algorithm to the autocorrelation function. AV association was detected in all 20 AV associated rhythms and AV dissociation was detected for 11 of 17 AV dissociated rhythms (sensitivity 65%, specificity 100%, positive and negative predictive accuracy 100%, 77%). The correlation coefficient of detected vs true atrial cycle length for the 11 correctly detected AV dissociated rhythms was r = .98. Visual inspection of the remainder electrocardiograms along with the original electrocardiogram may increase the ease with which human readers can identify the presence of AV dissociation and thus diagnose ventricular tachycardia. Computer diagnosis of wide QRS complex tachycardias should be significantly improved by use of this algorithm.