Can the Heart Beat Again Where Does the Refractory Period Start in the Ekg

Information technology is generally accepted that AF is caused by multiple and meantime circulating reentrant circuits.^{i 2 3} Recordings of electrograms have demonstrated short and variable fibrillation intervals similar to ventricular fibrillation. Opthof et al⁴ suggested that during ventricular fibrillation, myocardial cells are reexcited equally soon as their refractory period ends. They demonstrated by transmembrane potential recording that at that place was no diastolic interval between successive activity potentials and that there was only a small departure in refractory periods during ventricular fibrillation. In contrast to ventricular fibrillation, larger variations in local fibrillation intervals have been observed during AF.^five Possible explanations for this have included either variation in local refractory periods or the presence of a meaning excitable gap. Mapping in both canine and human AF suggests that there is a loftier degree of spatial organization of wave fronts and that cells do not reexcite equally presently as their refractory periods finish.^{6 7} Still, the major determinant of the maximum charge per unit at which a region of myocardium can reexcite is the local ERP. Furthermore, the magnitude and spatial distribution of the ERP will determine whether intra-atrial reentry is initiated and maintained.^{8 nine 10} Withal, to measure out the local refractory period at multiple sites by the extrastimulus technique requires an all-encompassing menses of time. A method to rapidly approximate the distribution of refractory periods would assist in elucidating a potential underlying substrate of AF. Information technology would also allow evaluation of interventions that change ERP. The hypothesis of this study is that during AF, an individual site will eventually activate at an interval nearly its ERP. The objective of this study was to use local activation intervals during AF to estimate the local ERP. Specifically, the goals of this written report were (1) to demonstrate the temporal stability of local refractory periods under controlled conditions in the isolated canine atrial model, (2) to demonstrate a correlation between the local ERP and local minimum AFI, (3) to employ the computer-calculated local AFI as a predictor of the local ERP, and (4) to use AFI distribution maps to predict sites of conduction block.

Methods

Normal mongrel dogs (n=8) weighing 28.6±1.6 kg were anesthetized with pentobarbital (30 mg/kg Iv). The animals were intubated and ventilated with a positive-pressure ventilator. A median sternotomy was performed, and the azygos vein was ligated and divided. After the pericardium was opened, the fat pad on the correct AV groove was opened to betrayal the right coronary avenue and its atrial and ventricular branches. After heparinization of the animals with sodium heparin (100 U/kg Four), the ventricular branches of the right coronary avenue were ligated. The inferior and superior venae cavae were ligated and divided, and the aorta was cantankerous-clamped. Cold crystalloid cardioplegia solution (500 mL) was infused into the aortic root, and both atria were rapidly excised. The proximal right and left coronary arteries were separately cannulated with polyethylene tubing (ID, 0.86 mm; OD, 1.27 mm). After the ventricular branches of the left coronary artery were dissected and ligated, the ventricular myocardium was trimmed away. Both intact atria were mounted on carve up endocardial electrodes through each AV valve orifice. The training was placed in a temperature-controlled bath at 37°C and perfused with Krebs-Henseleit solution (pH, 7.4) through each coronary cannula. A flow charge per unit of ten to 15 mL/min was used to maintain a coronary perfusion force per unit area of 80 to 100 mm Hg. The preparation was likewise continuously superfused. Within 1 minute of establishing of perfusion, the preparation beat spontaneously in sinus rhythm. Subsequently a xxx-infinitesimal stabilization menstruation, information acquisition was started. Bipolar electrograms were simultaneously recorded from 253 endocardial sites during control conditions at the beginning and end of the study (sinus rhythm) and during the ERP measurement and consecration of AF with a single extrastimulus. 16 to 20 electrodes that were randomly selected from both atria were used to measure the local ERP. The electrode locations were chosen to comprehend all regions of both atria. The pacing threshold was determined at each electrode site. Only sites with a threshold of <one mA were used. The pacing stimulus was set at two times threshold. The S_oneSouth_ane interval was fix at 300 ms, and the extrastimulus was delivered afterwards a railroad train of viii paced complexes. ERP was determined by initially increasing the S₁S_ii interval by 10 ms until capture occurred. The Due south₁South₂ interval was then decreased by 1 ms until failure to capture occurred on iii successive attempts. ERP determinations were repeated in the same manner at the same sites ≈ii hours later for statistical comparison to determine electrophysiological stability of the preparation. In all studies, several episodes of sustained AF were induced during the measurement of ERP. During fibrillation, the electrophysiological information were saved for 5 to eighteen seconds from the fourth dimension of initiation of AF. In cases of sustained AF >iii minutes in duration, infusion of ii to 3 mL of cold crystalloid cardioplegia solution was required to defibrillate the atria chemically. Data analysis was resumed 10 minutes subsequently restoration of sinus rhythm.

A 256-channel computerized data acquisition and analysis arrangement was used to collect, procedure, and display information. The mapping system was based on a VaxStation Ii/GPX graphics workstation connected to two 128-channel PDP 11/23+–based information acquisition subsystems. Each PDP system contains two data translation DT3362 64-channel analog-to-digital converter boards and a 4-Mb memory board. The PDPs are diskless systems run past a control program that is downloaded from the Vax. The PDP memory is configured every bit a circular buffer, which allows the most contempo 16 seconds of data to exist saved. When the desired data are obtained, it is uploaded to the Vax via a directly retentiveness access interface. The system uses a 256-channel bipolar amplifier organization designed and built in-house with selectable loftier- and low-pass filters and gains. The systems are run with software developed in-house (GLAS) for data conquering command, data management, raw data display, and information analysis.

A selected electrogram was continuously monitored throughout the study. Bipolar electrograms were recorded at a gain of 1000, with a frequency response of l to 500 Hz. Each aqueduct was digitized at 1000 Hz with 12-bit resolution. Local endocardial activation times were determined from the maximum amplitude of the bipolar electrograms. All electrograms were edited visually to verify accuracy of the reckoner-picked activation time. In particular, the data were examined for double potentials, which resulted from recordings fabricated virtually an activation block or rotating wave fronts. All electrograms that had deflections occurring inside 100 ms of some other activation were considered candidates for double potentials. Both electrograms were examined relative to the surrounding electrograms. Usually, electrograms from two side by side sites had activations that corresponded with each deflection of the electrogram in question. The largest potential was always chosen from the double potential, and the smaller one was not counted as an activation. Typically, 1 deflection was much smaller in aamplitude, as illustrated in Fig 1, electrogram 208, cycles six and seven. In addition, the computer did not choice activations occurring inside lx ms of another activation. This usually eliminated the computer's picking both deflections in a double potential; even so, this was verified manually past a check of next sites. Each AFI was calculated by subtracting the local activation time between 2 adjacent local activations during a 2-2nd period of AF. A full of 8 to 18 seconds of AF were and so analyzed to calculate the minimum, mean, and median AFIs during that time span. Examples of four electrograms recorded during AF are shown in Fig 1, along with the AFI and the hateful, SD, and minimum values. Also shown is the local ERP determined by extrastimulation. The minimum AFIs calculated at all 253 sites were used to construct maps that were displayed on a schematic diagram or three-dimensional surface model of both atria.

Paired and unpaired t tests were used for statistical analysis. Correlations were made with the standard Pearson'due south correlation, and probabilities were calculated for each correlation coefficient. Linear regression was used to relate the AFI to the ERP. Results were considered to be statistically meaning when P<.05. All data, unless otherwise noted, were expressed as hateful±SD. All statistical analyses were performed with the SYSTAT statistical plan.^eleven

All animals received humane care in compliance with the "Principles of Laboratory Animal Care" formulated by the National Order for Medical Research and the Guide for the Care and Employ of Laboratory of Animals prepared past the National University of Scientific discipline and published by the National Institutes of Wellness (NIH publication 86-23, revised 1985). In addition, the report protocol was canonical by the Washington University Creature Studies Committee.

Results

Within xxx minutes after reperfusion with Krebs-Henseleit solution, the spontaneous rhythm stabilized. Data conquering was started at this time. The mean duration of the study, from the beginning to the end of data acquisition, was 215±36 minutes. The spontaneous cycle length of sinus rhythm was measured at the beginning and the end of the study, with hateful cycle lengths of 665±69 and 664±63 ms, respectively (north=8, P=.876, NS). The hateful ERPs of all measured sites during the initial and later recordings were 145±27 and 144±25 ms, respectively (north=173, P=.471, NS).

In all studies, multiple episodes of sustained AF (>three minutes) were induced by a single extrastimulus during measurement of ERP. Fig 2A illustrates an example electrogram recorded during 12 seconds of AF induced by a single extrastimulus. The individual cycle lengths of each AFI are shown over the 12-2nd recording period in Fig 2B. The ERP measured at this same recording site was 118 ms. In Fig 2C, a histogram shows the distribution of AFIs for the recording menstruum. The distribution of AFIs from 19 different sites at which the ERP was measured is illustrated in Fig 3 for a ten-2nd episode of AF. The data are shown as the AFIs minus the measured ERP. The aggregate data are consistent with the information shown in Fig 2, in which the majority of AFIs are longer than the local ERP. In the data shown in Fig 3, >93% of the AFIs are longer than the measured ERP.

To compare the local ERP with the local AFI, sites that showed an ERP difference of <10 ms over the fourth dimension form of the report and a pacing threshold of <one mA in both the initial and later measurements were selected. The smaller of the 2 ERPs was used for comparing with the AFI. The mean ERP at the sites at which AF could be induced was 124±18 ms (n=21), in comparison to the ERP of all sites, which was 141±25 ms (n=173, P<.005). Each AFI was calculated during a two-2d menstruation of AF. Four to 9 of these 2-second periods were then analyzed to calculate the minimum, mean, and median values encompassing the total duration of AF analyzed. The ERP and minimum AFI values converged with assay of an increasing time interval of AF (Fig 4). The mean accented departure betwixt the local ERP and local minimum AFI was 33 ms when but a 2-2nd period of AF was analyzed. Even so, equally longer durations were analyzed, the mean accented difference decreased to 18 ms at 4 seconds, 10 ms at 6 seconds, six ms at 8 seconds, etc (Fig four). Although the mean absolute divergence decreased as more seconds of AF were analyzed, x seconds was chosen as the maximum fourth dimension interval because the rate of decrease of the mean absolute divergence was physiologically insignificant beyond this betoken.

The correlation coefficient between the local ERP and minimum local AFI was .922 (northward=119, P<.001) when 10 seconds of AF was analyzed (Fig 5A). During that time interval, a range of two to four different episodes of AF were included, with a mean of 2.6 episodes. The number of local activations ranged between 5 and viii beats per 2nd. The mean and median local AFIs were also calculated and compared with the minimum local AFI (Fig 5). The correlation coefficients between the local ERP and mean local AFI and between the local ERP and median local AFI were .658 (due north=119, P<.001) and .735 (n=119, P<.001), respectively, when the same elapsing of AF was analyzed. Although both the mean and median AFIs showed statistically significant correlations, the percentage of variation accounted for by linear regression models was <60%, whereas that of minimum AFI was 86%. In 2 studies, a single x-second run of AF was analyzed. The correlation coefficient between the local ERP and minimum AFI was .771 (due north=34, P<.001). This was college than those of mean AFI (r=.438, n=34, P<.04) and of median AFI (r=.594, northward=34, P<.001) (Tabular array).

An case minimum AFI map constructed from a total of 10 seconds of AF for all 250 electrode sites is shown in Fig 6 displayed on a three-dimensional surface model of the endocardial surfaces of the atria. Sites at which AF was induced with a single extrastimulus are denoted by asterisks on the maps. Note that many of the sites in the atrium that induced AF are at sites of short ERP near a region of long ERP. Activation sequence maps of the A₁ and A₂ beats are shown along with electrograms recorded (Fig vii) from the three marked sites in Fig 6 recorded during a single extrastimulation. Cake of activation is demonstrated corresponding with the region of long AFI.

Discussion

This written report demonstrates a correlation between ERP and the minimum AFI (r=.92). The correlation is better than that for the mean (r=.66) and median (r=.74) AFIs. As a consequence of the stiff correlation, the minimum AFI adamant over at least a x-second menstruum of AF tin be used in conjunction with a multipoint mapping system to determine the field of ERP with high resolution. The model used is also unique in that it allowed interpretation of the ERP independent of reflex changes and atrial force per unit area changes associated with AF. In addition, as demonstrated in this study (Figs half-dozen and 7), the map of the estimated ERP distribution tin and then be used to predict sites of block and potential reentry.

A major deviation and a unique ascertainment of this report compared with in vivo studies is how the ERP relates to the AFI. In the in vivo studies, the AFI was generally much shorter than the ERP. It has been generally thought that this is due to rate-dependent shortening of the ERP. In the nowadays study, yet, the hateful AFI was longer. The present model is unique in that information technology is an in vitro model with no neuronal reflexes or pressure changes. In the in vivo studies, the information were taken in models in which reflex and dynamic atrial force per unit area changes occur. Both increased pressure and increased autonomic tone tin decrease ERP.^{12 xiii} The difference suggests that the AFIs measured in the in vivo studies may reflect both the intrinsic ERP, rate-dependent changes, and changes induced in ERP by reflexes and force per unit area changes. The minimum AFI in vivo may more than accurately reflect the truthful ERP during AF, fifty-fifty if information technology does not correlate too with the ERP determined during pacing at a slower rate. Furthermore, charge per unit-dependent shortening of ERP may not be as pronounced during AF because of the variability of the intervals.

The ERP in the correct atrium was compared with that in the left atrium. Every bit has been demonstrated previously,^viii our data show that, even in the isolated atria, the left atrial refractory periods are shorter than the right atrial refractory periods. The mean ERPs in the right atrium and left atrium were 153±27 ms (n=84) and 130±18 ms (northward=89), respectively, showing a statistically significant difference (P<.001). This may permit faster reentrant circuits to form in the left atrium, but repetitive 1:i activation of the right atrium may be precluded by the longer refractory flow of the right atrium.⁹ The mean refractory periods and the deviation betwixt the left and correct atria are similar to those recorded in the intact animal.^{ix 13}

In this study, several episodes of sustained AF were induced past a single extrastimulus during measurement of ERP. The ERP at the sites at which AF was induced was much shorter than at other sites. This implies that the shorter S₁S₂ was immune to propagate from those sites, reaching other sites that were still refractory and causing entrance block (Figs vi and 7) and later on AF. During AF, local atrial electrograms vary in both configuration and bicycle length (Figs 1 and 2). In this written report, the relative differences between the AFI and ERP ranged from −44 to +223 ms, with skew of the distribution positive to the ERP. Allessie et al^five attributed the variation in local fibrillation intervals to either the variation in duration of local refractoriness or the presence of a significant excitable gap. The data in the present report suggest that at that place is an excitable gap, because most intervals are greater than the ERP. It is unlikely that the refractory menstruum is greater during fibrillation than during extrastimulation, considering the average AFIs are significantly shorter than the basic S_aneDue south₁ drive charge per unit (300 ms).

Previous studies have shown that the hateful or median AFI correlates with ERP. Lammers et al^fourteen demonstrated a significant correlation between the median AFI and ERP and suggested that the analysis of local AFI could be used to gauge the spatial dispersion of refractory periods. However, the correlation was fabricated at only a single site. Although Lammers et al demonstrated a very good correlation, 8% of their data included much shorter AFIs, ranging between 5 and 50 ms. In retrospect, these probably represent double potentials and not private activation. To eliminate the trouble of picking both deflections of a double potential, the AFI information could be fitted to a statistical distribution and a lower hinge of the distribution used to estimate ERP. However, this type of analysis was not required because of the high spatial resolution and low dissonance of the data. If there is a significant amount of racket in the signal or if the spatial resolution is less, this technique may be needed to eliminate the consequence of picking both deflections when merely one activation occurs. Ramdat Misier et al^xv likewise showed a close correlation between the mean AFI and ERP. They made the correlation at only four sites. More recently, Morillo et al¹⁶ demonstrated a stiff correlation between ERP and mean ERP from a limited number of sites in a chronically paced canine model of AF.

In the nowadays written report, the ERP and minimum AFI converged with assay of an increasing time interval of AF. The mean accented departure decreased as more seconds of AF were analyzed; however, 10 seconds was chosen as the maximum time interval because the mean accented difference bend became flat beyond this point. During this fourth dimension interval, 2 to 4 different runs of AF were included, with a mean of two.half-dozen runs. The mean number of local activations during this interval was 36. Considering that atrial refractoriness shows cross-species difference and tends to increase with body size, the number of local activations would theoretically exist lower in humans than in dogs. Therefore, a longer period of AF may need to be analyzed in humans. In this report, the correlation coefficients between the ERP and hateful AFI and between the ERP and median AFI were analyzed, resulting in an R ² value <60%. A college correlation coefficient was obtained betwixt the ERP and minimum AFI, with an R ² value of 86%, when x seconds of AF was analyzed. A single run of AF of 10-second elapsing was also analyzed in 2 studies. The correlation coefficient between the local ERP and minimum AFI was .771, which showed a lower value than that obtained from analysis of several runs. This value, however, was still higher than those of the hateful or median AFI. These results suggest that assay of at least a 10-2d duration of AF that includes more than than ii runs and about 35 activations gives the best prediction of ERP from the minimum AFI.

The rate of convergence of the AFI to the ERP may requite insight into the organization of the AF. The slower convergence of AFI to the ERP in a single episode of AF compared with multiple episodes, both of the same elapsing, suggests that there is a high degree of organization of the AF. The more random the activation process, the more rapid the charge per unit of convergence volition be, since whatever one region would be activated from an increasing number of directions at a wider range of fourth dimension intervals. This would increment the probability that the region would activate near its ERP. Conversely, if a region activates synchronously, areas within that region with shorter ERP may never be stimulated by a wave front at a fourth dimension near its ERP. An example of this is seen during regular flutter, in which all regions answer at the same rate. In this case, the AFI would never converge to the ERP.

The measurement of AFI could exist used to evaluate antiarrhythmic drug therapy quantitatively, peculiarly class 3 agents that act to prolong refractory flow. Information technology is anticipated that the AFI would increase with prolongation of the ERP. Measurements of AFI at various concentrations of a drug would show how effective the drug was in prolonging ERP. In addition, when the AF terminated, it would delineate the critical amount of ERP prolongation needed to terminate AF in a item patient.

Selected Abbreviations and Acronyms

AF	=	atrial fibrillation
AFI	=	atrial fibrillation interval
ERP	=	constructive refractory period

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Effigy ane. 4 examples of bipolar electrograms recorded during AF are shown for a 1.5-second period. Vertical lines higher up each complex mark computer-picked activation times. Interval between each activation is also shown. To the left of each of the four tracings are hateful, SD, minimum interval, and ERP.

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Figure 2. A, A 12-second run of AF induced by a single extrastimulus. B, For the same run, intervals for each cycle are plotted against fourth dimension. A horizontal line shows measured ERP at same site. C, A distribution of the bicycle-length intervals is shown. Measured ERP is marked. A₁A_i interval is last interval of bones drive train before introduction of premature stimulus.

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Figure 3. Distribution of difference between measured ERP and AFIs measured from xix dissimilar sites at which ERP was directly determined over a 10-second flow.

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Figure 4. Accented difference of minimum AFI and ERP plotted over time for 18 seconds of AF.

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Figure v. ERP for all sites and all animals is plotted against minimum AFI (A), median AFI (B), and mean AFI (C). A regression line is shown for each graph, and the correlation coefficient is as well shown.

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Figure six. AFI at 250 sites is shown in 1 animal. Iv orthogonal views of a three-dimensional display of endocardial surfaces are shown. Asterisks mark sites at which the AF was initiated. Colour lawmaking for AFI is shown at lesser. Electrode sites 84, 142, and 141 are shown on anterior view. Gray areas are regions not covered by electrodes. RAA indicates right atrial appendage; LAA, left atrial bagginess; SVC, superior vena cava; IVC, inferior vena cava; and PV, pulmonary veins.

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Figure 7. Top, Electrograms recorded from iii electrode sites during last A₁A₁ interval (first complex) and A_iA₂ interval (second complex at sites 84 and 142). Electrode sites represent to sites marked in Fig 6. Activation sequence maps for concluding A₁ shell and A₂ beat are shown in lower 2 panels. Hatched area on A_two beat is a region that blocked and did not activate. Just anterior attribute of the right atrium is shown. Information were recorded from the same animal as used to make the AFI map in Fig vi. Next to each electrogram is the minimum AFI for that site. Betwixt each complex is the interval. Note that at site 141, activation is blocked.

Table 1. Comparison of Correlations Between the Minimum, Mean, and Median AFIs

	Minimum AFI	Mean AFI	Median AFI
10 Seconds of AF with >2 runs analyzed
Due north	119	119	119
Gradient	0.812	0.292	0.356
Intercept	xxx.076	70.351	68.551
r	.922	.658	.735
P	<.001	<.001	<.001
Single x-2d run of AF analyzed
Northward	34	34	34
Gradient	0.530	0.123	0.174
Intercept	62.925	101.093	95.828
r	.771	.438	.594
P	<.001	<.05	<.001

This report was supported in part by National Institutes of Health grants R01-HL-32257 and R01-HL-33722.

Footnotes

Correspondence to Richard B. Schuessler, PhD, Partition of Cardiothoracic Surgery, Box 8234-3308 CSRB, Washington University School of Medicine, 660 S Euclid Ave, St Louis, MO 63110.

References

• 1 Moe GK. On the multiple wavelet hypothesis of atrial fibrillation. Curvation Int Pharmacodyn Ther . 1962; 140:183-188.Google Scholar
• 2 Allessie MA, Lammers WJEP, Bonke FIM, Hollen J. Experimental evaluation of Moe's multiple wavelet hypothesis of atrial fibrillation. In: Zipes EP, Jalife J, eds. Cardiac Electrophysiology and Arrhythmias. Orlando, Fla: Grune & Stratton, Inc; 1985:265-275.Google Scholar
• 3 Schuessler RB, Grayson TM, Bromberg BI, Cox JL, Boineau JP. Cholinergically mediated tachyarrhythmias induced by a single extrastimulus in the isolated canine right atrium. Circ Res . 1992; 71:1254-1267.CrossrefMedlineGoogle Scholar
• iv Opthof T, Ramdat Misier AR, Coronel R, Vermeulen JT, Verberne HJ, Frank RGJ, Moulijn Air-conditioning, van Capelle FJL, Janse MJ. Dispersion of refractoriness in canine ventricular myocardium: effects of sympathetic stimulation. Circ Res . 1991; 68:1204-1215.CrossrefMedlineGoogle Scholar
• 5 Allessie MA, Kirchhof C, Scheffer GJ, Chorro F, Brugada J. Regional control of atrial fibrillation by rapid pacing in conscious dogs. Circulation . 1991; 84:1689-1697.CrossrefMedlineGoogle Scholar
• 6 Cox JL, Canavan TE, Schuessler RB, Cain ME, Lindsay BD, Stone C, Smith PK, Corr PB, Boineau JP. The surgical treatment of atrial fibrillation, II: intraoperative electrode physiologic mapping and description of the electrophysiologic basis of atrial flutter and atrial fibrillation. J Thorac Cardiovasc Surg . 1991; 101:406-426.CrossrefMedlineGoogle Scholar
• 7 Allessie MA. Reentrant mechanisms underlying atrial fibrillation. In: Zipes DP, Jalife J, eds. Cardiac Electrophysiology: From Cell to Bedside. Philadelphia, Pa: WB Saunders Co; 1995:562-566.Google Scholar
• 8 Boineau JP, Schuessler RB, Mooney CR, Miller CB, Wylds AC, Hudson RD, Borremans JM, Brockus CW. Natural and evoked atrial flutter due to circus movement in dogs. Am J Cardiol . 1980; 45:1167-1181.CrossrefMedlineGoogle Scholar
• 9 Sato S, Yamauchi Southward, Schuessler RB, Boineau JP, Matsunaga Y, Cox JL. The result of augmented atrial hypothermia on atrial refractory menses, conduction, and atrial palpitate/fibrillation in the canine heart. J Thorac Cardiovasc Surg . 1992; 104:297-306.MedlineGoogle Scholar
• 10 Schoels Due west, Kuebler Due west, Yang H, Gough W, El-Sherif Due north. A unified functional/anatomic substrate for circus motility atrial flutter: activation and refractory patterns in the canine right atrial enlargement model. J Am Coll Cardiol . 1993; 21:73-84.CrossrefMedlineGoogle Scholar
• 11 Systat for Windows: Statistics, Version 5 Edition. Evanston, Sick: SYSTAT, Inc; 1992.Google Scholar
• 12 Calkins H, El-Atassi R, Kalbfleisch Southward, Langberg J, Morady F. Effects of an acute increase in atrial pressure on atrial refractoriness in humans. Pacing Clin Electrophysiol. 1992;15(pt i):1674-1680.Google Scholar
• xiii Schuessler RB, Boineau JP, Bromberg BI, Paw DE, Yamauchi South, Cox JL. Normal and aberrant activation of the atrium. In: Zipes DP, Jalife J, eds. Cardiac Electrophysiology: From Cell to Bedside. Philadelphia, Pa: WB Saunders Co; 1995:543-562.Google Scholar
• 14 Lammers WJEP, Allessie MA, Rensma PL, Schalij MJ. The utilize of fibrillation cycle length to make up one's mind spatial dispersion in electrophysiological properties and to characterize the underlying mechanism of fibrillation. New Trends Arrhythmias . 1986; two:109-112.Google Scholar
• fifteen Ramdat Misier AR, Opthof T, van Hemel NM, Defauw JJAM, de Bakker JMT, Janse MJ, van Capelle FJL. Increased dispersion of 'refractoriness' in patients with idiopathic paroxysmal atrial fibrillation. J Am Coll Cardiol . 1992; 19:1531-1535.CrossrefMedlineGoogle Scholar
• 16 Morillo CA, Klein GJ, Jones DL, Guiraudon CM. Chronic rapid atrial pacing: structural, functional, and electrophysiological characteristics of a new model of sustained atrial fibrillation. Circulation . 1995; 92:1588-1595.Google Scholar

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Source: https://www.ahajournals.org/doi/10.1161/01.cir.94.11.2961

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