Temporal repolarization lability differences among genotyped patients with the long QT syndrome

that they were at their ATP III goals. The progressive biologic efficacy of statins is unlikely to cause this outcome, because they reach their full effect by 3 weeks9 and would therefore have been at steady state during the study period. We therefore postulate that the changes in LDL cholesterol that occurred between follow-up visits (increases and decreases) were largely independent of the specific pharmacologic activity of the drugs. Moreover, because the efficacy of statins is not dependent on baseline LDL cholesterol levels (per package inserts), baseline LDL cholesterol differences between the groups should not contribute to the divergence in LDL response from follow-up 1 to follow-up 2. We hypothesized that a patient’s initial LDL cholesterol reduction from statins, as communicated at the first follow-up visit, would modify subsequent lipid changes. Further, we speculated that these changes would reflect nonprescriptive influences, including patient adherence to medication, lifestyle (dietary change, weight loss, exercise), or both. We contend that in patients who return for follow-up, those who achieve their LDL cholesterol goals subsequently become less compliant, whereas those not initially at their goals become more compliant. Because we did not explicitly measure compliance with medication (e.g., with pill counts or drug levels) or lifestyle (ex-

cept by self-report of physical activity and dietary adherence), we cannot specify whether the variability in LDL cholesterol that we observed reflected medication compliance, adherence to diet and exercise, or both. However, our results suggest that efforts to prevent cardiovascular disease must recognize the clinical relevance of nonprescriptive influences to improve the achievement of recommended treatment targets and narrow the treatment gap. 1. Pearson TA, Peters TD. The treatment gap in coronary artery disease and heart failure: community standards and the post-discharge patient. Am J Cardiol 1997;80(suppl):45H–52H. 2. EUROASPIRE I and II Group. Clinical reality of coronary prevention guidelines: a comparison of EUROASPIRE I and II in nine countries. European Action on Secondary Prevention by Intervention to Reduce Events. Lancet 2001;357:995–1001. 3. Hoerger TJ, Bala MV, Bray JW, Wilcosky TC, LaRosa J. Treatment patterns and distribution of low-density lipoprotein cholesterol levels in treatment-eligible United States adults. Am J Cardiol 1998;82:61– 65. 4. Marcelino JJ, Feingold KR. Inadequate treatment with HMG-CoA reductase inhibitors by health care providers. Am J Med 1996;100:605– 610. 5. Frolkis JP, Pearce GL, Nambi V, Minor S, Sprecher DL. Statins do not meet expectations for lowering low-density lipoprotein cholesterol levels when used in clinical practice. Am J Med 2002;113:625– 629. 6. Frolkis JP, Sprecher DL, Foody JM, Pearce GL. Improving risk factor control in heart disease: the effectiveness of a multidisciplinary preventive cardiology program. Prev Med Manage Care 2000;1:77– 88. 7. Stein EA, Lane M, Laskarzewski P. Comparison of statins in hypertriglyceridemia. Am J Cardiol 1998;81(suppl):66B– 69B. 8. Jones PH. Tachyphylaxis in 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors. Am J Cardiol 2001;87:1032–1034. 9. Illingworth DR, Tobert JA. HMG-CoA reductase inhibitors. Adv Protein Chem 2001;56:77–114.

Temporal Repolarization Lability Differences Among Genotyped Patients With the Long QT Syndrome Kenneth Bilchick, MD, Matti Viitasalo, MD, Lasse Oikarinen, MD, Barry Fetics, MSE, Gordon Tomaselli, MD, Heikki Swan, MD, Päivi J. Laitinen, MSc, Heikki Väänänen, MSc, Kimmo Kontula, MD, and Ronald D. Berger, MD, PhD The investigators sought to test whether certain long QT syndrome (LQTS) mutations are associated with increased repolarization lability and whether repolarization lability (quantified by the QT variability index [QTVI]) is increased in patients with LQTS compared with controls. In 32 genotyped patients with LQTS type 1 (LQT1), 32 genotyped patients with LQTS From the Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; the Departments of Cardiology and Medicine, University of Helsinki, Helsinki; and the Laboratory of Biomedical Engineering, Helsinki University of Technology, Espoo, Finland. This work was supported by grants P50 HL52307 and R44 HL61903 from the National Heart, Lung, and Blood Institute, Bethesda, Maryland; the Finnish Foundation for Cardiovascular Research, Helsinki, Finland; the Sigrid Juselius Foundation, Helsinki, Finland; and the Finnish Academy, Helsinki, Finland. Dr. Berger is an established investigator of the American Heart Association, Dallas, Texas, and receives support from the Donald W. Reynolds Foundation, Las Vegas, Nevada. Dr. Berger’s address is: Carnegie 592, Johns Hopkins Hospital, 600 North Wolfe Street, Baltimore, Maryland 21287. E-mail: [email protected]. Manuscript received June 11, 2004; revised manuscript received and accepted July 21, 2004.

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type 2 (LQT2), and 32 controls, the QTVI was increased in patients with LQT2 (ⴚ0.973 ⴞ 0.394, p ⴝ 0.01 vs controls) and in patients with LQT1 with mutations other than KCNQ1-FIN (ⴚ0.942 ⴞ 0.264, p ⴝ 0.04 vs controls) but was similar between the KCNQ1-FIN group and controls. 䊚2004 by Excerpta Medica, Inc. (Am J Cardiol 2004;94:1312–1316)

lthough the degree of QTc prolongation has prognostic significance in long QT syndrome (LQTS), A the development of additional noninvasive indexes to characterize phenotypes associated with specific LQTS mutations may be clinically useful. We have recently described a method for quantifying the temporal fluctuations in ventricular repolarization reflected in QT variability (QTV) on surface electrocardiograms. In this study, we sought to test the hypotheses that repolarization is more labile in patients with LQTS compared with controls and that quantifiable repolarization lability differs among pa0002-9149/04/$–see front matter doi:10.1016/j.amjcard.2004.07.123

were eligible for this study. In total, we studied 32 patients with LQTS Controls LQT1-FIN LQT1-OTHER LQT2 type 1 (LQT1), 32 patients with (n ⫽ 32) (n ⫽ 18) (n ⫽ 14) (n ⫽ 32) LQTS type 2 (LQT2), and 32 unafCharacteristic (33%) (18%) (14%) (33%) p Value fected control patients. The specific Men/women 19/13 9/9 7/7 18/14 0.745* LQTS-causing mutations and their Age (yrs) 36 ⫾ 13 31 ⫾ 14 31 ⫾ 17 32 ⫾ 14 0.565† assays have been previously described.1–5 In the LQT1 group, the *Chi-square. † Analysis of variance. KCNQ1 mutations were G239S (n ⫽ 2), D371N (n ⫽ 12), and G589D or KCNQ1-FIN (n ⫽ 18). In a prospectively defined subgroup analysis, we separated the LQT1 group into the LQT1-FIN (those with the KCNQ1-FIN mutation) and LQT1-Other (those with 2 other mutations) groups. In the LQT2 group, the KCNH2 mutations were del453C (n ⫽ 8), R176W (n ⫽ 3), P451L (n ⫽ 1), L552S (n ⫽ 11), Y569H (n ⫽ 1), G584S (n ⫽ 5), and G601S (n ⫽ 3). The control population was composed of the clinically unaffected family members of the patients with LQTS who were proven noncarriers of the respective KCNQ1 or KCNH2 mutations. None of the subjects was on ␤ blockers or antiarrhythmic drug therapy during data collection. The ethical review committee of the institute approved the study, and informed consent was obtained from all participants. Patients and controls underwent ambulatory 24hour 2-lead Holter monitoring. All subjects were in normal sinus rhythm during monitoring. For each subject, we selected and digitized a 20-minute segment obtained in the afternoon, while the patient was awake, that was free of noise or motion artifacts. Beat-to-beat QTV analysis has been validated for segments as short as 5 minutes.6,7 In addition, the importance of a good signal-to-noise ratio in the electrocardiographic signal for accurate QTV analysis has been shown,7 thus limiting the applicability of this analysis to long (e.g., 24-hour) records. We therefore elected to set the segment length to 20 minutes so that the analysis could be confined to electrocardiographic data manually scanned for a good signal-to-noise ratio. Temporal QTV analysis was performed in a blinded fashion using custom-written software. The algorithm used for QT interval measurement has been described in detail previously.6,7 Briefly, after R-wave detection, the algorithm finds the QT interval of each beat by determining how much the ST segment and T FIGURE 1. (A) QTVI: group means and 95% confidence intervals. wave must be stretched or compressed in time to best For comparison between patients with LQT2 and controls, p ⴝ 0.01. For comparison between patients with LQT2 and those match a preselected template beat. Evenly sampled with LQT1, p ⴝ 0.39. For comparison between patients with heart rate and QT interval time series were then conLQT1 and controls, p ⴝ 0.19. (B) Influence of the LQT1 genotype structed from the sequence of RR and QT intervals. on QTVI: group means and 95% confidence intervals. For comThe heart rate mean (HRM) and heart rate variance parison between patients with LQT2 and controls, p ⴝ 0.01. For (HRV) and the QT interval mean (QTM) and QTV comparison between patients with LQT1 other and controls, p ⴝ were computed from the 20-minute epochs. A normal0.04. ized QTV index (QTVI) was then derived for each epoch according to the equation: QTVI ⫽ log10[(QTV tients with LQTS with different disease-causing / QTM2) / (HRV / HRM2)]. The QTVI is taken as the mutations. logarithm of a quotient. The quotient quantifies the ••• ratio between QT and heart rate variability; each is Finnish patients with a genotype-verified diagnosis internally normalized by its respective mean square. of LQTS and available 24-hour Holter recordings Because a quotient is not gaussian distributed, the TABLE 1 Demographic Data of the Patients and Controls

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TABLE 2 Results by Genotype

Variable QTVI QTV/QTM2 HRV/HRM2 Mean QTc (ms) HRM beats/min

Controls (n ⫽ 32) ⫺1.220 0.271 4.480 415 67

⫾ ⫾ ⫾ ⫾ ⫾

0.314 0.223 2.741 25 12

LQT1-FIN (n ⫽ 18) ⫺1.184 0.268 3.984 463 72

⫾ ⫾ ⫾ ⫾ ⫾

0.173 0.181 1.875 30 8

LQT1-Other (n ⫽ 14) ⫺0.942 0.507 4.146 494 70

⫾ ⫾ ⫾ ⫾ ⫾

0.264* 0.533 3.238 52‡ 13

LQT2 (n ⫽ 32) ⫺0.973 0.487 4.585 472 67

⫾ ⫾ ⫾ ⫾ ⫾

0.394† 0.530 5.001 46§ 14

Analysis of Variance p Value 0.004 0.051 0.900 ⬍0.001 0.458

Posthoc tests:*p ⫽ 0.04 versus controls and p ⫽ 0.15 versus LQT1-FIN; †p ⫽ 0.01 versus controls and p ⫽ 0.12 versus LQT1-FIN; ‡p ⬍0.001 versus controls and p ⫽ 0.12 versus LQT1-FIN; §p ⬍0.001 versus controls.

FIGURE 2. QTVI versus QTc in (A) the entire study population (r ⴝ 0.251, p ⴝ 0.014), (B) the 32 control patients (r ⴝ 0.010, p ⴝ 0.96), (C) the 32 patients with LQT1 (r ⴝ 0.469, p ⴝ 0.007), and (D) the 32 patients with LQT2 (r ⴝ ⴚ0.016, p ⴝ 0.93).

logarithm is taken to provide a normally distributed index and allow standard parametric statistical testing. Data were analyzed with SPSS version 10.0 (SPSS, Inc., Chicago, Illinois). All continuous data are presented as means ⫾ SDs. Mean values of normally distributed parameters were compared among groups using analysis of variance. Because the QTV and HRV parameters were not normally distributed, they were log-transformed before testing. For multiple comparisons, post hoc testing with Tukey’s method was used. A 2-tailed p value ⬍0.05 was required to reject the null hypothesis in all tests. 1314 THE AMERICAN JOURNAL OF CARDIOLOGY姞

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Age and gender were similar among the control, LQT1-FIN, LQT1-Other, and LQT2 groups (Table 1). The mean heart rates in the different groups were similar and ranged from 67 to 72 beats/min. When the initial groups were compared with one another, QTVI was greater in the patients with LQT2 than in controls (p ⫽ 0.01; Figure 1). The QTVI in patients with LQT2 tended to be greater than that in patients with LQT1, and the QTVI of patients with LQT1 tended to be greater than that in controls, but neither difference reached statistical significance. When the LQT1 group was separated into those NOVEMBER 15, 2004

with the KCNQ1-FIN mutation (LQT1-FIN) and those with 1 of 2 other KCNQ1 mutations (LQT1Other) (Figure 1), we found that the mean QTVI was less in patients in the LQT1-FIN group, with minimal overlap in observed QTVI between the 2 groups, although only a statistical trend was observed (⫺1.184 ⫾ 0.173 vs ⫺0.942 ⫾ 0.264, p ⫽ 0.15). However, as listed in Table 2, we did observe a significantly greater QTVI in the LQT2 group (⫺0.973 ⫾ 0.394) and the LQT1-Other group (⫺0.942 ⫾ 0.264) compared with controls (⫺1.220 ⫾ 0.314; p ⫽ 0.01 for LQT2 comparison, p ⫽ 0.04 for LQT1-Other comparison). Of note, the group differences in HRM and HRV (Table 2) were not significant. The group differences in QTV by analysis of variance were significant, but none of the pairwise comparisons for QTV reached statistical significance. As listed in Table 2, the mean QTc in the LQT2, LQT1-FIN, and LQT1-Other groups was greater than that in the normal subjects (p ⬍0.001). The difference in QTc among the LQT1-FIN, LQT1-Other, and LQT2 groups was not significant, although a trend was noted for greater QTc in the LQT1-Other group compared with the LQT1-FIN group. There was a weak correlation in the overall group between the QTc and the QTVI (r ⫽ 0.251, p ⫽ 0.014; Figure 2). When the data were analyzed according to group (control vs LQT1 vs LQT2), a correlation was observed only in the LQT1 group (r ⫽ 0.469, p ⫽ 0.007), although this correlation was also weak, with a broad range of observed QTVIs for any given QTc (Figure 2) When the LQT1 group was further subdivided into the LQT1-FIN and LQT1-Other groups, no significant correlations were observed. •••

We found that patients with the LQT2 phenotype and those with the LQT1 mutations other than G589D exhibited greater temporal QTV than controls and patients in the KCNQ1-FIN group. In fact, temporal QTV in the KCNQ1-FIN group was quite similar to that of controls. Although temporal QTV initially appeared to be greater in patients with LQT2 than in patients with LQT1, the difference was no longer present when only patients with LQT1 having mutations other than the KCNQ1-FIN mutation were included in the comparison. We thus build on recent clinical and mechanistic observations in patients with mutations of KCNQ18 –11 and KCNH210 –13 by showing that increased temporal repolarization variability may be associated with mutations affecting the ion channels for IKr and IKs, depending on the nature of the mutation. Furthermore, we have shown that an IKs mutation associated with a prolonged QTc (G589D) may have normal QTV. This supports the conclusion that increased temporal repolarization lability as measured by the QTVI provides additional information complementary to that provided by the QTc regarding the degree to which ion channel function is disrupted. In addition, as shown in Figure 2, only weak QTVI-QTc correlations were observed in the overall group, and these weak correlations persisted only in the LQT1

group after subgroup analysis. These figures also illustrate that there is a broad range of observed QTV for any QTc, even in the LQT1 group. Although a prolonged QTc interval presumably reflects an overall decrease in repolarizing currents, it does not necessarily imply significant temporal variability in these currents. In contrast, the QTVI, which has already been shown to be increased in patients with ischemic and nonischemic cardiomyopathies,14 hypertrophic cardiomyopathy,15 and acute coronary ischemic episodes,16 likely reflects the overall variability and perhaps instability of the repolarizing currents. Reasons why some LQTS mutations produce more repolarization lability than others include differences in the degree to which mutations disrupt channel function directly, through dominant negative effects, or through alterations of the gating kinetics, thus changing time-dependent channel function. Evaluation of the clinical significance of LQTS-associated mutations with normal QTV was not part of the present study design and deserves further investigation. Acknowledgment: We wish to thank Melvin Scheinman, MD, for his encouragement in the design of this study.

1. Piippo K, Swan H, Pasternack M, Chapman H, Paavonen K, Viitasalo M,

Toivonen L, Kontula K. A founder mutation of the potassium channel KCNQ1 in long QT syndrome: implications for estimation of disease prevalence and molecular diagnostics. J Am Coll Cardiol 2001;37:562–568. 2. Saarinen K, Swan H, Kainulainen K, Toivonen L, Viitasalo M, Kontula K. Molecular genetics of the long QT syndrome: two novel mutations of the KVLQT1 gene and phenotypic expression of the mutant gene in a large kindred. Hum Mutat 1998;11:158 –165. 3. Neyroud N, Richard P, Vignier N, Donger C, Denjoy I, Demay L, Shkolnikova M, Pesce R, Chevalier P, Hainque B, et al. Genomic organization of the KCNQ1 K⫹ channel gene and identification of C-terminal mutations in the long-QT syndrome. Circ Res 1999;84:290 –297. 4. Laitinen P, Fodstad H, Piippo K, Swan H, Toivonen L, Viitasalo M, Kaprio J, Kontula K. Survey of the coding region of the HERG gene in long QT syndrome reveals six novel mutations and an amino acid polymorphism with possible phenotypic effects. Hum Mutat 2000;15:580 –581. 5. Piippo K, Laitinen P, Swan H, Toivonen L, Viitasalo M, Pasternack M, Paavonen K, Chapman H, Wann KT, Hirvela E, et al. Homozygosity for a HERG potassium channel mutation causes a severe form of long QT syndrome: identification of an apparent founder mutation in the Finns. J Am Coll Cardiol 2000;35:1919 –1925. 6. Berger RD, Kasper EK, Baughman KL, Marban E, Calkins H, Tomaselli GF. Beat-to-beat QT interval variability: novel evidence for repolarization lability in ischemic and nonischemic dilated cardiomyopathy. Circulation 1997;96:1557– 1565. 7. Berger RD. QT variability. J Electrocardiol 2003;36:S83–S87. 8. Zareba W, Moss A, Sheu G, Kaufman ES, Priori S, Vincent GM, Towbin JA, Benhorin J, Schwartz PJ, Napolitano C, et al. Location of mutation in the KCNQ1 and phenotypic presentation of the long QT syndrome. J Cardiovasc Electrophysiol 2003;14:1149 –1153. 9. Donger C, Denjoy I, Berthet M, Neyroud N, Cruaud C, Bennaceur M, Chivoret G, Schwartz K, Coumel P, Guicheney P. KVLQT1 C-terminal missense mutation causes a forme fruste long-QT syndrome. Circulation 1997;96:2778 –2781. 10. Swan H, Viitasalo M, Piippo K, Laitinen P, Kontula K, Toivonen L. Sinus node function and ventricular repolarization during exercise stress test in long QT syndrome patients with KvLQT1 and HERG potassium channel defects. J Am Coll Cardiol 1999;34:823– 829. 11. Perkiomaki JS, Zareba W, Nomura A, Andrews M, Kaufman ES, Moss AJ. Repolarization dynamics in patients with long QT syndrome. J Cardiovasc Electrophysiol 2002;13:651– 656. 12. Moss AJ, Zareba W, Kaufman ES, Gartman E, Peterson DR, Benhorin J, Towbin JA, Keating MT, Priori SG, Schwartz PJ, et al. Increased risk of arrhythmic events in long-QT syndrome with mutations in the pore region of the human ether-a-go-go-related gene potassium channel. Circulation 2002;105: 794 –799.

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13. Sanguinetti MC, Curran ME, Spector PS, Keating MT. Spectrum of HERG K⫹-channel dysfunction in an inherited cardiac arrhythmia. Proc Natl Acad Sci USA 1996;93:2208 –2212. 14. Atiga WL, Calkins H, Lawrence JH, Tomaselli GF, Smith JM, Berger RD. Beat-to-beat repolarization lability identifies patients at risk for sudden cardiac death. J Cardiovasc Electrophysiol 1998;9:899 –908.

15. Atiga WL, Fananapazir L, McAreavey D, Calkins H, Berger RD. Temporal

repolarization lability in hypertrophic cardiomyopathy caused by beta-myosin heavy-chain gene mutations. Circulation 2000;101:1237–1242. 16. Murabayashi T, Fetics B, Kass D, Nevo E, Gramatikov B, Berger RD. Beat-to-beat QT interval variability associated with acute myocardial ischemia. J Electrocardiol 2002;35:19 –25.

Slow Pathway Modification for Atrioventricular Nodal Reentrant Tachycardia Jonathan R. Kaltman, MD, Larry A. Rhodes, MD, Tammy S. Wieand, Jean E. Ennis, RN, Victoria L. Vetter, MD, and Ronn E. Tanel, MD The change in the “refractory window” was assessed as a possible indicator of successful slow pathway modification in 26 pediatric patients with persistent dual–atrioventricular node physiology. The “refractory window” was defined as the difference between the fast and slow pathway effective refractory periods. A significant decrease in the refractory window (p <0.001) after successful slow pathway modification was found. 䊚2004 by Excerpta Medica, Inc. (Am J Cardiol 2004;94:1316 –1319)

low pathway modification for atrioventricular (AV) nodal reentrant tachycardia (AVNRT) acS counts for approximately 25% of pediatric radiofre-

quency ablations.1 Success rates of ⬎90% have been reported,1,2 with 71% freedom from recurrence at 3 years.2 Despite this high success rate, controversy exists regarding the most accurate end point for the procedure. The noninducibility of supraventricular tachycardia (SVT) is generally considered 1 of the criteria for elimination of AVNRT. However, previous work is unclear as to the necessity for the elimination of dual–AV node physiology to prevent recurrence.3–9 The potential expense of attaining the complete elimination of slow pathway conduction is an increased incidence of AV block. In addition, special consideration must be taken for pediatric patients, who provide unique challenges for the avoidance of AV block. Therefore, there is a need to identify an alternative indicator of slow pathway modification success in the setting of persistent dual–AV node physiology. Studies in adults have shown that the difference between the effective refractory period (ERP) of the fast and slow pathways decreases after successful slow pathway modification.3,8,10 This difference has become known as the “refractory window.”8 This study evaluates the change in the refracFrom The Cardiac Center at The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; and the Department of Pediatrics, University of Pennsylvania, Philadelphia, Pennsylvania. Dr. Kaltman was supported by training grant T32-HL07915 from the National Institutes of Health, Bethesda, Maryland. Dr. Kaltman’s address is: Division of Cardiology, The Children’s Hospital of Philadelphia, 34th and Civic Center Boulevard, Philadelphia, Pennsylvania 19104. E-mail: [email protected]. Manuscript received April 5, 2004; revised manuscript received and accepted July 7, 2004.

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MS,

tory window during slow pathway modification in pediatric patients. •••

We reviewed 125 consecutive electrophysiologic studies involving slow pathway modification for AVNRT in patients ⬍21 years of age at our institution from August 1995 to February 2004. Forty-one studies (33%) had evidence of dual–AV node physiology in the absence of isoproterenol at the end of the procedure. Nine studies were excluded because AVNRT prevented the measurement of the refractory window, and 6 were excluded because of incomplete data. Therefore, the study population consisted of 26 patients. The characteristics of these patients and their procedures are listed in Table 1. The local institutional review board approved this retrospective review. Our institutional protocol for the electrophysiologic study and slow pathway modification has previously been described.11 Briefly, after percutaneous venous access was achieved, multipolar catheters were placed in the high right atrium, His bundle, right ventricular apex, and coronary sinus locations. Baseline intervals and ERPs of the fast pathway, slow pathway, and atria were measured during programmed extrastimulus testing. The presence of dual–AV node physiology was determined by a ⬎40-ms increase in the A2H2 interval in response to a 10-ms decrement in the A1A2 interval.12 The fast pathway ERP was defined as the longest A1A2 interval that exhibited a ⬎40-ms increase in the A2H2 interval with a 10-ms decrement in the A1A2 interval. The slow pathway ERP was defined as the longest A1A2 interval that activated the atrium but did not conduct to the ventricle. The atrial ERP was defined as the longest A1A2 interval that did not activate the atrium. The intervals and refractory periods used for this study were measured in the absence of an isoproterenol infusion. Sustained SVT was induced with atrial or ventricular pacing or with programmed extrastimulus testing. If SVT could not be induced under baseline conditions, an isoproterenol infusion was started. AVNRT was confirmed by a VA interval ⬍60 ms with retrograde atrial activation earliest in the His catheter electrogram,13 the failure of premature ventricular extrastimuli to advance atrial activity when placed into SVT during His refractoriness,14 and an HA interval 0002-9149/04/$–see front matter doi:10.1016/j.amjcard.2004.07.124