(Circulation. 2000;102:300.)
© 2000 American Heart Association, Inc.
Clinical Investigation and Reports |
Reduced Ventricular Response Irregularity Is Associated With Increased Mortality in Patients With Chronic Atrial Fibrillation
From the Third Department of Internal Medicine, Nagoya City University Medical School, Nagoya, Japan.
Correspondence to Akira Yamada, MD, Third Department of Internal Medicine, Nagoya City University Medical School, 1 Kawasumi Mizuho-cho Mizuho-ku, Nagoya 467-8601, Japan. E-mail a.yamada{at}med.nagoya-cu.ac.jp
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Abstract |
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Background—Variations in the ventricular response interval (VRI) during atrial fibrillation (AF) may be reduced in patients with adverse clinical outcomes. The properties of VRI dynamics associated with prognosis remain undetermined.
Methods and Results—In 107 patients with chronic AF (age, 64±9 years), we analyzed a 24-hour ambulatory ECG for VRI variability (SD, SD of successive differences, and SD of 5-minute averages) and VRI irregularity (Shannon entropy of histogram, symbolic dynamics, and approximate entropy of beat-to-beat and minute-to-minute fluctuations [ApEnb-b and ApEnm-m]). During a follow-up period of 33±16 months, 18 patients died (17%), 9 from cardiac causes, 7 from fatal strokes, and 2 from malignancies. Reductions in all VRI variability and irregularity measures were associated with an increased risk for cardiac death but not for fatal stroke. A significant association with cardiac death was also found for ejection fraction (relative risk, 1.10; 95% confidence interval [CI], 1.04 to 1.17, per 1% decrement) and ischemic AF (relative risk, 6.52; 95% CI, 1.62 to 26.3). After adjustment for these clinical variables, all irregularity measures except symbolic dynamics had predictive value (relative risks [95% CIs] per 1SD decrement: Shannon entropy of histogram, 2.03 [1.14 to 3.61]; ApEnb-b, 1.72 [1.14 to 2.60]; and ApEnm-m, 1.90 [1.03 to 3.52]); however, the predictive power of variability measures was no longer significant. When the patients were stratified with the 33rd and 67th percentile values of ApEnb-b (1.83 and 1.94, respectively), the 5-year cardiac mortality rates for the upper, middle, and lower tertiles were 0%, 13%, and 43%, respectively (log-rank test, P=0.04).
Conclusions—Reduced VRI irregularity in a 24-hour ambulatory ECG has an independent prognostic value for cardiac mortality during long-term follow-up in patients with chronic AF.
Key Words: atrial fibrillation • entropy • heart rate • mortality • nonlinear dynamics
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Introduction |
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During atrial fibrillation (AF), the sinus node loses its pacemaker function; rapid and random atrial impulses result. These impulses create disorganized atrioventricular nodal conduction and, thus, generate a highly irregular fluctuation of the ventricular response interval (VRI). Such conditions seem to preclude applications of standard heart rate variability (HRV) analysis.1 Nevertheless, some studies suggest that reduced HRV (VRI variability) may predict adverse prognosis, even in patients with chronic AF.2 3 However, these studies examined only conventional HRV measures assuming sinus rhythm; they may have overlooked important prognostic information existing in different properties of VRI dynamics. Recently, new mathematical methods were introduced for characterizing the nonlinear dynamics of biological signals.4 Such methods revealed that the complexity/irregularity of heart rate dynamics had prognostic value in cardiac patients with sinus rhythm.5 6 In this study, we applied these methods to the analysis of 2 different features of VRI dynamics, variability and irregularity, in patients with chronic AF and observed the associations of these features with the risk for mortality during long-term follow-up.
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Methods |
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Patients
We studied 115 consecutive outpatients with chronic AF who underwent ambulatory ECG monitoring at Nagoya City University Hospital between 1993 and 1997. Patients were eligible if they were between 20 and 75 years of age and had chronic AF, as documented by at least bimonthly medical records for >1 year. Patients were excluded for the following reasons: (1) congestive heart failure of New York Heart Association class III or IV; (2) a myocardial infarction, stroke, or major surgical procedure within the previous 3 months; (3) high-grade atrioventricular block, bundle branch block, or pacemaker therapy; (4) sustained ventricular tachycardia or frequent ventricular ectopies >5% of 24-hour total beats; (5) class I, II, or III antiarrhythmic medication; or (6) insulin-dependent diabetes, chronic obstructive pulmonary disease, uncontrolled hypertension, active thyroid disease, severe renal or hepatic disease, or other life-threatening disease. All patients gave written informed consent. The study protocols were in accordance with the ethical guidelines of Nagoya City University Medical School.
Baseline Measurements and Follow-Up
The ambulatory ECG was recorded with a 3-channel portable
tape recorder (DMC-3253, Nihon Koden) during the patient’s
usual daily activities. Analyzable data were obtained in only 109
patients; data were lost due to technical failure in 5 patients and due
to frequent ventricular ectopies in 1 patient.
The patients were followed-up in the outpatient clinic of the Nagoya City University Hospital or by their family doctors. The ventricular rate was controlled, if necessary, by digoxin. Anticoagulation therapy with warfarin was recommended in patients with nonidiopathic AF.
In August 1998, 108 of the 109 patients or their families completed a mailed inquiry and were interviewed by telephone about cardiovascular and noncardiovascular events by a physician blinded to the results of the VRI measurements. One patient with idiopathic AF was lost to follow-up after the baseline measurements. Death was the only end point; it was classified as (1) cardiac death (heart failure, fatal arrhythmia, and sudden unexpected death within 1 hour after the onset of a new symptom), (2) fatal stroke (deaths attributable to cerebral infarction or hemorrhage), and (3) all-cause death.
Data Processing
The ambulatory ECG tapes were digitized (128 Hz, 12 bit) with a
Holter scanner (DMC-4100, Nihon Koden). The ECG lead with the least
distinct f-wave relative to R-wave height was selected for detecting
and labeling QRS complexes. The results were reviewed, and all errors
were edited manually. Data were transferred to a supercomputer
(S-7/7000U, Fujitsu), on which VRI dynamics were analyzed. The
detailed procedure has been reported elsewhere.7
To characterize the 24-hour VRI dynamics, several measures were used;
they are defined in Table 1
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Variability and irregularity represent different properties of
VRI dynamics (Figure 1). The variability
measures (SD [SDVRI], SD of successive differences [SDDVRI], and SD
of 5-minute averages [SDAVRI]) quantify the magnitude of
deviation from the mean. The irregularity measures (Shannon entropy of
histogram [ShEn], symbolic dynamics [SymDyn], and approximate
entropy of beat-to-beat and minute-to-minute fluctuations
[ApEnb-b and ApEnm-m])
quantify the intrinsic unpredictability (unlikelihood of the
reappearance of similar patterns). Analyses of
representative patients are presented in Figure 2.
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Statistical Analysis
We used an SAS program (SAS Institute)12 for
statistical analysis. Differences in quantitative and
categorical data were evaluated by Student’s t tests and
2 tests with Yates’ correction, respectively,
and relationships between quantitative variables were assessed by
Spearman’s rank correlation analysis. A Cox proportional
hazards regression model was used for survival analysis. To
remove the impact of conditions with a high fatality rate, patients who
died within 2 months of follow-up were excluded. The independent
prognostic value of VRI measures was determined by
multivariate Cox models that included clinical
variables with a significant univariate association.
The best predictive model was made with step-wise variable
selection in which P=0.05 was used for entering and
removing a variable. Kaplan-Meier survival curves were calculated
for patients stratified by VRI measures into high, middle, and low
tertiles. Quantitative data were expressed as the mean±SD, and risk
for death was expressed as relative risk (RR) and 95% confidence
interval (CI). P<0.05 was considered significant.
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Results |
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Clinical Characteristics
The duration of follow-up ranged from 12 to 67 months (mean, 33±16 months) for surviving patients. During the follow-up, 19 patients (18%) died; 9 died from cardiac causes (5 of progressive heart failure and 4 of sudden cardiac death), 8 from fatal strokes (7 infarctions and 1 bleeding), and 2 from malignancies. One fatal stroke occurred within 2 months of measurement, and this patient was excluded from further analysis. The mean age of the remaining 107 patients was 64±9 years at entry; 28 of them (26%) were female. The duration of chronic AF was 8.8±7.3 years. The cause of AF was idiopathic in 50 patients (47%), valvular in 33 patients (31%), and nonvalvular in 24 patients (22%). The survival duration of the 18 nonsurvivors ranged from 3 to 67 months (mean, 27±21 months).
Idiopathic AF was less frequent in the patients who died from fatal
stroke and from all causes than in the surviving patients (Table 2). Nonvalvular AF, particularly
ischemic AF, was less common in the survivors than in the
nonsurvivors. The survivors and nonsurvivors did not differ in age,
sex, duration of AF, left ventricular ejection fraction,
left atrial diameter, or medication, except for warfarin, which had
been prescribed more often in those who died from fatal stroke.
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Although mean VRI did not differ significantly between the survivors
and nonsurvivors, all variability measures (SDVRI, SDDVRI, and SDAVRI)
and one irregularity measure (ApEnm-m) were lower
in the patients who died from cardiac causes than in the surviving
patients (Table 3). No such differences
were observed between the patients who died of fatal stroke and the
surviving patients.
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In the entire patient population, close mutual correlations were
observed among variability measures and some irregularity measures
(ShEn and ApEnm-m), whereas other irregularity
measures (SymDyn and ApEnb-b) were relatively
independent (Table 4). SDVRI, SDAVRI, and
ShEn correlated positively with left ventricular ejection
fraction, and all VRI measures except ApEnb-b
correlated with left atrial diameter. Except for SDAVRI, which was
greater in female patients, none of the measures was associated with
age, sex, duration of AF, or medication (digoxin, diuretics,
calcium antagonists, or angiotensin-converting
enzyme inhibitors).
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Survival Analysis
Reductions in all VRI measures showed a significant
univariate association with the risk for cardiac death
(Table 5). All irregularity measures
except ApEnm-m were also univariate
predictors of all-cause death, but none of the measures predicted fatal
stroke. Among clinical variables, left ventricular
ejection fraction was a univariate predictor of cardiac
death (RR, 1.10; 95% CI, 1.04 to 1.17, per 1% decrement) and, in
ischemic AF, it was a predictor of cardiac and all-cause death
(RRs, 6.52 and 7.54; 95% CIs, 1.62 to 26.3 and 2.74 to 20.7,
respectively). No predictive value was observed for AF duration, left
atrial diameter, or medication at baseline.
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Even after adjusting for left ventricular ejection fraction
and ischemic AF, all irregularity measures except SymDyn had a
predictive value for cardiac death; however, after adjustment, the
predictive power of variability measures was no longer significant for
any cause of death (Table 5
). Multivariate Cox
regression with step-wise model building revealed that the risk for
cardiac death was best predicted by left ventricular
ejection fraction (RR, 1.08; 95% CI, 1.01 to 1.16, per 1% decrement)
and ApEnb-b (RR, 1.75; 95% CI, 1.13 to 2.71, per
1SD decrement) and that all-cause death was best predicted by
ischemic AF (RR, 14.2; 95% CI, 3.76 to 53.6) and ShEn (RR,
1.65; 95% CI, 1.10 to 2.47, per 1-SD decrement). No significant
predictive model was obtained for fatal stroke.
Finally, we stratified patients into tertiles using the 33rd and 67th
percentile values of ApEnb-b (1.83 and 1.94,
respectively). A Kaplan-Meier plot for cardiac death revealed that
5-year cardiac mortality rates for the upper, middle, and lower
tertiles were 0%, 13%, and 43%, respectively (Figure 3; log-rank test, P=0.04).
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Discussion |
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Major Findings
To our knowledge, this is the first study to examine the prognostic value of VRI irregularity in patients with chronic AF. Even after adjustments for coexisting cardiovascular conditions, VRI irregularity (as assessed by entropy measures) was a significant predictor of cardiac death, but mean VRI and VRI variability had no independent prognostic value.
Previous Studies
Stein et al2 examined 24-hour VRI variability in 21
patients with chronic AF due to nonischemic mitral
regurgitation. During a 5.2-year follow-up, 5 patients
died of cardiac causes and 8 underwent mitral valve replacement
surgery. Although none of the measures predicted mortality, the authors
observed a univariate association between reduced SDAVRI
and combined risk (mortality and mitral valve surgery). Frey et
al3 also examined 24-hour VRI variability in 35 patients
with chronic AF and advanced heart failure. During a 12-month
follow-up, 8 patients clinically deteriorated (3 died and 5 underwent
heart transplantation). They reported that reduced SDAVRI was the only
independent predictor of event-free survival. In the present study,
we failed to find an independent predictive value of SDAVRI. Although
this may be due to the heterogeneity of our patient
population, we did find that 24-hour VRI fluctuation had an angular
spectral structure with a distinct breakpoint in the frequency range
reflected by SDAVRI, which may cause instability in this
measure.7
Prognostic Relevance of VRI Dynamics
Although our observations suggest that important prognostic
information is more likely to exist in irregularity than variability
measures of VRI, one of the irregularity measures (SymDyn) had no
independent prognostic value. In the algorithm for SymDyn, the
resolution of analysis (symbol separation) was defined as the
24-hour SD of VRI in each patient. The larger the VRI variability, the
lower the resolution, which resulted in relative insensitivity to small
changes in VRI. However, ApEnb-b and
ApEnm-m were computed with a fixed resolution
(tolerance value [r] for vector comparison) for all patients, and
ShEn was calculated with the same resolution as VRI measurement. These
findings suggest that prognostic information may exist in fine (low
amplitude) VRI irregularity. Indeed, ApEnb-b and
ApEnm-m, which were computed with a tolerance
normalized by individual VRI variability (20% of individual SD), had
no significant predictive value (data not shown).
Possible Mechanisms
Because of the observational nature of the present study, it
is difficult to determine whether decreased VRI irregularity is a part
of the mechanisms of increased mortality in patients with chronic AF or
if it is merely a marker of poor prognosis among them. However, VRI
irregularity had prognostic value for cardiac death but not fatal
stroke, which indicates that the association between irregularity and
mortality is unattributable to the potential effect of VRI
irregularity on atrial thrombogenesis. Also, the prognostic value of
these measures was independent of both left ventricular
ejection fraction and origin of AF. Thus, these findings are not a
simple reflection of poor ventricular performance
or the characteristics of known cardiac diseases, although we cannot
exclude the possibility that reduced VRI irregularity identifies
patients with other unmeasured differences in disease severity that
themselves influence survival in this population.
Multivariate Cox models revealed the best independent predictive value was with beat-to-beat VRI irregularity (ApEnb-b). ApEnb-b could be modified by many factors. Atrial expansion and, thereby, induced reflex vagal excitation may increase the dispersion of atrial refractoriness and VRI irregularity.13 14 15 The atrial electrical remodeling induced by AF itself16 may shorten atrial refractoriness, thereby increasing the number and frequency of f-waves, which could increase VRI irregularity by enhancing concealed conduction within the atrioventricular node.15 17 Although atrial expansion and electrical remodeling might progress as a pathological process of chronic AF, we observed that neither left atrial diameter nor the duration of chronic AF had prognostic value; furthermore, these factors, if involved, would increase VRI irregularity. Much evidence from HRV analysis during sinus rhythm suggests an adverse prognostic value of decreased vagal activity in cardiac patients.18 19 20 Decreased vagal activity may prolong atrial refractoriness and reduce its dispersion,13 resulting in reduced VRI irregularity.15 21 These factors suggest that vagal dysfunction is the most likely mediator of the association between reduced beat-to-beat VRI irregularity and cardiac mortality, although this attractive hypothesis deserves further study.
Limitations
We collected VRI data from patients under medication. We cannot
exclude the possible influence of such medication on VRI dynamics,
although we observed no significant associations of any drug with any
VRI measure or prognosis. We must consider the possible effects of
clinical decisions made for the patients during the follow-up. However,
the end point of this study was simply death, and the patients were
managed as recommended by recent standards.22 Thus, our
observations seem to reflect current general practice. Our patient
population, however, was heterogenous in the origin of
chronic AF, although the prognostic value of VRI irregularity was
independent of AF pathogenesis. Our observations may not be directly
applicable to other populations with different AF origins. Finally, as
a technical issue, the presence of the f-wave may have affected the
precision of R-R interval measurement by distorting the R-wave forms.
However, we selected the ECG lead with the least distinct f-wave. Also,
the measures derived from average VRI values, SDAVRI, and
ApEnm-m, were less influenced by the effect, and
ApEnb-b was guarded from this because the
tolerance for vector comparison (r) was set at 43 ms, indicating that 2
VRIs were considered identical unless they differed >43 ms. However,
the other measures may have been influenced, which then might have
deteriorated their prognostic value.
Clinical Implications
The prognostic implications of chronic AF are serious, even beyond
the increased risk for thromboembolic events.23 Growing
evidence indicates that, in patients with heart failure, those with AF
have excess mortality when compared with those who have sinus
rhythm24 25 ; the same holds true for patients after
myocardial infarction.26 27 A recent report on the
Framingham cohort indicated that AF was associated with a 1.5- to
1.9-fold increased risk of mortality, even after adjustment for
preexisting cardiovascular conditions.28
Given the recent progress in pharmacological and nonpharmacological
treatments for AF, risk stratification for mortality in these patients
seems increasingly important. The analysis of VRI irregularity
is applicable to routine ambulatory ECG recordings in almost
all patients with chronic AF. Our method may add unique clinical
information for identifying patients with an adverse prognosis,
particularly those with an increased risk for cardiac death.
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Acknowledgments |
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This work was supported by a Grant-in-Aid for Scientific Research from the Ministry of Education, Science, Sports, and Culture of Japan (11670698; to Dr Hayano), a Grant-in-Aid for Research from Nagoya City University (1999; to Dr Hayano), and a Research Grant from Pfizer Health Research Foundation (99A052; to Dr Hayano).
Received October 6, 1999; revision received February 1, 2000; accepted February 14, 2000.
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References |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. Camm AJ, Malik M, Bigger JT Jr, et al. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Circulation. 1996;93:1043–1065.
2. Stein KM, Borer JS, Hochreiter C, et al. Variability of the ventricular response in atrial fibrillation and prognosis in chronic nonischemic mitral regurgitation. Am J Cardiol. 1994;74:906–911.[Medline] [Order article via Infotrieve]
3. Frey B, Heinz G, Binder T, et al. Diurnal variation of ventricular response to atrial fibrillation in patients with advanced heart failure. Am Heart J. 1995;129:58–65.[Medline] [Order article via Infotrieve]
4.
Pincus SM, Goldberger AL.
Physiological time-series analysis: what
does regularity quantify. Am J Physiol. 1994;266:H1643–H1656.
5. Voss A, Kurths J, Kleiner HJ, et al. The application of methods of non-linear dynamics for the improved and predictive recognition of patients threatened by sudden cardiac death. Cardiovasc Res. 1996;31:419–433.[Medline] [Order article via Infotrieve]
6.
Ho KKL, Moody GB, Peng CK, et al. Predicting survival
in heart failure case and control subjects by use of fully automated
methods for deriving nonlinear and conventional indices of heart rate
dynamics. Circulation. 1997;96:842–848.
7.
Hayano J, Yamasaki F, Sakata S, et al. Spectral
characteristics of ventricular response to atrial
fibrillation. Am J Physiol. 1997;273:H2811–H2816.
8. Voss A, Hnatkova K, Wessel N, et al. Multiparametric analysis of heart rate variability used for risk stratification among survivors of acute myocardial infarction. Pacing Clin Electrophysiol. 1998;21:186–192.[Medline] [Order article via Infotrieve]
9.
Palazzolo JA, Estafanous FG, Murray PA. Entropy
measures of heart rate variation in conscious dogs. Am J
Physiol. 1998;274:H1099–H1105.
10.
Pincus SM. Approximate entropy as a measure of system
complexity. Proc Natl Acad Sci U S A. 1991;88:2297–2301.
11. Pincus SM, Gladstone IM, Ehrenkkranz RA. A regularity statistic for medical data analysis. J Clin Monit. 1991;7:335–345.[Medline] [Order article via Infotrieve]
12. SAS/STAT User’s Guide. Version 6. Cary, NC: SAS Institute; 1990.
13.
Ninomiya I. Direct evidence of nonuniform distribution
of vagal effects on dog atria. Circ Res. 1966;19:576–583.
14. Kaseda S, Zipes DP. Contraction-excitation feedback in the atria: a cause of changes in refractoriness. J Am Coll Cardiol. 1988;11:1327–1336.[Abstract]
15.
Chorro FJ, Kirchhof CJHJ, Brugada J, et al.
Ventricular response during irregular atrial pacing and
atrial fibrillation. Am J Physiol. 1990;259:H1015–H1021.
16.
Daoud E, Bogun F, Goyal R, et al. Effects of atrial
fibrillation on atrial refractoriness in human. Circulation. 1996;94:1600–1616.
17.
Langendorf R, Pick A, Katz LN. Ventricular
response in atrial fibrillation: role of concealed conduction in the AV
junction. Circulation. 1965;32:69–75.
18. Kleiger RE, Miller JP, Bigger JT Jr, et al, for the Multicenter Post-Infarction Research Group. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol. 1987;59:256–262.[Medline] [Order article via Infotrieve]
19. Brouwer J, Van Veldhuisen DJ, Veld AJMI, et al. Prognostic value of heart rate variability during long-term follow-up in patients with mild to moderate heart failure. J Am Coll Cardiol. 1996;28:1183–1189.[Abstract]
20.
Nolan J, Batin PD, Andrews R, et al. Prospective study
of heart rate variability and mortality in chronic heart failure:
results of the United Kingdom heart failure evaluation and assessment
of risk trial (UK- Heart). Circulation. 1998;98:1510–1516.
21. Van den Berg MP, Crijns HJGM, Haaksma J, et al. Analysis of vagal effects on ventricular rhythm in patients with atrial fibrillation. Clin Sci. 1994;86:531–535.[Medline] [Order article via Infotrieve]
22. Narayan SM, Cain ME, Smith JM. Atrial fibrillation. Lancet. 1997;350:943–950.[Medline] [Order article via Infotrieve]
23. Giardina EGV. Atrial fibrillation and stroke: elucidating a newly discovered risk factor. Am J Cardiol. 1997;80(suppl 4C):11D–18D.
24.
Middlekauff HR, Stevenson WG, Stevenson LW. Prognostic
significance of atrial fibrillation in advanced heart failure: a study
of 390 patients. Circulation. 1991;84:40–48.
25.
Dries DL, Exner DV, Gersh BJ, et al. Atrial
fibrillation is associated with an increased risk for mortality and
heart failure progression in patients with asymptomatic and
symptomatic left ventricular systolic
dysfunction: a retrospective analysis of the SOLVD trials.
J Am Coll Cardiol. 1998;32:695–703.
26. Grenshaw BS, Ward SR, Granger CB, et al, for the GUSTO-I Trial Investigators. Atrial fibrillation in the seting of acute myocardial infarction: the GUSTO-I experience. J Am Coll Cardiol. 1997;30:406–413.[Abstract]
27. Sakata K, Kurihara H, Iwamori K, et al. Clinical and prognostic significance of atrial fibrillation in acute myocardial infarction. Am J Cardiol. 1997;80:1522–1527.[Medline] [Order article via Infotrieve]
28.
Benjamin EJ, Wolf PA, D’Agostino RB, et al. Impact of
atrial fibrillation on the risk of death: the Framingham Heart Study.
Circulation. 1998;98:946–952.
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