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European Journal of Heart Failure 2000 2(3):265-271; doi:10.1016/S1388-9842(00)00065-9
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© 2000 European Society of Cardiology

QT interval lengthening in cardiac disease relates more to left ventricular systolic dysfunction than to autonomic function

Patrick Davey*

Department of Cardiovascular Medicine, John Radcliffe Hospital Oxford OX3 9DU, UK


   Abstract
Top
 Notes
 Abstract
1. Introduction
 2. Hypothesis
 3. Methods
 4. Results
 5. Discussion
 6. Conclusion
 References
 
Background: There are multiple influences on the QTc interval, including the autonomic nervous system. Which influence is the principal determinant of the variation in QTc interval between different cardiac diseases is not yet clear, though some studies have suggested that the QTc interval primarily reflects sympatho-vagal balance. This study investigated this claim further.

Aim: To determine if autonomic tone was the prime determinant of variation in the QTc interval between subjects with different cardiac diseases.

Methods: Subjects with different cardiac diseases were studied, QTc interval determined and correlated with three different measures of the autonomic nervous system, that of baroreflex sensitivity, catecholamine levels (epinephrine and norepinephrine) and sympatho-vagal balance as determined by power spectrum analysis.

Results: 47 subjects were studied, comprising 17 subjects with heart failure, 14 subjects with left ventricular hypertrophy and 16 control subjects. For the group as a whole there was no relationship between QTc interval and any measure of the autonomic nervous system function, but there was a reasonable relationship between fractional shortening and QTc interval (r = 0.47, P < 0.003). For subjects with an echocardiographic fractional shortenings less than 0.35 (which correlates with an ejection fraction of < 50%), a strong relationship between fractional shortening and QTc interval remained (r = 0.57, P < 0.002), but in addition a relationship between QTc interval and catecholamine levels developed (for epinephrine: r = 0.67, P < 0.002; and for norepinephrine: r = 0.62, P < 0.005). Multiple regression analysis showed that fractional shortening and epinephrine levels were independently related to QTc interval.

Conclusion: In subjects with a variety of cardiac diseases, the prime determinant of QTc interval is left ventricular systolic performance rather than the autonomic nervous system, though in subjects with low normal and less fractional shortenings catecholamine levels are independently related to QTc interval.

Received February 12, 1999; Revised January 19, 2000; Accepted February 16, 2000


   1. Introduction
Top
 Notes
 Abstract
 1. Introduction
2. Hypothesis
 3. Methods
 4. Results
 5. Discussion
 6. Conclusion
 References
 
The duration of the QT interval varies with age, sex, cardiac and non-cardiac disease (such as sub-arachnoid haemorrhage), haemodynamic status, nutritional status, with different drugs and in response to a number of other factors, such as diabetic autonomic neuropathy and chronic liver disease [1–9]. In addition the autonomic nervous system has a powerful influence on the QT interval [10,11]. However, of all of these factors influencing the QT interval, which one is in practice the most important has not yet been determined. It is possible that physiologically the most important influence is the state of the autonomic nervous system, and that some, or even most, of the pathological influences on the QT interval operate through derangements in autonomic nervous system function, though this is not as yet clear. Despite there being no clear evidence some authors have suggested that not only is the autonomic nervous system the most important influence, but that one particular marker of autonomic nervous system function, that of sympatho-vagal balance, is the prime factor determining QT interval duration, and thus the ‘QT interval is a marker of sympatho-vagal balance’ [12]. This paper investigates this claim more fully, and in particular examines whether differences in the QT interval between individuals with different cardiac diseases are principally due to differences in autonomic tone. The cardiac diseases studied were heart failure, where the QT interval is known to be prolonged and left ventricular hypertrophy, as animal models of hypertrophy are associated with prolongation of the duration of the action potential, thus suggesting that QT interval prolongation should also be found [13–15]. This study sought to determine if QT interval prolongation in these two common cardiac conditions related to the autonomic nervous system.


   2. Hypothesis
Top
 Notes
 Abstract
 1. Introduction
 2. Hypothesis
3. Methods
 4. Results
 5. Discussion
 6. Conclusion
 References
 
The aim of the experiments was to test the hypothesis that autonomic tone was the prime determinant of variation in the QTc interval between subjects with different cardiac diseases.


   3. Methods
Top
 Notes
 Abstract
 1. Introduction
 2. Hypothesis
 3. Methods
4. Results
 5. Discussion
 6. Conclusion
 References
 
Subjects expected to have different QTc intervals were recruited, and their QTc intervals measured. Several different measures of the autonomic nervous system were determined. Correlation between QTc interval and markers of the autonomic nervous system was then carried out using linear regression analysis.

3.1. Subjects
Three patient groups were recruited, comprising those with heart failure, left ventricular hypertrophy and a control group. All subjects underwent echocardiography using a Hewlett Packard SONOS 2000, and standard measurements of internal dimensions at end systole (LVIDs) and diastole (LVIDd), septal and posterior wall thickness were made. Fractional shortening was defined as (LVIDd–LVIDs)/(LVIDd). LV mass was derived using standard formula [16]. Heart failure was defined as typical symptoms with echocardiographic evidence of left ventricular systolic dysfunction. Left ventricular hypertrophy was defined echocardiographically by an increase in left ventricular mass with normal left ventricular systolic function [16]. The hypertrophy population were by definition not allowed to have any symptoms of heart failure. An age matched control population was also recruited. All patients were in sinus rhythm, did not have any condition known to affect the QT interval (including diabetes or thyroid disease) and, as diuretics and ACE inhibitors were the only drugs allowed, were not on any drugs known to affect the QT interval (including digoxin and β-blockers). There was no symptomatic or exercise ECG evidence of ongoing myocardial ischaemia, and all significant valve lesions had been dealt with by surgery.

3.2. QT interval measurement
QT interval was measured after subjects had been supine for 30 min in a quiet and darkened room, using high-speed and high-gain 12-lead electrocardiogams (ECGs) (50 mm/s and 20 mm/mV) obtained from the CASE 15 ECG machine (from MarquetteTM instruments). The QT interval from each individual lead was obtained using a digitising tablet, and the mean QT interval was then derived from the 12 leads of the ECG. This mean QT interval was then used in subsequent analysis. In five patients repeat QT interval measurements were made after 1 week. These differed by (mean±S.D.) 0.4±2.4% of the day 1 QT interval.

3.3. Autonomic function tests
A variety of measures of autonomic function were obtained. As a study in subjects with cardiac transplants suggested that the major influence on the QT interval may be circulating catecholamines, the level of circulating catecholamines was measured [17]. Plasma levels of epinephrine and norepinephrine were determined after subjects had been supine for 30 min in a quiet and darkened room, by obtaining venous blood from hand veins, after prewarming. Samples were immediately frozen to –20°C for subsequent analysis. Batch processing occurred later, and catecholamine levels were obtained from a previously validated set-up using the HPLC technique [18].

Baroreflex sensitivity (BRS), a measure of vagal function, was obtained using the phenylephrine pressor technique, in which blood pressure is transiently elevated (by approx. 20 mmHg) using an intravenous bolus of phenylephrine and the reflex bradycardic response of the heart measured. The RR interval is plotted out against systolic blood pressure during the phenylephrine bolus, and the slope of this relationship obtained from a least squares linear regression analysis computer program. The slope of the change in heart rate against the change in systolic blood pressure is the baroreflex sensitivity (BRS) [19]. BRS was determined on four separate occasions and the mean value used.

Sympatho-vagal balance was determined from power-spectrum analysis [20]. Subjects were allowed to rest in a darkened room for at least 20 min. Continuous ECG recordings were made after this time period, using an ECG lead with the best developed R wave, and the data stored on FM tape, using a RACAL tape recorder, for later analysis. Power spectrum analysis was then carried out according to standard methodology, using a previously validated interactive computer program that had been originally developed in our laboratory [20–22]. The data obtained on heart rate variability was broken down into very low (VLF≤0.04 Hz), low (LF 0.04–0.15 Hz) and high frequency (HF 0.15–0.4 Hz) bands. The high frequency component of the spectrum relates to respiratory sinus arrhythmia, and may reflect vagal outflow to the heart, whereas the low frequency component of the power spectrum may relate to sympathetic outflow to the heart [23]. The data are presented in a number of ways. The absolute value of power is presented and the LF and HF components are also presented in normalised units, which is the relative value of each power component in proportion to the total power minus the VLF component. To correct for overall changes in heart rate variability as opposed to specific changes in the magnitude of each component it is usual to quote the sympatho-vagal balance as a ratio of high to the low frequency power, and this was done here.


   4. Results
Top
 Notes
 Abstract
 1. Introduction
 2. Hypothesis
 3. Methods
 4. Results
5. Discussion
 6. Conclusion
 References
 
4.1. Basic data
Subjects were recruited after informed consent and with local ethical committee approval. A total of 47 subjects were studied, of whom 16 were controls, 14 had left ventricular hypertrophy and 17 had heart failure. The basic data (mean±standard error) on the subjects are shown in Table 1, where it can be seen that heart failure subjects had depressed fractional shortening, and subjects with left ventricular hypertrophy had increased left ventricular mass. Exercise capacity was depressed in the heart failure group, as was peak oxygen uptake. VPC count over 24 h was increased in both the left ventricular hypertrophy group and in the heart failure group. The non-heart rate variability related autonomic tests showed the expected derangement with heart failure patients having increases in resting norepinephrine, though resting epinephrine levels were not raised. Baroreflex sensitivity was markedly depressed in the heart failure group (Table 2). The data on power spectrum analysis are shown in Table 3. Due to ectopy, power spectrum analysis was only possible in selected cases: those in whom analysis was possible did not have any different degree of ventricular impairment or QTc interval from those in whom analysis was possible. Though there was statistically no difference between the three groups in low or high frequency total power, there was a non-significant trend towards the heart failure group having less heart rate variability. There was no significant difference between the high/low frequency ratio between the three groups.


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  		Table 1 Demographic data on subjectsa

 


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  		Table 2 Catecholamines and baroreflex sensitivitya

 


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  		Table 3 Power spectrum measuresa

 
4.2. Relation between autonomic function tests and QTc interval
Using simple linear regression analysis the correlation between each of the autonomic function tests and the QTc interval was determined (Table 4). For the group as a whole there was a reasonable relationship (r=0.47, P<0.003) between fractional shortening and mean QTc interval (Fig. 1), but there was no relationship between any of the markers of autonomic nervous system function and QTc interval.


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  		Table 4 Relationship between mean QT interval and autonomic function tests for the entire group

 


Figure 1
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  		Fig. 1 The relationship between QTc interval and fractional shortening. This graph shows data for the population as a whole, with fractional shortening plotted out against QTc interval. Using linear regression analysis there is a significant relationship between these two variables, with r=0.47, P<0.003.

 
When the graph of fractional shortening against QTc interval was examined more closely there appeared to be two relationships present (Fig. 2). At values of fractional shortening greater than approximately 0.35 (which in our institute correlates with an MUGA ejection fraction of approx. 50%) there appeared to be no relationship between mechanical function and QTc interval, whereas at values of fractional shortening less than this there appeared to be rather a steep relationship. This hypothesis was supported by further analysis. Using simple linear regression analysis, at values of fractional shortening greater than 0.35, there was no relationship between QTc interval and with either fractional shortening or any of the markers of autonomic function. However, at values of fractional shortening of less than 0.35 there was a highly significant relationship between QTc interval and fractional shortening (Table 5). Interestingly, at fractional shortenings of less than 0.35, a highly significant relationship now developed between QTc interval and levels of either epinephrine or norepinephrine, as shown in Table 5. Multiple regression analysis shows that, at these lower levels of fractional shortening, only epinephrine and fractional shortening were independently related to the QTc interval, with a P<0.04 for fractional shortening and P<0.02 for epinephrine and that these two measures together accounted for 64% of the variability of the QTc interval. Norepinephrine levels did not add further to the correlation as norepinephrine and epinephrine levels were very closely related to each other (r=0.52, P<0.009).


Figure 2
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  		Fig. 2 The relationship between QTc interval and fractional shortening-evidence for a threshold effect. This graph is the same as in Fig. 1, though here two relationships between QTc interval and fractional shortening are seen. For fractional shortenings greater than 0.35, no relationship is present between QTc interval and fractional shortening, whereas for fractional shortenings less than 0.35 a reasonably strong relationship is present.

 


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  		Table 5 Relationship between autonomic and mechanical variables in those with fractional shortenings less than 0.35

 

   5. Discussion
Top
 Notes
 Abstract
 1. Introduction
 2. Hypothesis
 3. Methods
 4. Results
 5. Discussion
6. Conclusion
 References
 
This small study looking at subjects with different cardiac diseases examined the hypothesis that QTc interval was primarily a marker of sympathovagal balance, as has been proposed previously [12]. No correlation was found between three different markers of autonomic nervous system function, baroreflex sensitivity, catecholamine status and in particular different measures derived from power spectrum analysis and the QTc interval when the group as a whole were studied. Accordingly the hypothesis that QTc interval across populations, and in particular between subjects with differing cardiac disease, is primarily determined by sympatho-vagal balance is not supported by this data.

That the autonomic nervous system can have substantial influence on the QTc interval is beyond doubt. The overall action of the autonomic nervous system appears to be to shorten the QTc interval: if the influence of the autonomic nervous system is removed, as it is in subjects with primary autonomic failure then the QTc interval is prolonged [24,25]. Consistent with this data is the finding that exogenous catecholamines (>30 s) shorten and β-blockers usually lengthen the QTc interval. [26–28]. Acute removal of cardiac vagal tone with atropine can substantially lengthen the QTc interval (in one study, 410–454 ms), whereas chronic age related decline in baroreflex function is associated with a prolongation of the QTc interval [1,29]. The diurnal variation of the QTc interval interestingly may relate mainly to enhanced sympathetic tone during the day rather than increased vagal tone at night [30].

In some diseases such as primary biliary cirrhosis there does appear to be substantial evidence that QT interval lengthening relates directly to altered autonomic function [8,31]. Most, though not all, investigators have found similar results in insulin dependent diabetes [32–34]. However, the data relating QTc interval abnormalities directly to autonomic dysfunction in cardiac disease are have produced variable results and this study adds to these previous findings. Why is this? There are several interpretations. The first is that spectral analysis does not relate to autonomic inflow to the heart and thus these findings are spurious. This seems unlikely as there is substantial data that spectral analysis, at least in subjects at rest, while differing from other autonomic tests, does reflect cardiac autonomic status (for review see Malliani et al. [35]). The second interpretation is that QTc interval across populations of patients with cardiac disease, rather than being related to sympatho-vagal balance, is intimately related to the mechanical performance of the heart. Thus it appears that factors very closely associated with left ventricular systolic performance are the primary determinants of QTc interval across populations rather than derangements in autonomic nervous system function.

Within segments of the population examined here this study did find evidence that the autonomic nervous system may have an important role. In those with fractional shortenings less than 0.35, which corresponds to an ejection fraction of approximately 0.50 (i.e. at the low end of the normal range), not only was fractional shortening powerfully related to QT interval, but in addition for this restricted portion of the total population, catecholamine levels (either epinephrine levels or norepinephrine levels, though not both as they are related to each other) were related independent of fractional shortening to QTc interval. Thus in those subjects who have the greatest variation from normal in the QT interval, catecholamines may determine part of this variation. This finding may go some way to explaining the association between QTc prolongation post myocardial infarction and subsequent prognosis, given the known association between neuro-endocrine activation in heart failure and subsequent outlook [36,37]. Thus in this restricted segment of the population QTc interval may be associated with high levels of catecholamines, and thus be a surrogate marker for neuro-endocrine activation.

The positive association between high plasma levels of catecholamine levels and prolongation of the QT interval is perhaps a surprising finding, as exogenous catecholamines shorten the QT interval and as β-blockers, at rest, lengthen the QT interval [27,38]. However, prolonged β-receptor stimulation down-regulates β-receptor and second messenger systems, which may alter QT interval in much the same way that autonomic failure does [24,25,39]. In this context it is perhaps interesting to note that β-blockers in syndrome X appear to shorten the prolonged QT interval found here, perhaps by antagonising the effects of elevated levels of catecholamines [40]. Accordingly it is possible that the finding of a relationship between QTc interval and catecholamine levels reflects a genuine association, though it is, however, also possible that this finding is a surrogate for another relationship that was not found.


   6. Conclusion
Top
 Notes
 Abstract
 1. Introduction
 2. Hypothesis
 3. Methods
 4. Results
 5. Discussion
 6. Conclusion
References
 
This study examined the hypothesis that the primary determinant of QTc prolongation was autonomic nervous system function and in particular alterations in sympatho-vagal balance. This study did not find evidence to support this assertion in the generality of cardiac disease. Rather this study suggested that the primary determinant of QT interval duration was the systolic contractile function of the left ventricle. In subjects with low normal or lower ejection fractions a relationship independent of contractile function was found between QT prolongation and elevations in resting catecholamine levels.


   Notes
Top
 Notes
Abstract
 1. Introduction
 2. Hypothesis
 3. Methods
 4. Results
 5. Discussion
 6. Conclusion
 References
 
* Tel.: +44-1865-741166; fax: +44-1865-220252. E-mail address: patrick.davey{at}ndm.ox.ac.uk (P. Davey). Back


   References
Top
 Notes
 Abstract
 1. Introduction
 2. Hypothesis
 3. Methods
 4. Results
 5. Discussion
 6. Conclusion
 References
 

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