European Heart Journal Advance Access originally published online on November 13, 2006
European Heart Journal 2007 28(11):1344-1350; doi:10.1093/eurheartj/ehl367
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QT variability strongly predicts sudden cardiac death in asymptomatic subjects with mild or moderate left ventricular systolic dysfunction: a prospective study
1 Dipartimento di Scienze dell'Invecchiamento, I Clinica Medica, Policlinico Umberto I, Università ‘La Sapienza’, Viale del Policlinico, 00161 Rome, Italy
2 Dipartimento del Cuore e Grandi Vasi ‘Attilio Reale’, Policlinico Umberto I, Università ‘La Sapienza’, Rome, Italy
Received 8 October 2006; revised 13 October 2006; accepted 19 October 2006; online publish-ahead-of-print 13 November 2006.
* Corresponding author. Tel: +39 064463301 2 3; fax: +39 064940594. E-mail address: gianfranco.piccirillo{at}uniroma1.it
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Abstract |
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Aims: The most widely accepted marker for stratifying the risk of sudden cardiac death (SCD) in post myocardial infarction patients is a depressed left ventricular function. Left ventricular ejection fractions (EF) of 35% or less increase the risk of sudden death but values between 35 and 40% raise concern. The underlying pathophysiological mechanism is sustained ventricular tachycardia or fibrillation, both associated with increased cardiac repolarization variability. We assessed whether the indices of QT variability from a short-term electrocardiographic (ECG) recording predict sudden death.
Methods and results: A total of 396 subjects with chronic heart failure (CHF) due to post-ischaemic cardiomyopathy, with an EF between 35 and 40% and in NYHA class I, underwent a 5 min ECG recording to calculate the following variables: QT variance (QTv), QT normalized for the square of the mean QT (QTVN), and QT variability index (QTVI). Corrected QT (QTc) was calculated from a 12-lead ECG recording. All participants were followed for 5 years. A multivariable survival model indicated that a QTVI greater than or equal to the 80th percentile indicated a high risk of SCD [hazards ratio (HR) 4.6, 95% confidence interval (CI) 1.5–13.4, P = 0.006] and, though to a lesser extent, a high risk of total mortality (HR 2.4, 95% CI 1.2–4.9, P = 0.017). The model including QTVI as a continuous variable confirmed a similar high risk for SCD (HR 2.9, 95% CI 1.3–6.5, P = 0.01) and for total mortality (HR 2.6, 95% CI 1.3–5.2, P = 0.008).
Conclusion: Although asymptomatic patients with CHF who have a slightly depressed EF are at low risk of sudden death, the category is extraordinarily numerous. The QTVI could be helpful in stratifying the risk of sudden death in this otherwise undertreated population.
Key Words: QT dynamic • QT variability • Chronic heart failure • Sudden cardiac death • Autonomic nervous system
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Introduction |
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Chronic heart failure (CHF) secondary to post-ischaemic dilated cardiomyopathy is among the major risk factors for sudden cardiac death (SCD) from arrhythmia. The guidelines issued by the American College of Cardiology/American Heart Association (ACC/AHA)1 and European Society of Cardiology2 based upon clinical trials such as the first and second Multicentre Automatic Defibrillator Implantation Trials (MADIT I-II),3,4 the Multicentre Unsustained Tachycardia Trial (MUSTT),5 and the Sudden Death in Heart Failure Trial (SCD-HeFT),6,7 recognize a low ejection fraction (EF) (
30–35%) as a major predictor of SCD. Hence under these conditions they recommend use of an implantable cardioverter defibrillator (ICD). These recommendations notwithstanding no published evidence yet proves the real benefit of implanting an ICD in patients who have a moderately depressed EF (>35 and 40%) and are asymptomatic for CHF, namely the New York Heart Association (NYHA) functional class I or stage B (ACC/AHA),1 whereas patients with an EF between 32 and 42% have a sizeable mortality rate estimated at around 2.8% per year.8,9 A MADIT II substudy10 also showed that a level higher than or equal to the 70th percentile of the QT variability index (QTVI) and QT variance indexed for the square of the mean QT interval length (QTVN) is independently associated with ventricular tachycardia or fibrillation in patients implanted with an ICD. Others reported a higher QTVI in patients at high risk of sudden death11 or in those implanted with an ICD for secondary prophylaxis of malignant ventricular arrhythmias,12 and the QTVI increased as the NYHA functional class became more severe.13
More information is therefore needed on QT variables as predictors of SCD, especially in patients with asymptomatic CHF and moderately depressed EF who might benefit from prophylactic therapy with an ICD.
We therefore undertook this prospective study in a single centre to determine whether the QTVI and QTVN were predictors of SCD in a study sample of outpatients with post-ischaemic dilated cardiomyopathy who had a moderately depressed EF and no symptoms of CHF when the study began.
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Study subjects
For this study, we selected 396 consecutive clinically stable outpatients with post myocardial infarction in sinus rhythm, who had an EF between 35 and 40% and no symptoms of CHF (NYHA class I or stage B for ACC/AHA1). We defined clinically stable patients as those who had not been hospitalized or had their therapy adjusted or experienced any other acute coronary artery or non-coronary event during the past three months. All participants had undergone revascularization either cutaneously or by aorto-coronary artery bypass at least 6 months before entering the study. No further revascularization procedures were envisaged when patients entered the study. None of the patients had left bundle branch block (LBBB), malignancy, primary valve disease, antiarrhythmic therapies, atrial fibrillation, extrasystoles (one extrasystole per minute was permitted), or other arrhythmias likely to interfere with assessments. None of the subjects had a documented history of cardiac arrest, ventricular tachycardia, or fibrillation.
Study subjects were from a larger database of 881 patients: 99 subjects were excluded because of atrial fibrillation, 57 because of pacemaker implantation, 185 because they were clinically unstable, 58 because their EF was lower than 35%, and 44 because of LBBB. A further 21 subjects initially enrolled were excluded: nine patients because their ECG recording was of poor quality (large artefacts or high number of extrasystoles), two because they refused to give their consent, and ten because they were unavailable for follow-up.
Before entering the study, all subjects underwent a complete history taking, physical examination, routine laboratory investigations, including 24 h plasma and urine sampling of sodium and potassium, electrocardiography (ECG), a two-dimensional Doppler ultrasonographic study of the carotid arteries, and echocardiography. Venous blood samples were obtained from an indwelling catheter after subjects had rested for 30 min supine. Test tubes were placed on ice, centrifuged immediately at 3000 g and plasma samples obtained were stored at –70°C until determination of B-type natriuretic peptide (by enzyme-linked immunosorbent assay).
All participants gave their informed consent to the procedures and the Ethics Committee of the Department of the Science of Ageing, University of Rome, ‘La Sapienza’ approved the study. The study complied with the ethical rules for human experimentation stated in the Declaration of Helsinki.
Study protocol and data acquisition
At 9.00 am, after a 15 min rest lying down, each subject underwent a 15 min recording from a single ECG lead (Telemetria Mortara Rangoni). The ECG analogical signal was acquired simultaneously and digitally converted with a custom-designed card (Keithley Metrabyte—DAS 1200 Series, Cleveland, Ohio, USA) at a sampling frequency of 500 Hz per channel with 12-bit precision.
For recognition and measurement of the RR and QT intervals, we used a software program based upon an automated derivative/threshold algorithm. To calculate the QT interval and to make the end of the T-wave easier to identify, we used a software program based upon the algorithm for quantifying beat-to-beat fluctuations in QT interval variability proposed by Berger et al.13 and validated in other previous studies.14–16
To obtain the QTVI from the 5 min beat segments recorded, we calculated QT and RR mean (QTm and RRm) and variances (QTv and RRv). The QTVI was then determined with the following formula:11–16
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To validate the software program based on Berger's algorithm,13 the same physician (G.P.), blinded to the RR and QT interval values obtained automatically, analysed a sample of 40 ECG recordings, randomly chosen from among the ECG recordings of the patients enrolled, measuring RR and QT intervals manually with the tangential method. In brief, the physician selected the ECG lead with the least noise and the most consistent T-wave morphology among limb lead I, lead aVF, and lead V3 and applied the tangential method to these leads. The physician chose the lead V3 in 22 ECG, the limb lead I in 11 ECG, and the lead aVF in the remaining nine ECG.
The QT corrected (QTc) was obtained from the initial 12-lead ECG recording according to Bazett's formula.17
Follow-up
Recruitment of subjects began on 1 January 1999 and ended on 31 December 2000. Follow-up began after recruitment and lasted 5 years until 31 December 2005. Participating subjects were followed-up at our outpatient clinic four times a year and were contacted by telephone monthly. Causes of death were obtained from the death certificate. The ninth revision of the International Classification of Diseases18 was used for coding. Sudden (presumably arrhythmic) death was defined as natural death that occurred within 1 h after the onset of acute symptoms.
Data and statistical analysis
Unless otherwise indicated all data are expressed as mean ± SD. Data with skewed distribution are given as median and interquartile range [75th percentile–25th percentile]. All data were evaluated with the database SPSS-PC+ (SPSS-PC+ Inc., Chicago, IL, USA). Data were analysed in two subgroups: patients who died of SCD and those who survived. Patients who died of causes other than SCD were excluded.
One-way analysis of variance (ANOVA) was used to compare the general characteristics and other linear data in the study groups. Mann–Whitney U test or 
2 test were used for comparison between data with nonlinear distribution. Spearmen correlation coefficient was used to test relations between two variables.
We prespecified a high-risk subgroup of studied patients by identifying individuals in the highest quintile (80th percentile) of distribution of QTc, QTv, QTVN, and QTVI values. Kaplan–Meier curves, with log-transformed data were used to address our primary hypothesis, namely to test the association between these QT variables and total mortality, mortality unrelated, and mortality related to SCD. The association between continuous QT (QTc, QTv, QTVN, and QTVI) or dichotomized QT variables (80th percentile of QTc, QTv, QTVN, and QTVI values) and endpoints (total mortality, mortality unrelated, and mortality related to SCD) was tested with univariable and multivariable Cox proportional-hazard regression model. The other known clinical predictors of mortality (listed in Table 1) were preliminarily analysed using a stepwise multivariable regressional model including age, sex, body mass index, systolic and diastolic blood pressure, heart rate, echocardiographic data, QRS length, B-type natriuretic peptide values, hypertension, dyslipidaemia, diabetes mellitus, parental history of sudden death or myocardial infarction, and pharmacological therapies. The limits of agreement between automatically (Berger's algorithm) and manually detected RR and QT intervals were calculated according to the method proposed by Bland and Altman19 (mean difference ±1.96 SD). A P-value of <0.05 was considered to indicate statistical significance.
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Results |
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Of the 396 subjects who were effectively studied, 42 had died when the 5-year follow-up ended (overall mortality rate 11%, 2% per year): 23 subjects had died of SCD (mortality rate of 6% for SCD, 1.2% per year), whereas 19 subjects had died of causes unrelated to SCD (nine of worsening CHF and 10 subjects of non-cardiovascular causes). Of the 396 patients, 62 experienced 69 non-fatal cardiovascular events during follow-up: 23 were hospitalized for CHF, 12 underwent CRT-ICD implantation, nine experienced acute myocardial infarction, nine had unstable angina and angioplasty, six had stroke, and 22 had atrial fibrillation. Demographic, clinical characteristics, and dynamic-derived ECG values are given in Tables 1 and 2.
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According to the preliminary analysis with the stepwise multivariable regressional model, none of the known clinical predictors of mortality (age, sex, body mass index, systolic and diastolic blood pressure, heart rate, echocardiographic data, QRS length, B-type natriuretic peptide values, hypertension, dyslipidemia, diabetes mellitus, parental history of SCD or myocardial infarction, and pharmacological therapies) were associated with the defined endpoints (total mortality, mortality unrelated, and related to SCD). Hence, none of them were included as covariates in the subsequent analysis to test the association between QT variables (QTc, QTv, QTVN, and QTVI) and prespecified endpoints.
The 80th percentile values of the QT variables studied were 0.421 s for QTc, 0.024 s2 for QTv, 0.24 for QTVN, and –0.47 for QTVI. Values greater or equal to the 80th percentile were found in 74 subjects for QTv, in 72 for QTVN, and in 75 for QTVI. The 80th percentile of QTv, QTVN and QTVI succeeded in identifying the same number of cases of SCD, namely 14 of 23 (61%), whereas the QTc value identified only five (22%).
In the univariable prognostic model considering QTv, QTVN, and QTVI as continuous (Table 3) and as dichotomized variables for values equal to or above the 80th percentile (Table 4) were associated with increased hazards ratios (HR) for total mortality and for mortality related to SCD. Values for mortality related to SCD reached greatest significance. The multivariable prognostic model considering QTv, QTVN, and QTVI as continuous variables (Table 5) and as dichotomized variables for values equal to or above the 80th percentile (Table 6) disclosed no significant association with total mortality or mortality related to SCD, except for QTVI. Neither the univariable nor the multivariable prognostic model disclosed a significant association among the QT variables and the endpoint, mortality unrelated to SCD. Accordingly, the survival curves constructed for the 80th percentile values of QTVN (Figure 1) and QTVI (Figure 2) exhibited a good significance for total mortality and mortality related to sudden death but no significance when victims of sudden cardiac were censored from the analysis.
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QTv correlated significantly with QTVI (r = 0.639, P < 0.01) and QTVN (r = 0.938, P < 0.01), QTVI also correlated significantly with QTVN (r = 0.648, P < 0.01).
Subjects who did not experience acute non-fatal cardiovascular events (n = 292) had significantly lower QT values than those who did (n = 62): for QTv [0.011 (0.042) vs. 0.028 (0.009), P < 0.0001], for QTVN [0.011 (0.09) vs. 0.025 (0.029), P < 0.0001], and for QTVI [–1.05 (0.63) vs. –0.71 (0.77), P < 0.0001]. No difference between these three variables was observed among survivors with acute non-fatal events and victims of SCD.
Automatically calculated (Berger's algorithm) and manually calculated RR and QT interval measures showed good agreement (RR-interval mean difference –0.55 ms ±4.16 ms; lower 95% limit –8.7 ms and upper 95% limit 7.6 ms; QT mean difference –0.4 ms ±2.28 ms; lower 95% limit –4.1 ms and upper 95% limit 4.8 ms).
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Discussion |
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Our findings in this prospective study conducted in over 400 outpatients from a single centre indicate that the measures of temporal QT variability we studied, especially the QTVI, are strong predictors of SCD in patients with post-ischaemic dilated cardiomyopathy with a moderately depressed EF and symptomless for CHF. We show that patients with a QTVI value equal to or higher than the 80th percentile (
–0.47) are at exceedingly high risk for SCD. No other data on QT variability are available from prospective studies. The only relevant study is a post hoc analysis conducted on subjects enrolled in the MADIT II and using as the endpoint data on ventricular fibrillation or sustained ventricular tachycardia extracted from the memory of an ICD. The multivariable model identified a QTVN around the 75th percentile as the most valuable predictor of SCD.10 The differences between the populations studied obviously invalidate comparisons between the two studies. For example, patients in the MADIT II had severe CHF, whereas our patients were symptomless.
Another interesting finding emerging from our study is that in post-infarction subjects who had a moderately depressed EF and were symptomless for CHF, the incidence of sudden death was around 1.2% per year. Although this figure may not seem particularly high in relative terms in absolute terms, it is extraordinarily high. Patients with CHF number around 10 million in Europe2 and 5 million in the USA.1 An estimated 60% of these, 6 million in Europe and 3 million in the USA, are symptomless.20 Assuming our annual mortality rate of 1.2% as valid presumably about 72 000 deaths a year in Europe and 36 000 in the USA in such a population are caused by SCD. The annual mortality rate we report is nevertheless lower than the 2.8% recently reported in the Candesartan in Heart Failure Reduction in Mortality study (CHARM)8 also in a population with a moderately depressed EF. In the CHARM study and also in the population studied retrospectively in MADIT II,10 the difference lies in the worse NYHA functional class (II–IV vs. I) of subjects enrolled in the CHARM study than in ours and the different EF (32–42% vs. 35–40%).
Our findings might well suggest considering patients with a high QTVI and a moderately depressed EF (from 35 to 40%) possible candidates to receive an ICD as primary prophylaxis for SCD, even though this strategy needs to be confirmed in a larger, multicentre prospective study. Nevertheless if all our study participants who had a QTVI –0.47 had received an ICD (about 75 patients) and ICD therapy had prevented the 23 SCDs, only five patients would need to be treated to save one life per year (NNTx year). The NNTx year estimated from our comparatively simple study approaches figures obtained with far more restrictive selection criteria and complicated study protocols, in MADIT I (NNTx year = 4) and MUSTT (NNTx year = 3).21 Indeed, in MADIT I,3 the inclusion criteria were previous myocardial infarction, an EF 35% percent, NYHA functional class II–IV, the presence of non-sustained asymptomatic ventricular tachycardia, and electrophysiologic testing-induced ventricular tachycardia resistant to procainamide. In the MUSTT,4 conversely, the inclusion criteria were previous myocardial infarction, an EF 40%, the presence of non-sustained ventricular tachycardia, and ventricular tachycardia identified on electrophysiological testing. Another salient point is that the current guidelines for ICD therapy as primary prophylaxis for SCD are based on trials such as MADIT II,4 the COMPANION22 branch ICD trial 21, and the SCD-HeFT,6 all of which used the EF as the sole criterion and yielded an NNTx year of 11 in MADIT II and 14 in both COMPANION and SCD-HeFT.21 Finally, we emphasize that stratifying the risk of sudden death in a population at relatively low risk, such as the one we studied, means selecting tests that minimizes the number of subjects at real risk. In practice, our study suggests that subjects with QTv, QTVN, and QTVI values below the 80th percentile are not at risk of SCD.
The QTVI is a marker of temporal inhomogeneity in myocardial repolarization, an abnormality associated with re-entrant malignant ventricular arrhythmias. SCDs in patients with CHF are in most cases caused by sustained ventricular tachycardia or fibrillation, or both, and are associated with transmural dispersion of myocardial repolarization.23 In healthy subjects, the duration of repolarizations among subepicardial, intermediate layer (M cells) and subendocardial cells physiologically suffer from a certain degree of asynchrony.24 Indeed, the repolarization phase lasts longer in the intermediate layer where sodium channels (INa) predominantly concentrate and slow-activating components of the delayed rectifier current (IKs) decrease.24 In ECG recordings from patients with CHF, the temporal myocardial repolarization inhomogeneity is accentuated owing both to structural disruption (including fibrosis and ischaemia) and ultrastructural imbalance that severely alter ion channels,25 and probably to the sympathetic hyperactivity and reduced cardiac vagal control. Finally, the electrophysiological mechanisms through which increased transmural dispersion of repolarization induces and maintains malignant arrhythmia are the trigger activity and re-entry.23,26 Transmural dispersion of repolarization underlies the QT temporal dispersion seen in surface ECG recordings. On a surface ECG recording, the end of the T-wave or U-wave coincides with the end of cardiac repolarization in the last myocardial layer and differs by some tens of milliseconds between the various cycles. The larger the difference the more the QTv increases and the greater is the tendency for SCD. This being so, the QTv and the two measures of temporal dispersion derived from it (QTVN and QTVI) should be able to stratify the risk of SCD from malignant ventricular arrhythmias. Given that sympathetic hyperactivity and lower heart rate variability play a determinant role in inducing malignant ventricular arrhythmias in patients with CHF,27 a further useful measure in stratifying the risk of SCD might be the QTVI numerator (see formula). By augmenting the influence of neuroautonomic functions, this feature might also explain why we found that QTVI was a more significant predictor than QTVN.
Last, we wish to draw attention to a technical problem that hampers more widespread use of QT, namely the difficulty in computing the end of the T-wave. None of the commercially available software guarantee reliable estimates in this ECG zone and evaluation errors (also lasting few thousandths of a second) tend exponentially to increase QTv. For this reason, we recommend using the method based on the template of Berger et al.13 even if it entails visually checking the proper postioning of the points on the ECG tracing.
In conclusion, in a population with CHF (NYHA I, stage B) secondary to post-ischaemic dilated cardiomyopathy and a moderately depressed EF (from 35 to 40%), an increase in the indices of QT variability is associated with a significant increase in the risk of SCD. This finding warrants a randomized prospective study enrolling subjects with these clinical characteristics and using the QTVI value as a criterion for implanting an ICD, so as to determine the real validity of this index in improving survival in such patients.
Conflict of interest: none declared.
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