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From the Department of Epidemiology and Biostatistics (M.C. de B.,
A.W.H., A.H., D.E.G.), Erasmus University Medical School, Rotterdam;
Department of Medical Informatics (M.D. de B., J.A.K., J.H. van B.), Erasmus
University Medical School, Rotterdam; and Julius Center for Patient Oriented
Research (A.W.H., D.E.G.), Utrecht University, Academic Hospital Utrecht,
Netherlands.
Correspondence to Martine de Bruyne, MD, Department of Epidemiology and Biostatistics, Erasmus University Medical School, PO Box 1738, 3000 DR Rotterdam, Netherlands. E-mail debruyne{at}epib.fgg.eur.nl
Methods and Results—QTc dispersion was computed with the use of
the Modular ECG Analysis System as the difference between the
maximum and minimum QTc intervals in 12 and 8 leads (ie, the 6
precordial leads, the shortest extremity lead, and the median of
the 5 other extremity leads). After exclusion of those without a
digitally stored ECG, the population consisted of 2358 men and 3454
women. During the 3 to 6.5 years (mean, 4 years) of follow-up, 568
subjects (9.8%) died. The degree of QTc dispersion was categorized
into tertiles. Data were analyzed using the Cox proportional
hazards model, with adjustment for age. For QTc dispersion in 8 leads,
those in the highest tertile relative to the lowest tertile had a
twofold risk for cardiac death (hazard ratio, 2.5; 95% confidence
interval [CI], 1.6 to 4.0) and sudden cardiac death (hazard ratio,
1.9; 95% CI, 1.0 to 3.7) and a 40% increased risk for total mortality
(hazard ratio, 1.4; 95% CI, 1.2 to 1.8). Additional adjustment for
potential confounders, including history of myocardial infarction,
hypertension, and overall QTc, did not materially change the risk
estimates. Hazard ratios for QTc dispersion in 12 leads were comparable
to those found for QTc dispersion in 8 leads.
Conclusions—QTc dispersion is an important predictor of cardiac
mortality in older men and women.
In these previous studies, QT dispersion was measured retrospectively
and manually in a limited number of cases and controls by one or more
observers with the use of a digitizing tablet. Evidence from large,
prospective studies on the prognostic implications of QT dispersion is
lacking. The use of a computer program to measure QT dispersion
facilitates large studies and excludes intraobserver and interobserver
variability.
We assumed that the risk associated with increased QT dispersion
applies not only to patient populations but also to the population at
large; therefore, we examined whether increased QT dispersion,
established by computer analysis, was associated with a higher
risk for total mortality, cardiac death, sudden cardiac death, and
nonfatal cardiac disease in a large nonhospitalized population of older
adults.
A digitally stored ECG was available for 6160 participants (86%). An
ECG was missing for 14% of the participants, mainly due to temporary
technical problems of the ECG recorder. Blood pressure was
calculated as the average of two consecutive measurements with a random
zero mercury manometer. Body mass index was calculated as
weight/length2 in kg/m.2
Hypertension was defined as systolic blood pressure of
>160 mm Hg or diastolic blood pressure of >95
mm Hg or the use of antihypertensive medication for the indication of
hypertension. Diabetes mellitus was defined as a nonfasting blood
glucose level of >11.1 mmol/L or the use of antidiabetic
medication. History of MI was defined as self-reported MI with hospital
admission, or MI on the ECG. Presence of angina pectoris was
established through use of the Rose
Questionnaire.20
After exclusion of 345 subjects without follow-up data, mainly because
they moved to unknown addresses, and 3 subjects with ECGs of poor
technical quality that could not be interpreted by the computer
program, the study population consisted of 2358 men and 3454 women.
Follow-up Procedures
The cause and circumstances of death were established soon after the
report of death by the municipal health service or the GP through the
use of a questionnaire from the GP and through scrutiny of information
from hospital discharge records in the case of admittance or
referral.
Overall, complete follow-up information was available for 94% of the
population of the Rotterdam Study. Participants for whom no follow-up
information was available were similar to those included in the
present study; they were an average of 3.5 years older (mean age,
73.9 years) and had a lower prevalence of hypertension (25% versus
30%) and diabetes (10% versus 14%). No other differences in baseline
characteristics were found.
Classification of fatal and nonfatal events was based on the
International Statistical Classification of Diseases
and Related Health Problems, 10th
revision.21 We defined cardiac mortality as
death from MI (ICD-10: I21 to I24), chronic ischemic heart
disease (ICD-10: I25), pulmonary embolism or other
pulmonary heart disease (ICD-10: I26 to I28),
cardiomyopathy (ICD-10: I42 to I43), cardiac arrest
(ICD-10: I46), arrhythmias (ICD-10: I47 to I49), heart failure
(ICD-10: I50), or sudden cardiac death. Sudden cardiac death was
defined as death occurring instantaneously or within 1 hour after the
onset of symptoms or unwitnessed death in which a cardiac cause could
not be excluded.22 23 Nonfatal cardiac events
were defined as MI (ICD-10: I21 to I24), chronic ischemic heart
disease (ICD-10: I25), coronary artery bypass graft surgery (no
ICD-10 code), or percutaneous transluminal
coronary angioplasty (no ICD-10 code).
All events were classified independently by two research physicians. If
there was disagreement, a consensus was reached in a separate session.
Finally, all events were verified by a medical expert in the field of
cardiovascular disease. In case of discrepancies, the
judgment reached by this expert was considered definite.
ECG Interpretation and Measurements
Normally, the MEANS program determines an overall end of T waves
for all 12 leads together using a representative beat,
which results from selective averaging of dominant beats, and thus
QTc dispersion is not disclosed. The program was therefore
adjusted to determine the end of the T wave per lead. Taking the
location of the overall end of the T wave as a starting point, the
program searches forward and backward to establish the lead-specific
end of the T wave. If the T wave amplitude is <50 µV, the T wave is
considered to be flat and the lead is excluded from further
analysis. QTc dispersion is determined as the difference
between the maximum and minimum QTc in all considered leads.
Analogously, QT dispersion is determined as the difference between the
maximum and minimum QT interval, without correction for heart rate, in
all considered leads.
QTc dispersion measured by the MEANS program was validated against
the results of two human observers on a set of 100 ECGs (unpublished
data, 1997). Both observers independently marked the end of the T wave
in each lead with the cursor on a high-resolution computer screen. We
found a mean QTc dispersion difference between MEANS and pooled
data from both observers of 5.1 ms (SD, 29.3 ms). These results are
comparable with the interobserver variability between the two human
observers (mean, 6.7 ms; SD, 28.4 ms). Therefore, we concluded that the
performance of the program was comparable to that of human
observers.
LVH was determined using voltage as well as repolarization criteria. A
negative T wave was defined as
Lead Selection for QTc Dispersion
It can be shown that if there is a shortest T wave in one of the
extremity leads, the other 5 extremity leads must have the same end of
T (see "Appendix"). As a consequence, true QTc dispersion
cannot exist among these leads, and QTc dispersion measured in
these leads can only be the result of measurement inaccuracy.
Therefore, we defined QTc dispersion as the difference between the
maximum and the minimum QTc interval in 8 leads (ie, the 6
precordial leads, the shortest extremity lead and the median of the
5 other extremity leads). In addition, we computed QTc dispersion
in 12 leads. ECGs in which QTc dispersion could be measured in
fewer than 9 of the 12 leads were excluded (n=16 of the 5812 subjects
in the present study).
Data Analysis
The degree of QTc dispersion in both 8 and 12 leads was
categorized in tertiles, with intertertile values of 39 and 60 ms (in 8
leads) and 47 and 66 ms (in 12 leads) respectively. In addition, QT
dispersion in 8 and 12 leads was categorized in tertiles. All
analyses were performed for both 8- and 12-lead measures of
dispersion.
To evaluate the association between QTc dispersion and potentially
confounding factors, differences in the distribution of selected
baseline characteristics between subjects in tertiles of QTc
dispersion were examined with one-way ANCOVA, with adjustment for age
and sex when appropriate.
The Cox proportional hazards model was used to examine the risk for
cardiac and total mortality and nonfatal cardiac events in relation to
tertile of baseline QTc and QT dispersion, with adjustment for two
sets of confounders: age and sex (the latter only when
non–sex-specific risks were estimated), and all
possible confounders, excluding other ECG abnormalities, resulting from
the ANCOVA (P<.05). The lowest tertile of QTc
dispersion or QT dispersion was taken as the reference category. To
minimize the effect of missing data in the multivariate
analysis, missing values of categorical variables were
replaced by dummies. Missing values of continuous variables were
replaced by the average value, and a dummy variable (to indicate
that the participant's individual value was missing) was added to the
model.28
To compare predictive value of QTc dispersion with that of other
commonly used cardiovascular risk indicators, age- and
sex-adjusted hazard ratios for cardiac mortality of important
cardiovascular risk indicators were computed.
Influence of age and history of MI on the risk for cardiac death
associated with increased QTc dispersion was examined through
subgroup analyses for these possible effect modifiers.
The distribution of QTc dispersion, measured in both 8 and 12
leads, in cases of cardiac death during the follow-up period was
shifted to the right compared with survivors (Fig 1
During the 3 to 6.5 years (mean, 4 years) of follow-up, 568 subjects
(9.8%) died: 166 (2.9%) died of a cardiac cause and 73 (1.3%) died
suddenly. In 193 of the subjects (3.3%), at least one nonfatal cardiac
event occurred. Cardiac mortality according to tertile of QTc
dispersion for men and women is presented in Fig 2a
Participants in the highest tertile relative to the lowest tertile of
QTc dispersion in 8 leads had a more than twofold age- and
sex-adjusted risk for cardiac death (hazard ratio, 2.5; 95% CI, 1.6 to
4.0) and sudden cardiac death (hazard ratio, 1.9; 95% CI, 1.0 to 3.7)
and an increased risk for total mortality (hazard ratio, 1.4; 95% CI,
1.2 to 1.8) and nonfatal cardiac events (hazard ratio, 1.3; 95% CI,
0.9 to 1.8), although the latter result was not statistically
significant (Table 2
QTc dispersion in both 8 and 12 leads ranks among the strongest
predictors for cardiac mortality (Fig 3
Subgroup analysis showed that the risk for cardiac death
associated with increased QTc dispersion for participants in the
highest relative to the lowest tertile of QTc dispersion was not
modified by age but was more pronounced in those without a
history of MI (hazard ratio, 3.5; 95% CI, 1.8 to 6.9) than in
those with a history of MI (hazard ratio, 1.8; 95% CI, 0.8 to
3.9).
The risks associated with QTc dispersion based on 12 leads was
very similar to the risk associated with QTc dispersion in 8 leads
(Table 3
The risk estimates for the various end points associated with QT
dispersion, without correction of the QT interval for heart rate, in 8
and 12 leads were similar but had wider 95% CIs compared with the risk
estimates for QTc dispersion in 8 and 12 leads.
Previous studies were performed in patient populations. Their
findings that QT dispersion is larger in those with
MI,2 9 10 hypertension,
LVH,13 and diabetes
mellitus14 are confirmed by ours. Increased risk
for cardiac mortality associated with QTc dispersion has been
reported in patients with peripheral artery
disease7 and MI.18 Our
findings provide support for an association of increased QTc
dispersion and cardiac death in those with and without coronary
heart disease. However, differences in mean values of QTc
dispersion in those who die from a cardiac cause compared with
survivors were much more pronounced in these earlier studies: 25 to 30
ms versus 4 to 6 ms in the Rotterdam Study. This may be explained by
differences in severity of the underlying disease in the population at
large compared with patient populations. In addition, differences in
measurement techniques may play a role.
Our findings are in accordance with the hypothesis that QTc
dispersion is due to patchy myocardial fibrosis resulting from MI,
ventricular dilatation, and neurohormonal activation
because we found a positive association of QTc dispersion with
many cardiovascular risk indicators.
Regardless of the technique used, QTc dispersion is difficult to
measure. The end of repolarization, assessed as the end of the T wave,
is a gradual process and therefore hard to define. The definition of
the end of the T wave is further complicated by low-amplitude T waves
and the presence of U waves. Differences in measurement techniques, by
hand or computer, are known to be the source of large variations in
absolute values of QT intervals.26 Prior studies
have shown that measurement of QTc dispersion is characterized by
from large measurement error and has a poor reproducibility in both
manual and computerized measurements29 30 31 32 33 ;
therefore, reported risk estimates are likely to be substantially
diluted.
QTc dispersion in 12 leads was larger than QTc dispersion in
8 leads. Because this difference probably is due mainly to measurement
error, it seems preferable to measure QTc dispersion in 8 leads,
although any difference between QTc dispersion in 8 and 12 leads
has little effect on the risk associated with QTc dispersion.
We conclude that QTc dispersion is a strong and independent
predictor of cardiac mortality in older men and women. Further studies
are warranted to study the mechanism underlying QTc dispersion and
to search for the most accurate measure of this mechanism.
Received June 24, 1997;
revision received October 1, 1997;
accepted October 6, 1997.
© 1998 American Heart Association, Inc.
Clinical Investigation and Reports
QTc Dispersion Predicts Cardiac Mortality in the Elderly
The Rotterdam Study
Abstract
Top
Abstract
Introduction
Methods
Results
Discussion
Appendix 1
References
Background—Increased QTc dispersion
has been associated with an increased risk for ventricular
arrhythmias and cardiac death in selected patient populations.
We examined the association between computerized QTc-dispersion
measurements and mortality in a prospective analysis of the
population-based Rotterdam Study among men and women aged 
55
years.
Key Words: electrocardiography • heart disease • age • risk factors • QT dispersion
Introduction
Top
Abstract
Introduction
Methods
Results
Discussion
Appendix 1
References
Recent clinical
studies have suggested that the interlead variability of the QT
interval in the standard ECG, defined as QT dispersion, reflects
regional differences in ventricular
repolarization.1 2 Increased dispersion of
recovery time is believed to increase the risk for serious
ventricular arrhythmias.3 4 5 6
It is hypothesized that an important entity underlying QT dispersion is
patchy myocardial fibrosis, resulting from myocardial ischemia,
ventricular dilatation, and neurohormonal
activation.3 7 This is supported by findings of
increased QT dispersion in patients with acquired long-QT
interval,1 8 MI,2 9 10
hypertrophic
cardiomyopathy,11 12 and
hypertension and LVH13 and in diabetic patients
with autonomic neuropathy.14
Moreover, QT dispersion has been associated with increased risk for
ventricular arrhythmias and sudden death in
patients with chronic heart failure,15 mitral
valve prolapse,16 MI,17 and
familial long-QT syndrome1 and with an increased
risk for cardiac mortality in patients with peripheral
arterial disease7 and
MI.18
Methods
Top
Abstract
Introduction
Methods
Results
Discussion
Appendix 1
References
Study Population and Baseline Data Collection
This study is part of the Rotterdam Study, a
population-based cohort study aimed at assessing the occurrence and
risk factors for chronic diseases in the elderly. Objectives and
methods of the Rotterdam Study have been described in
detail.19 Briefly, in the Rotterdam Study, all
men and women aged 55 years who live in the Rotterdam district
Ommoord were invited to participate (response rate, 78%). Of 7129
participants, the baseline data, collected from 1990 to 1993, included
an ECG and information on history of cardiovascular
disease, established cardiovascular risk factors, and
use of medications.
The follow-up period, which started at the baseline examination
and in the present analysis lasted until April 1996, was 3
to 6.5 years (mean, 4 years). With respect to the vital status of
participants, information was obtained at regular intervals from the
municipal health service in Rotterdam. Information on fatal and
nonfatal end points was obtained from the GPs working in the study
district of Ommoord. These GPs, covering 
85% of the cohort, have
their practices computerized and report possible fatal and nonfatal
events of participants on computer file to the Rotterdam Study data
center on a regular basis. All possible events reported by the GP were
verified by research physicians from the Rotterdam Study through
patient records of the participating GPs and medical specialists.
In April 1996, the medical records of participants with GPs from
outside the Ommoord area, representing 15% of the
cohort, were checked by research physicians, and for all possible
events, additional information for coding was collected.
A 12-lead resting ECG was recorded with an ESAOTE-ACTA
cardiograph with a sampling frequency of 500 Hz and stored digitally.
All ECGs were processed with the use of MEANS to obtain ECG
measurements and diagnostic interpretations. The MEANS
program has been extensively evaluated by the developers and
others.24 25 26 To adjust QT for heart rate, we
calculated QTc according to Bazett's formula:
QTc=QT/
, where RR is the RR interval in
seconds.27 1.00-mm negative deflection of the T
wave in lead II, aVF, or the precordial leads.
Traditionally, QTc dispersion is defined as the difference
between the maximum and minimum QTc interval in 12 leads. However,
in the standard 12-lead ECG, only 2 of the 6 extremity leads are
actually recorded. The other 4 leads are derived mathematically
from these 2 leads.
Differences in baseline characteristics between those with and
without follow-up data were examined with one-way ANCOVA, with
adjustment for age and sex when appropriate.
Results
Top
Abstract
Introduction
Methods
Results
Discussion
Appendix 1
References
Baseline characteristics of participants in different tertiles of
QTc dispersion are presented in Table 1
. Statistically significant differences
existed among the three comparison groups with regard to age,
systolic and diastolic blood pressure,
hypertension, diabetes mellitus, history of MI, overall QTc
interval, presence of negative T waves, and LVH on the basis of
ECG.
View this table:
[in a new window]
Table 1. Baseline Characteristics of Study Participants
According to Tertiles of QTc Dispersion ). In addition, QTc dispersion in
12 leads was shifted to the right compared with the distribution in 8
leads, reflecting larger dispersion in 12 than in 8 leads.
View larger version (19K):
[in a new window]
Figure 1. Distribution of QTc dispersion measured in 8 and
12 leads in those who die from a cardiac cause and in survivors among
5812 men and women aged 55 years. and 2b. It appears that in men,
increased risk for cardiac mortality starts at a lower level of
QTc dispersion than in women.
View larger version (20K):
[in a new window]
Figure 2. a, Cardiac mortality (percentage) by tertile of
QTc dispersion in 8 leads in men. b, Cardiac mortality (percentage) by
tertile of QTc dispersion in 8 leads in women. ). Additional
adjustment for hypertension, diabetes, and history of MI did not
materially change hazard ratio estimates for cardiac and all-cause
mortality, although the 95% CI of the adjusted hazard ratios for
sudden death events included one. Inclusion of other ECG abnormalities,
notably LVH, negative T waves, and maximum QTc interval, in this
model did not influence the results.
View this table:
[in a new window]
Table 2. Hazards Ratios in Subjects in the Middle and Highest
Tertiles Relative to the Lowest Tertile of QTc Dispersion Measured in
Eight Leads and Adjusted for Age and Sex (Model A) and for All Possible
Confounders (Model B) ).
The highest age- and sex-adjusted hazard ratios for cardiac mortality
were found for LVH (hazard ratio, 2.6; 95% CI, 1.7 to 4.0) and
QTc dispersion in 8 leads >60 ms (hazard ratio, 2.5; 95% CI, 1.6
to 4.0), whereas in the multivariate model, QTc
dispersion in 8 leads >60 ms was the strongest predictor for cardiac
mortality, followed by history of MI (hazard ratio, 2.0; 95% CI, 1.5
to 2.5). The corresponding multivariate hazard ratio
for cardiac death for QTc >440 ms was identical to the age- and
sex-adjusted hazard ratio, notably 2.3 (95% CI, 1.0 to 2.1).
View larger version (45K):
[in a new window]
Figure 3. Age- and sex-adjusted hazard ratios QTc dispersion
in 8 and 12 leads and other commonly used
cardiovascular risk indicators and ECG abnormalities.
QTcD8 indicates QTc dispersion in 8 leads; QTcD12, QTc dispersion in 12
leads. ). Hazard ratios tended to be
higher in QTc dispersion in 8 leads compared with QTc
dispersion in 12 leads, but 95% CIs hardly differed.
View this table:
[in a new window]
Table 3. Hazards Ratios in Subjects in the Middle and Highest
Tertile Relative to the Lowest Tertile of QTc Dispersion Measured in 12
Leads and Adjusted for Age and Sex (Model A) and for All Possible
Confounders (Model B)
Discussion
Top
Abstract
Introduction
Methods
Results
Discussion
Appendix 1
References
The results of this study show that increased QTc dispersion
is a strong and independent risk factor for cardiac mortality in older
men and women.
Selected Abbreviations and Acronyms
CI
=
confidence interval
GP
=
general practitioner
LVH
=
left ventricular hypertrophy
MEANS
=
modular ECG analysis system
MI
=
myocardial infarction
Appendix 1
Top
Abstract
Introduction
Methods
Results
Discussion
Appendix 1
References
Relationship Between Extremity Leads
In the standard 12-lead ECG, only 2 of the 6 extremity leads are
actually recorded (eg, leads I and II); the other 4 leads are
derived from mathematical relationships imposed by the lead system.
Thus, for the amplitudes in the extremity leads at any time, it holds
that III=II-I, aVR=-(I+II)/2, aVL=(I-III)/2, and aVF=(II+III)/2. If
all T waves end at the same moment, of course QT dispersion (QTD)=0.
Suppose the T wave in 1 lead, say I, is shorter than that in the other
leads, ending at some time instant t1. Then, with lead I equal to 0,
III=II for t>t1. This means that II and III must end at the same time.
Let us assume this moment to be t2. In the time interval t1-t2, lead
I=0, and using the above basic relationships, aVR=-II/2, aVL=-III/2,
and aVF=II=III. Thus, the T waves in all augmented leads end when the T
waves in the leads II and III end (ie, at t2). The same argument can be
applied to any extremity lead other than I. It is always true that if
there is a shortest T wave in 1 of the extremity leads ending at some
time t1, the T waves in the other 5 extremity leads must all end at the
same time instant t2>t1. As a consequence, QTD cannot exist among
these leads, and any measured QTD can only be the result of measuring
inaccuracy. The only possible true dispersion is between these 5 leads
and the single short lead, QTD=t2-t1.
Acknowledgments
This study was supported by the Netherlands Institute for Health
Sciences. The Rotterdam Study is supported by grants from several
institutions, including the Municipality of Rotterdam, the NESTOR
program for research in the elderly (supported by the Netherlands
Ministries of Health and Education); the Netherlands Heart Foundation,
the Netherlands Prevention Fund, and the Rotterdam Medical Research
Foundation (ROMERES).
References
Top
Abstract
Introduction
Methods
Results
Discussion
Appendix 1
References
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A Mosterd, B Cost, A.W Hoes, M.C de Bruijne, J.W Deckers, A Hofman, and D.E Grobbee The prognosis of heart failure in the general population. The Rotterdam Study Eur. Heart J., August 1, 2001; 22(15): 1318 - 1327. [Abstract] [PDF]
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M D Lowe, E Rowland, M J Brown, and A A Grace {beta}2 Adrenergic receptors mediate important electrophysiological effects in human ventricular myocardium Heart, July 1, 2001; 86(1): 45 - 51. [Abstract] [Full Text] [PDF]
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M. Malik and V. N. Batchvarov Measurement, interpretation and clinical potential of QT dispersion J. Am. Coll. Cardiol., November 15, 2000; 36(6): 1749 - 1766. [Abstract] [Full Text] [PDF]
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M. Zabel, B. Acar, T. Klingenheben, M. R. Franz, S. H. Hohnloser, and M. Malik Analysis of 12-Lead T-Wave Morphology for Risk Stratification After Myocardial Infarction Circulation, September 12, 2000; 102(11): 1252 - 1257. [Abstract] [Full Text] [PDF]
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 P. Sahu, P.O. Lim, B.S. Rana, and A.D. Struthers QT dispersion in medicine: electrophysiological Holy Grail or fool's gold? QJM, July 1, 2000; 93(7): 425 - 431. [Full Text] [PDF]
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M. Malik QT dispersion: time for an obituary? Eur. Heart J., June 2, 2000; 21(12): 955 - 957. [PDF]
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P. M. Okin, R. B. Devereux, B. V. Howard, R. R. Fabsitz, E. T. Lee, and T. K. Welty Assessment of QT Interval and QT Dispersion for Prediction of All-Cause and Cardiovascular Mortality in American Indians : The Strong Heart Study Circulation, January 4, 2000; 101(1): 61 - 66. [Abstract] [Full Text] [PDF]
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B. Houltz, B. Darpo, K. Swedberg, P. Blomstrom, H.J.G.M. Crijns, S.M. Jensen, E. Svernhage, and N. Edvardsson Comparison of QT dispersion during atrial fibrillation and sinus rhythm in the same patients, at normal and prolonged ventricular repolarization Europace, January 1, 2000; 2(1): 20 - 31. [Abstract] [PDF]
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R. Marfella, F. Rossi, D. Giugliano, M. C. de Bruyne, and J. M. Dekker QTc Dispersion, Hyperglycemia, and Hyperinsulinemia • Response Circulation, December 21, 1999; 100 (25): e149 - e149. [Full Text] [PDF]
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J. A. Kors, G. van Herpen, and J. H. van Bemmel QT Dispersion as an Attribute of T-Loop Morphology Circulation, March 23, 1999; 99(11): 1458 - 1463. [Abstract] [Full Text] [PDF]
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