Download QTc interval and survival in 75-year

Europace (2006) 8, 233–240
doi:10.1093/europace/euj040
QTc interval and survival in 75-year-old men and women
from the general population
Göran Nilsson1,2*, P. Hedberg3, T. Jonasson3, I. Lönnberg4, and J. Öhrvik1
1
Department of Clinical Research, University of Uppsala, Central Hospital, S-721 89 Västerås, Sweden; 2 Department of
Electronics, University of Mälardalen, Västerås, Sweden; 3 Department of Clinical Physiology, Central Hospital, Västerås,
Sweden; and 4 Department of Internal Medicine, Division of Cardiology, Central Hospital, Västerås, Sweden
Received 15 March 2005; accepted after revision 13 November 2005; online publish-ahead-of-print 13 February 2006
KEYWORDS
ECG;
QT;
BNP;
Echocardiography;
Risk stratification;
Heart rate
Aims The study concerns the relationship of the corrected QT (QTc) interval to 6.4 years of survival and
to measures of cardiac function, such as echocardiographic variables and plasma levels of brain
natriuretic peptide (BNP), in 75-year-old people.
Methods and results QTc was measured in a 12-lead electrocardiogram (ECG) in 210 men and 223
women, comprising a randomly selected sample from the general population (70% participation rate).
The Sicard 440/740 computer-analysis program, with Hodges’ formula for heart rate-based QT correction, was used. The optimal cut-off point for predicting survival according to the receiver operating
characteristic curve was found between 429 and 430 ms. Individuals with a QTc interval of 430 ms
(n ¼ 115) had decreased survival when compared with those with shorter QTc interval (n ¼ 318); the
relative risk was 2.4 (95% confidence interval 1.5–3.7). The predictive ability of QTc reflects an association between QTc and the following variables: BNP, left ventricular mass, and left ventricular ejection
fraction (but not diastolic filling patterns). Both Hodges’ and Bazett’s formulae for heart rate correction
of the QT interval were useful for predicting survival. The median QTc was 415 ms using Hodges’ formula
and 430 ms with Bazett’s formula. The QRS component of QTc predicted survival better than the rest of
the QTc interval and was approximately as useful as the QTc interval itself.
Conclusion The computer-derived QTc obtained from the ordinary 12-lead ECG identifies high-risk individuals among elderly people from the general population.
Introduction
Most, but not all, studies suggest that a prolonged QT
interval corrected (QTc) for heart rate is associated with
an increased risk of both cardiovascular and all-cause mortality in the general population.1–4 The increase in mortality
appears to be restricted to subsets with signs of cardiovascular disease, suggesting that a relatively long QTc may
be a marker of cardiovascular disease. A relationship has
also been found between QTc and carotid atherosclerosis
in non-diabetic patients, suggesting that a long QTc interval
may be a marker of subclinical atherosclerotic disease.5
In addition, a long QTc interval may be associated with
dysfunction of the autonomic nervous system.6
QTc increases with age.7,8 Population-based studies of the
survival implications of the length of the QTc interval usually
recruit people aged ,65, but in the Rotterdam study9 a
cohort of elderly subjects (a few .75 years of age) were
followed for 3–6 years. The increase in all-cause mortality
* Corresponding author. Tel: þ46 21173376; fax: þ46 21173733.
E-mail address: [email protected]
associated with the prolongation of QTc was less pronounced
in people .70 years of age than in younger age groups.
There is a need to extend our knowledge of the relationship
between QTc length and survival and the extent to which the
QTc interval reflects cardiac function in elderly people.
Objective
The primary objective of the present study was to determine the relationship of all-cause mortality, as well as of
cardiovascular death, with the length of the QTc interval
in 75-year-old men and women from the general population.
It should be noted that all-cause-mortality is an objective
and unbiased endpoint, unlike cardiovascular death, which
may be significantly affected by ascertainment bias.10
A secondary objective was to examine whether the predictive ability of QTc with regard to survival was related to
established signs of reduced cardiac function, such as echocardiographically determined systolic and diastolic left ventricular function, plasma concentration of B-type or brain
natriuretic peptide (BNP), and signs of a pathological ECG
as determined by the Minnesota code. Other secondary
& The European Society of Cardiology 2006. All rights reserved. For Permissions, please e-mail: [email protected]
234
G. Nilsson et al.
objectives were to examine the impact on survival prediction
of different formulae for heart rate correction and to define
the relative importance for survival of the QRS and the JTc
(also called non-QRS) components of the QTc interval.
Self-reported previous myocardial infarction (confirmed from
medical records), angina pectoris, hypertension, and diabetes
were registered. Beta-blockers and calcium inhibitors (Table 1)
were the only antiarrhythmic drugs used in the patients of present
study. No patient was taking sotalol.
Methods
Electrocardiography
Study population
A standard 12-lead electrocardiogram (ECG) was taken using a
Siemens Elema AB (Solna, Sweden) machine. The QT and QRS intervals were measured by the Sicard 440/740 ECG computer-analysis
programme (Megacart version 3 V4, 7/2.38/23, Siemens Elema),12
which is used worldwide and has been extensively validated.13
In this programme, an overall onset and termination were computed for QT and QRS from the average beat. The QT intervals were
corrected for heart rate using Hodges’ linear-correction formula
[QTc ¼ QT þ 1.75(heart rate 2 60)].14 This formula was chosen
because the QT interval corrected with this formula was found to
have a negligible correlation with heart rate as opposed to the extensively used Bazett’s formula.15 However, in the present study, survival was also determined after correcting the computer-derived QT
interval according to the formulae of Bazett15 (QTc ¼ QT/square
root of RR interval), Fridericia16 (QTc ¼ QT/cubic root of RR interval), and Rautaharju.17
The heart rate-corrected JT interval, JTc, was defined as QTc
minus QRS.18
The ECG was registered in the morning after a resting period of
at least 10 min. Two physicians blinded to the clinical data of
the patient coded the ECG according to the Minnesota system.19 If
the coding differed between the physicians, a new coding was
The details of the Västerås study of 75-year-old men and women
have previously been published.11 In short, 433 persons (210 men
and 223 women) born in 1922, representing 70% of a random
sample of 618 men and women born in 1922 and living in the town
of Västerås, Sweden, were extensively examined in 1997 in terms
of their cardiovascular health. The reasons for non-participation
by 185 persons were that the person could not be reached
(n ¼ 29), the person died before the investigation procedure was
initiated (n ¼ 2), language difficulties and logistical problems
(n ¼ 26), locomotor impairment (n ¼ 28), treatment for heart
disease (n ¼ 13), other diseases (n ¼ 41), and unknown (n ¼ 46).
None of the participants was using drugs associated with the
prolongation of the QT interval.
The survival status was determined on 1 September 2003 (median
follow-up 6.4 years; maximum follow-up 6.6 years). Death certificates were obtained from the Epidemiological Centre, Swedish
National Board of Health and Welfare. Cardiovascular death was
defined as ICD codes I21 through I71. The research Ethics
Committee at the University of Uppsala, Sweden, approved the
study. The study complies with the Declaration of Helsinki.
Table 1 Baseline characteristics of the study patients according to survival
Clinical characteristics
Survivors (n ¼ 353)
Non-survivors (n ¼ 81)
P-value
Male gender
BMI
Diabetes
Hypertension
History of myocardial infarction
Angina pectoris
Current smokers
Beta-blockers
Digitalis
Diuretics
Calcium inhibitors
ACE-inhibitors
Lipid-lowering drugs
Antidepressant drugs
Systolic blood pressure
Diastolic blood pressure
Echocardiographic variables
Wall motion index
EF (Simpson)
Left ventricular mass
BNP (pg/mL)
Ordinary 12-lead ECG
Normal according to the
Minnesota code
Abnormal Q-wave
Bundle branch block
Atrial fibrillation
QTc (ms)
QRS (ms)
JTc (ms)
44.5
25.9 + 3.6
6.8
26.0
7.7
11.1
8.2
19.8
3.4
19.0
13.0
6.5
2.8
1.1
165.5 + 25.0
84.3 + 9.8
69.1
25.4 + 3.4
12.3
38.3
17.3
22.2
19.8
25.9
11.0
8.6
6.1
9.9
6.2
2.5
163.1 + 25.3
84.3 + 10.5
,0.001
0.272
0.109
0.039
0.012
0.011
0.019
0.228
0.019
0.032
0.088
0.337
0.171
0.313
0.457
0.998
2.04 + 0.26
60.0 + 9.0
87.7 (75.3–104.4)
25.4 (12.5–48.0)
1.90 + 0.41
53.6 + 13.9
95.5 (84.7–123.7)
35.1 (19.5–81.4)
67.4
50.6
4.0
4.5
4.2
413 (401–428)
90 (82–98)
322 (310–337)
9.5
5.2
8.6
425 (407–439)
94 (85–110)
324 (311–342)
Values are presented as the mean + SD, median (interquartile range), or percentage.
BMI, body-mass index; ACE, angiotensin converting enzyme; EF, ejection fraction.
,0.001
,0.001
0.002
0.001
0.007
0.087
0.775
0.154
0.002
0.002
0.331
QTc interval and survival in 75-year-old men and women
235
performed by consensus. Using the Minnesota code, the ECG was
classified as normal in the absence of the following major abnormalities20: abnormal Q-wave, ST-segment depression or elevation,
T-wave change, incomplete or complete left or right bundle
branch block, atrial fibrillation, atrioventricular block, left-axis
deviation, and high R-wave amplitude.
Echocardiography
Echocardiography was performed using an Acuson XP 128 system
(Acuson Co, Mountain View, CA, USA). The same physician (P.H.),
who was blinded to the participants’ clinical data, performed all
the studies. Left ventricular ejection fraction (LVEF) was calculated
online using the biplane disc summation method (modified
Simpson’s rule) in participants in whom at least 60% of the endocardial border could be detected (n ¼ 279). A wall motion index for the
left ventricle was computed by dividing the left ventricular wall into
nine segments examined in five standard projections, as described
in detail by Hedberg et al. 11 This measure was available in 411
cases. In addition, adjusted left ventricular mass was calculated
as left ventricular mass/body surface area in square metres,
which was calculated according to the formula of Dubois [length
(in cm)0.425 weight (in kg)0.725 71.84].
Using the Doppler technique, the following measures representing
diastolic filling patterns of the left ventricular chamber were
obtained: peak atrial (A-wave) and early diastolic (E-wave)
velocities for transmitral flow, quotient between A- and E-waves,
and deceleration time of the E-wave. Some measurements were
not available in all patients (Table 2) for various reasons, such as
the lack of the A-wave in the cases of atrial fibrillation.
Laboratory methods
Venous blood was sampled in the morning from participants who had
been resting in a recumbent position for at least 5 min. For the
analysis of BNP, the blood was collected in 10 mL ice-chilled tubes
containing ethylenediamine tetraacetic acid. The tubes were
turned 5–10 times and placed again on ice, centrifuged at 48C at
200 g. The separated plasma was then put into polypropylene
tubes and frozen at 2708C. BNP analyses were performed at the
Western Infirmary, Glasgow, UK, using two-site monoclonal antibody
immunoradiometric assays (Shionoria BNP kit, Shionogi & Co. Ltd,
Osaka, Japan). The within-assay and between-assay coefficients
of variation were 3.7 and 7.5%, respectively. The concentration is
presented in pg/mL.
The concentration of total cholesterol, triglycerides, and highdensity cholesterol (HDL) were measured using routine methods;
low-density cholesterol (LDL) was calculated using Friedewald’s
formula.
Blood pressure was measured to the nearest 5 mmHg with a mercury
sphygmomanometer with subjects sitting and relaxed for 10 min.
Statistics
The Wilcoxon Mann–Whitney rank-sum test and Student’s t-test
were used to test differences between groups containing data
with non-normal and normal distribution, respectively. Categorical
data were compared using x 2 statistics.
Receiver operating characteristic (ROC) curves were calculated to
determine an optimal cut-off point, which was defined as the QTc
length resulting in the highest sum of the sensitivity and specificity.21 The purpose of this calculation was to define a QTc level
suitable as a rule of thumb for finding individuals with a high mortality risk in clinical practice. Ten-fold cross-validation was performed to compensate for the fact that the same individuals were
used to assess the optimal QTc cut-off level and for the classification
into survivors and non-survivors.22
Cumulative mortality was estimated by means of the Kaplan–
Meier analysis comparing participants below and above the
Table 2 Characteristics of patients with QTc ,430 ms and patients with QTc of 430 ms or longer
Men
Previous myocardial infarction
Angina pectoris
Hypertension
Diabetes mellitus
Current smokers
Atrial fibrillation
Abnormal ECG
Dead after 6.4 years
BMI
BNP (pg/mL)
Systolic blood pressure
Diastolic blood pressure
Electrocardiographic variables
QRS interval (ms)
JTc interval (ms)
Echocardiographic variables
Left ventricular mass (g/m2, body surface),
n ¼ 245/94
Left ventricular wall motion index,
n ¼ 302/109
EF, n ¼ 204/76
Peak velocity E-wave, n ¼ 305/107
Peak velocity A-wave, n ¼ 290/101
E/A ratio, n ¼ 290/101
E-wave deceleration time (ms), n ¼ 298/104
QTc , 430 ms
(n ¼ 318)
QTc 430 ms
(n ¼ 115)
P-value
47.8
7.2
9.1
25.3
8.2
11.6
4.7
26.7
11.0
25.6 + 3.3
23.0 (11.8–45.2)
164.0 + 25.1
83.7 + 9.7
51.8
15.8
24.6
36.5
7.0
6.9
5.6
60.3
27.6
26.6 + 4.1
37.9 (19.1–79.7)
167.9 + 24.7
85.8 + 10.2
ns
0.008
,0.001
0.028
ns
ns
ns
,0.001
,0.001
0.013
,0.001
ns
ns
88 (82–96)
317 + 16
96 (86–114)
346 + 23
,0.001
,0.001
87.4 (76.4–101.5)
2.1 + 0.3
60.3 + 8.9
0.57 (0.49–0.67)
0.68 (0.54–0.80)
0.84 (0.69–1.03)
224 (195–262)
95.8 (78.9–125.0)
1.9 + 0.4
54.3 + 13.0
0.61 (0.50–0.72)
0.69 (0.57–0.80)
0.84 (0.72–1.05)
232 (198–270)
Values are presented as the mean + SD, median (interquartile range), or percentage. Abbreviations as in Table 1.
,0.001
,0.001
,0.001
0.047
ns
ns
ns
236
optimal QTc interval cut-off level found by ROC curve analysis.
Difference in survival was calculated according to the log-rank
statistics.
We calculated QTc group differences, hazard ratios, and 95%
confidence intervals (CIs) with the Cox-proportional hazard
regression model, in both univariable and multivariable analyses.
Hazard ratios were used to estimate relative risks. A forward
stepwise analysis using 0.05 as entry probability and 0.10 as
removal probability was used in the adjusted analysis. Missing
values for blood pressure (n ¼ 11), LDL cholesterol (n ¼ 9), HDL
cholesterol (n ¼ 1), and BNP (n ¼ 1) were replaced by the mean
value for individuals with available measurements in the adjusted
analysis.
Pearson’s product moment correlation coefficient was used to
assess the association between variables.
A two-sided P-value of less than 0.05 was considered to be statistically significant. SPSS version 11.0 was used for statistical analysis.
Results
In all, 81 persons died during the 6.4 year follow-up. The
number of people who died of cardiovascular disease was
36 (ischaemic heart disease 12, other types of heart
disease 12, non-cardiac atherosclerotic disease 12). Among
the group with non-cardiac atherosclerotic diseases, seven
cases died of cerebrovascular disease.
The essential basal clinical characteristics of the patient
cohort are shown in Table 1.
The distribution of the QTc in the present cohort is
shown in Figure 1. The median (interquartile range) of QTc
was 415 (401–431) ms for all the participants in the study,
413 (401–428) ms for survivors, 425 (407–439) ms for nonsurvivors, 433 (416–450) ms for patients dying of cardiovascular disease, and 419 (402–436) ms for patients dying
of non-cardiovascular disease.
The area under the ROC curve, determining the sensitivity
and specificity of different lengths of QT interval to predict
survival, decreased steadily with time and was 0.716 after
Figure 1 Distribution of QTc interval length in 433 people, aged 75, comprising a randomly selected sample from the general population.
G. Nilsson et al.
1 year, 0.674 after 2 years, 0.647 after 5 years, and 0.614
(95% CI 0.543–0.684) after 6.4 years. At all these points in
time, this implies a significant deviation at the 0.001 level
from the null hypothesis that the true area under the ROC
curve is 0.5. The optimal cut-off point (maximum sum
of sensitivity and specificity) of QTc interval length for
predicting survival was found between 429 and 430 ms, at
both 5 and 6.4 years. All the QTc intervals were measured
to the nearest whole number (in ms), implying that this
classification corresponded to a dichotomization into
,430 ms/430 ms. Using 10-fold cross-validation, a specificity of 78%, a sensitivity of 41%, and a total misclassification rate of 29% were found at this QTc length.
A Kaplan–Meier curve for individuals with a QTc interval
above and below the cut-off point is shown in Figure 2.
The log-rank statistic was 15.57, one degree of freedom
(P , 0.001). As it is well known23 that left bundle
branch block, as opposed to right bundle branch block,
is associated with a dismal survival, we repeated the
analysis after exclusion of cases with left bundle branch
block (n ¼ 5). The log-rank statistic then was 15.02
(P , 0.001).
Restricting the analysis to cases with cardiovascular death
resulted in a Kaplan–Meier curve similar to that with total
mortality; log-rank statistic was 18.58 (P , 0.001). The corresponding P-value for non-cardiovascular deaths was 0.051,
with a better survival for patients with QTc intervals below
430 ms. There was no difference in survival between the
first and second tertiles of QTc. The third tertile
(QTc . 424 ms) differed significantly (log-rank statistic
10.30; P ¼ 0.001) from the first tertile by the Kaplan–Meier
analysis.
The relative risk was 2.4 (95% CI 1.5–3.7; P , 0.001) for
persons with a QTc 430 ms by comparison with persons
with shorter QTc interval.
Figure 2 Kaplan–Meier cumulative probability of survival by QTc length
dichotomized at 430 ms. Upper line 430 ms (n ¼ 115) and lower line
,430 ms (n ¼ 318).
QTc interval and survival in 75-year-old men and women
237
Combination of QTc and BNP determinations
Serum BNP is often determined in people with suspected
cardiac disease. Determination of the optimal cut-off point
for BNP in the same way as the determination of the cutoff point for QTc resulted in a cut-off point of 73 pg/mL (sensitivity 29%, specificity 89%). BNP .73 pg/mL in combination
with QTc . 430 ms delineated a group with 56% 6 year survival when compared with a 90% survival rate for patients with
QTc , 430 ms in combination with BNP ,73 pg/mL. The first
group comprised 7% and the latter group 68% of the participants in the study. Log-rank statistic by the Kaplan–Meier
analysis was 36.82 (P , 0.001).
Characteristics of participants with QTc above and
below 430 ms
In Table 2, some data, including echocardiographic, are
shown for patients with QTc ,430 ms and for those with
QTc of 430 ms or longer.
QTc and conventional risk factors
Univariable Cox-regression analysis of relative risks of death
associated with an increase of 1 SD in various risk factors
(Table 3) was performed in order to put the relationship of
QTc with survival into perspective. The length of the QTc
classified by the optimal cut-off between 429 and 430 ms
interval performed very well in predicting survival, in
comparison with conventional risk factors.
Forward stepwise Cox-regression analysis, including, in
addition to QTc, those conventional risk factors from
Table 3 that were significantly related to survival, yielded
the following significant variables in the final model: QTc
(P ¼ 0.004), HDL cholesterol (P ¼ 0.001), and LDL cholesterol (P ¼ 0.018). Relatively low serum levels of both HDL
and LDL cholesterol predicted dismal survival. Adding BNP
to the model resulted in the following variables as significant risk factors: QTc (P , 0.001), BNP (P , 0.001), HDL
(P ¼ 0.003), and LDL (P ¼ 0.024).
Table 3 Association between various risk factors and survival
according to the univariable Cox-regression analysis
Conventional risk factors
Systolic blood pressure
Diastolic blood pressure
LDL cholesterol
HDL cholesterol
Triglycerides
BMI
Cardiac risk factors
BNP
Left ventricular wall
motion index
LVEF
Left ventricular mass (m2)
QTc
Relative risk (95% CI)
P-value
0.92 (0.73–1.17)
0.93 (0.80–1.27)
0.77 (0.62–0.97)
0.62 (0.46–0.83)
1.07 (0.88–1.30)
0.88 (0.70–1.11)
ns
ns
0.027
0.001
ns
ns
1.30 (1.19–1.42)
0.70 (0.59–0.82)
,0.001
,0.001
0.61 (0.50–0.76)
1.42 (1.19–1.69)
1.40 (1.15–1.71)
,0.001
,0.001
0.001
Relative risk associated with an increase of 1 SD in the individual
variable.
QTc and echocardiographically determined indices
of left ventricular function
As indicated in Table 2, the length of QTc is closely
associated with echocardiographically determined left
ventricular wall-motion index, LVEF, and left ventricular
mass adjusted for body surface. Including these variables,
together with the significant variables (QTc interval, BNP,
HDL, and LDL) in a forward stepwise Cox-regression analysis,
yielded LVEF (P ¼ 0.002) and BNP (P ¼ 0.024) as significant
predictors of survival. It should be noted, however, that
this model included only 280 of 433 patients, because LVEF
could only be determined if at least 60% of the endocardial
border could be visualized.
Survival related to different heart rate correction
formulae for length of the QT interval
Hodges’ linear-correction formula [QTc ¼ QT þ 1.75(heart
rate 2 60)]14 is the heart rate correction in the Sicard analysis programme we used. The extensively used Bazett’s
formula (QTc ¼ QT/square root of RR)15 resulted in a
median value of 430 ms when compared with 415 ms using
Hodges’ formula.
Both QT intervals uncorrected for heart rate and QT
intervals corrected for heart rate by Hodges’, Bazett’s,
Fridericia’s, and Rautaharju’s formulae significantly predicted mortality (Table 4). Hodges’ formula showed the
highest value of relative risk.
Survival related to QRS and non-QRS (also called
JTc) components of the QTc interval
The QTc interval consists of two components: first the QRS
interval and then the non-QRS interval, usually known as
the JTc interval. These two components of the QTc interval
were analysed separately with regard to 6.4 year survival
(Table 4).
This table indicates that the QRS component of the QTc
interval is much more important for survival than the JTc
component of the QTc interval. The QTc interval was positively correlated with both QRS interval (P , 0.001) and
JTc interval (P , 0.001), with Pearson’s correlation coefficients 0.417 and 0.768, respectively. The QRS interval was
inversely correlated with the JT interval (r ¼ 20.261;
P , 0.001). A forward stepwise Cox-regression analysis,
including QRS and JTc, resulted in a model including both
these intervals, but with a higher significance for QRS
Table 4 Association between 6.4 year survival and QT corrected
for heart rate by different formulae as well as components of QTc
QT
Heart rate correction formulae
QTc (Hodges)
QTc (Bazett)
QTc (Fridericia)
QTc (Rautaharju)
Components of QTc (Hodges)
QRS
JTc
Relative risk (95%CI)
P-value
1.31 (1.05–1.64)
0.015
1.40 (1.15–1.71)
1.29 (1.06–1.58)
1.34 (1.10–1.65)
1.34 (1.10–1.64)
0.001
0.013
0.004
0.004
1.35 (1.14–1.61)
1.12 (0.91–1.39)
0.001
ns
Relative risk associated with an increase of 1 SD in the variable.
238
(P , 0.001) than for JTc (P ¼ 0.031). In the present investigation, the QRS component of the QTc interval is thus more
closely related to survival than the JTc component of the
QTc interval.
It is noteworthy that the ability of the QRS interval to
predict survival is approximately the same as that of the
QTc interval (Table 4). A forward stepwise Cox-regression
including these two intervals yielded practically the same
significance for QRS (P ¼ 0.035) as for QTc (P ¼ 0.029). No
relationship between heart rate and the QRS interval was
found.
Discussion
The QT interval is an indirect measure of the ventricular
action potential, including the depolarization and repolarization of the ventricular chambers. There is a physiological
relationship between increasing length of the QT interval
and increasing heart rate. This has led to the convention
of correcting the QT interval for heart rate by means of
various formulae prior to clinical evaluation of the interval.
There are some inherent problems when measuring the QT
interval on an ordinary 12-lead surface ECG, mainly
because of the difficulty in determining the end of the
T-wave and evaluating the U-waves.
Computerized QTc interval measurement
Several investigators have used computerized measurement
of the QTc interval. The computerized measurement in the
present investigation was developed by Macfarlane et al. 12
and is used in the Sicard system, which is an extensively
used computer-analysis programme. It was originally developed for the Siemens Elema ECG machine. At our department, the QTc intervals are shown on all paper printouts
of ordinary 12-lead surface ECGs. A thorough knowledge of
the clinical importance of the varying length of the QT interval is therefore of great value.
The present investigation demonstrates for the first time
the predictive power for survival of the QTc algorithm in
the Sicard computer-analysis programme.
G. Nilsson et al.
interval is determined at least in part by the activity of
the autonomic nervous system,26 and a relatively long QT
interval has been associated with sudden cardiac death
among diabetic patients with abnormal autonomic
function.27
In a clinical context, a QTc interval of 430 ms should
suggest further investigation with BNP and/or echocardiography. It must be noted that this figure is calculated by
Hodges’ formula and corresponds to 415 ms with Bazett’s
formula. In patients with advanced heart failure, Vrtovec
et al. 28 have observed a prognostic value of the combination
of QTc and BNP in excess of the value of QTc alone. This is
analogous to our observations in a general population.
In the present investigation, QTc has a much closer
relationship with systolic than with diastolic left ventricular
function. To our knowledge, data on the relationship
between QTc and diastolic function have not previously
been reported.
QTc and conventional risk factors
Information on the length of the computerized QTc interval
is easy to obtain and performs very well as a prognostic
instrument when compared with established risk factors
such as blood lipids and blood pressure. Systolic and
diastolic blood pressure, as well as triglycerides and
body-mass index failed to show a significant relationship
with survival, indicating that these traditional risk factors
have a reduced ability to predict prognosis in elderly
people. In the present study, the strongest conventional
risk factor in this age group was low HDL cholesterol; surprisingly, low LDL cholesterol is also a significant risk factor for
death in this age group and is not the good prognostic factor
that it is in younger people. An ECG with measurements of
QTc interval is therefore a simple and inexpensive method
for detecting high-risk individuals among the elderly. In
addition, the presence of a normal ECG according to the
Minnesota code is highly useful to predict left ventricular
systolic function as demonstrated by our group.20
Heart rate correction formulae
QTc interval and survival
The adverse prognostic importance of a relatively long QTc
interval has previously been demonstrated in the majority
of population-based studies.1,2,4,24 Conflicting results could
reflect imprecision in the measurement of the QTc interval,
a varying prevalence of cardiac disease at baseline and
different lengths of follow-up. It is essential to note that
the QTc interval increases with age.25 Our findings corroborate and extend previous work9 on the association between
the length of the QTc interval and survival in elderly people
from the general population. Studies of such a homogeneous
age group of elderly people from the general population
have not previously been reported.
The prognostic importance of the QTc interval probably
reflects structural abnormalities in the ventricular heart
muscle, most importantly reduced left ventricular systolic
function and increased left ventricular mass, which were
closely related to the length of the QT interval. The prognostic ability was practically unchanged after exclusion of
persons with left bundle branch block, which is known to
be associated with poor survival.23 Furthermore, the QTc
There have been many discussions about the best formula
for heart rate correction of the QT interval. The correction
method that best correlates with clinical outcome and survival is advantageous from a clinical point of view. Data that
relate clinical outcome to QT interval corrected by means
of different formulae have previously been reported by de
Bruyne et al. 9 The formulae tested by them included the
extensively used Bazett’s formula but not the linear
Hodges’ formula, which was used in the present investigation. They found that survival was hardly affected by
the heart rate correction formulae tested.
Our investigation indicates that the Hodges’ formula,14
which is routinely used in the Sicard 440/740 ECG
computer-analysis programme, performs well in comparison
with Bazett’s formula,15 which probably is the most extensively used formula for heart rate correction. The relationship between survival and QTc intervals, computed with
Hodges’ formula, has not previously been reported.
However, it must be noted that the relationship between
heart rate and the length of the QTc interval shows extremely
high interindividual variation.29
QTc interval and survival in 75-year-old men and women
Relative importance of the QRS and JTc components
of the QTc interval
QTc reflects the duration of both the QRS interval and the
JTc interval. In routine ECGs from a clinical institution,
Banker et al. 30 described a reciprocal relationship
between QRS and JTc in a general population, similar to
that observed by us.
The greater predictive value for survival of the QRS component of the QTc interval when compared with that of the
JTc component of the QTc interval is noteworthy and, to our
knowledge, it has not previously been reported for a general
population cohort. In actual fact, the QRS interval itself significantly predicts survival. QRS width has previously been
reported to be a prognostic factor in chronic heart
failure.31 In men with a QRS interval .120 ms, Crow
et al. 18 demonstrated a statistically significant predictive
value also of JTc for 13 year incident cardiovascular events
in a population-based prospective cohort.
The prognostic value of the QRS interval is of obvious clinical relevance. The QRS interval is more easily defined than
the QTc interval, and as opposed to the QTc interval, the
QRS complex is unaffected by heart rate.
Strengths and limitations of the study
The present investigation has some important strengths.
The uniform age of the participants prevented confounding
by age. Holter studies have demonstrated a diurnal variation in the QTc interval32 and our recording of the ECG at
the same time of the day (i.e. in the morning after at
least 10 min rest), thus facilitates the comparison of QTc
interval between different persons. People as old as 75
have previously only been studied to a very limited extent
with regard to the prognostic importance of the length of
the QTc interval. Our cohort is reasonably representative
of the general population, because as many as 70% of the
inhabitants in a restricted area participated in the study.
The investigation also offers unique data on the relationship
between QTc interval and diastolic filling patterns, as well
as on the relationship in elderly people between survival
and the QTc corrected by varying formulae. Furthermore,
data on the relative importance of the QRS and JTc components of the QTc interval have previously not been
reported.
A limitation in the present investigation is the relatively
small cohort, as well as the missing data, especially on ejection fraction determined echocardiographically according to
Simpson. This is, however, unavoidable because of the difficulty in defining the endocardial borders in many persons.
Furthermore, the present study does not evaluate the possibility that the relationship of QTc to survival reflects the
function of the autonomic nervous system.
Conclusion
In conclusion, the present investigation shows that the
length of the QTc interval is a valuable predictor of survival
in elderly men and women in the general population. The
computer-derived QTc is a simple and inexpensive method
of detecting high-risk individuals requiring special medical
attention in the general population.
239
Acknowledgements
This work was supported by grants from Västmanland’s research
foundation against cardiovascular disease and Sparbanksstiftelsen
Nya.
References
1. Goldberg RJ, Bengtson J, Chen ZY, Anderson KM, Locati E, Levy D.
Duration of the QT interval and total and cardiovascular mortality in
healthy persons (The Framingham Heart Study experience). Am J
Cardiol 1991;67:55–8.
2. Bednar MM, Harrigan EP, Anziano RJ, Camm AJ, Ruskin JN. The QT interval. Prog Cardiovasc Dis 2001;43:1–45.
3. Montanez A, Ruskin JN, Hebert PR, Lamas GA, Hennekens CH. Prolonged
QTc interval and risks of total and cardiovascular mortality and
sudden death in the general population: a review and qualitative overview of the prospective cohort studies. Arch Intern Med 2004;164:
943–8.
4. Dekker JM, Crow RS, Hannan PJ, Schouten EG, Folsom AR. Heart ratecorrected QT interval prolongation predicts risk of coronary heart
disease in black and white middle-aged men and women: the ARIC
study. J Am Coll Cardiol 2004;43:565–71.
5. Festa A, D’Agostino R Jr, Rautaharju P et al. Is QT interval a marker
of subclinical atherosclerosis in nondiabetic subjects? The Insulin
Resistance Atherosclerosis Study (IRAS). Stroke 1999;30:1566–71.
6. Lee SP, Yeoh L, Harris ND et al. Influence of autonomic neuropathy on QTc
interval lengthening during hypoglycemia in type 1 diabetes. Diabetes
2004;53:1535–42.
7. Macfarlane PW, McLaughlin SC, Devine B, Yang TF. Effects of age, sex,
and race on ECG interval measurements. J Electrocardiol 1994;
27(Suppl.):14–9.
8. Reardon M, Malik M. QT interval change with age in an overtly healthy
older population. Clin Cardiol 1996;19:949–52.
9. de Bruyne MC, Hoes AW, Kors JA, Hofman A, van Bemmel JH, Grobbee DE.
Prolonged QT interval predicts cardiac and all-cause mortality in the
elderly. The Rotterdam Study. Eur Heart J 1999;20:278–84.
10. Lauer MS, Blackstone EH, Young JB, Topol EJ. Cause of death in
clinical research: time for a reassessment? J Am Coll Cardiol 1999;
34:618–20.
11. Hedberg P, Lonnberg I, Jonason T, Nilsson G, Pehrsson K, Ringqvist I.
Left ventricular systolic dysfunction in 75-year-old men and women; a
population-based study. Eur Heart J 2001;22:676–83.
12. Macfarlane PW, Devine B, Latif S, McLaughlin S, Shoat DB, Watts MP.
Methodology of ECG interpretation in the Glasgow program. Methods
Inf Med 1990;29:354–61.
13. Willems JL, Abreu-Lima C, Arnaud P et al. The diagnostic performance of
computer programs for the interpretation of electrocardiograms. N Engl J
Med 1991;325:1767–73.
14. Hodges MSD, Erlien D. Bazett’s QT correction reviewed. Evidence that a
linear QT correction for heart rate is better. (Abstract). J Am Coll
Cardiol 1983;1:694.
15. Bazett H. An analysis of time relations of the electrocardiogram. Heart
1920;7:353–70.
16. Fridericia L. Die systolendauer im Elektrokardiogramm bei normalen
Menschen und bei Herzkranken. Acta Med Scand 1920;53:469.
17. Rautaharju PM, Manolio TA, Psaty BM, Borhani NO, Furberg CD. Correlates
of QT prolongation in older adults (the Cardiovascular Health Study).
Cardiovascular Health Study Collaborative Research Group. Am J
Cardiol 1994;73:999–1002.
18. Crow RS, Hannan PJ, Folsom AR. Prognostic significance of corrected QT
and corrected JT interval for incident coronary heart disease in a general
population sample stratified by presence or absence of wide QRS
complex: the ARIC Study with 13 years of follow-up. Circulation
2003;108:1985–9.
19. Blackburn H, Keys A, Simonson E, Rautaharju P, Punsar S. The electrocardiogram in population studies. A classification system. Circulation
1960;21:1160–75.
20. Hedberg P, Lonnberg I, Jonason T, Nilsson G, Pehrsson K, Ringqvist I.
Electrocardiogram and B-type natriuretic peptide as screening tools for
left ventricular systolic dysfunction in a population-based sample of 75year-old men and women. Am Heart J 2004;148:524–9.
21. Altman DG. Diagnostic tests. In: Altman DG, Machin D, Trevor NB,
Gardner M, eds. Statistics with Confidence. 2nd ed. BMJ Books; 2000.
p105–19.
240
22. Ciampi A, Zhang F. A new approach to training back-propagation artificial
neural networks: empirical evaluation on ten data sets from clinical
studies. Stat Med 2002;21:1309–30.
23. Fahy GJ, Pinski SL, Miller DP et al. Natural history of isolated bundle
branch block. Am J Cardiol 1996;77:1185–90.
24. Okin PM. QT interval prolongation and prognosis: further validation of the
quantitative approach to electrocardiography. J Am Coll Cardiol 2004;
43:572–5.
25. Dekker JM, Schouten EG, Klootwijk P, Pool J, Kromhout D. Association
between QT interval and coronary heart disease in middle-aged and
elderly men. The Zutphen Study. Circulation 1994;90:779–85.
26. Rosen MR, Jeck CD, Steinberg SF. Autonomic modulation of cellular repolarization and of the electrocardiographic QT interval. J Cardiovasc
Electrophysiol 1992;3:487–99.
27. Ewing DJ, Neilsson JM. QT interval length and diabetic autonomic neuropathy. Diabet. Med. 1990;7:23–6.
G. Nilsson et al.
28. Vrtovec B, Delgado R, Zewail A, Thomas CD, Richartz BM, Radovancevic B.
Prolonged QTc interval and high B-type natriuretic peptide levels
together predict mortality in patients with advanced heart failure.
Circulation 2003;107:1764–9.
29. Malik M, Farbom P, Batchvarov V, Hnatkova K, Camm AJ. Relation
between QT and RR intervals is highly individual among healthy subjects:
implications for heart rate correction of the QT interval. Heart 2002;
87:220–8.
30. Banker J, Dizon J, Reiffel J. Effects of the ventricular activation sequence
on the JT interval. Am J Cardiol 1997;79:816–9.
31. Shamim W, Francis DP, Yousufuddin M et al. Intraventricular conduction
delay: a prognostic marker in chronic heart failure. Int J Cardiol 1999;
70:171–8.
32. Molnar J, Zhang F, Weiss J, Ehlert FA, Rosenthal JE. Diurnal pattern of QTc
interval: how long is prolonged? Possible relation to circadian triggers of
cardiovascular events. J Am Coll Cardiol 1996;27:76–83.