Author + information
- Received September 28, 2011
- Revision received December 20, 2011
- Accepted January 3, 2012
- Published online April 17, 2012.
- Elsayed Z. Soliman, MD, MSc, MS⁎,⁎ (, )
- George Howard, DrPH†,
- Mary Cushman, MD, MSc‡,
- Brett Kissela, MD§,
- Dawn Kleindorfer, MD§,
- Anh Le, MS†,
- Suzanne Judd, PhD†,
- Leslie A. McClure, PhD† and
- Virginia J. Howard, PhD‖
- ↵⁎Reprint requests and correspondence:
Dr. Elsayed Z. Soliman, Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina 27157
Objectives The purpose of this study was to examine the association between prolongation of QT interval corrected for heart rate (QTc) with incident stroke.
Background Unlike cardiovascular morbidity and mortality, little is known about the relationship between QTc and risk of stroke.
Methods A total of 27,411 participants age 45 years and older without previous stroke from the REGARDS (REasons for Geographic and Racial Differences in Stroke) study were included in this analysis. QTc was calculated using Framingham formula (QTcFram). Stroke cases were identified and adjudicated during up to 8.2 years of follow-up (median, 5.1 years).
Results The risk of incident stroke in study participants with prolonged QTcFram was almost 3 times the risk in those with normal QTcFram (hazard ratio [HR] [95% confidence interval (CI)]: 2.88 [2.12 to 3.92], p < 0.0001). After adjustment for demographics (age, race, and sex), traditional stroke risk factors (antihypertensive medication use, systolic blood pressure, current smoking, diabetes, left ventricular hypertrophy, atrial fibrillation, and previous cardiovascular disease), warfarin use, aspirin use, QRS duration and use of QTc-prolonging drugs, the risk of stroke remained significantly high (HR [95% CI]: 1.67 [1.16 to 2.41], p = 0.0061) and was consistent across several subgroups of REGARDS study participants. Similar results were obtained when the risk of stroke was estimated per 1-SD increase in QTcFram, (HR [95% CI]: 1.12 [1.03 to 1.21], p = 0.0053 in multivariable-adjusted model) and when other QTc correction formulas including those of Hodge, Bazett, and Fridericia were used.
Conclusions QTc prolongation is associated with a significantly increased risk of incident stroke independent of traditional stroke risk factors. Examining the risk of stroke associated with QTc-prolonging drugs may be warranted.
The association between QT interval corrected for heart rate (QTc) and cardiovascular morbidity and mortality is well established (1–4). Little is known, however, about the relationship between this simple electrocardiographic (ECG) marker and incident stroke.
Prolonged QTc has been reported in 38% to 71% of patients during acute stroke, constituting the most frequent single ECG abnormality in this setting (5). The pathophysiology behind this phenomenon has not been elucidated. Autonomic dysregulation caused by overactivity of the sympathetic nervous system during acute stroke has been suggested as one of the potential mechanisms (6). Nevertheless, it is also possible that in some cases, prolonged QTc actually existed before the development of stroke, and its presence during the acute phase reflects its common presence in individuals at risk; hence, it could be used as a marker for future stroke. Further, prolonged QTc is associated with several cardiovascular disease (CVD) risk factors including advanced age, impaired glucose homeostasis, smoking, left ventricular hypertrophy (LVH), and high blood pressure (7,8), all of which are known risk factors for stroke. Therefore, it is plausible that QTc has prognostic value for prediction of future stroke. This contention is supported by a small study from Brazil that included 471 individuals with diabetes (9) and in a group from a general Japanese population (10), but no data exist from U.S. or European population-based studies.
We sought to examine the risk of incident stroke associated with prolongation of QTc in the REGARDS (REasons for Geographic and Racial Differences in Stroke) study. With its biracial population, centrally read ECG data, physician-adjudicated stroke events, and long-term follow-up, the REGARDS study provides a unique opportunity to address our research questions.
The goals and design of the REGARDS study were published elsewhere (11). Briefly, the study was designed to investigate the causes of regional and racial disparities in stroke mortality, oversampling blacks and residents of the southeastern stroke belt region (North Carolina, South Carolina, Georgia, Alabama, Mississippi, Tennessee, Arkansas, and Louisiana). Individuals were recruited from a commercially available list of residents using a combination of postal and telephone contact with a 49% cooperation rate. Using a computer-assisted telephone interview, trained interviewers obtained demographic information and a cardiovascular medical history. Consent was obtained initially on the telephone and subsequently in writing during an in-person evaluation. In-home brief physical examinations were conducted 3 to 4 weeks after the telephone interview. Participants are followed every 6 months by telephone for possible stroke outcomes.
Of the 30,239 REGARDS participants enrolled between 2003 and October 2007, we excluded 1,930 participants reporting previous stroke, 359 with no or poor quality ECG data, and 539 with no follow-up data, resulting in 27,411 (91%) participants for analysis.
The institutional review boards of each participating center reviewed and approved the study methods.
QT interval corrected for heart rate
Baseline resting electrocardiograms were recorded during in-home visits. ECG tracings were mailed for reading and coding at a central electrocardiography core laboratory located at the Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winson-Salem, North Carolina. To calculate QTc from the uncorrected QT and heart rate, we followed the recommendations of the American Heart Association, American College of Cardiology, and Heart Rhythm Society for the Standardization and Interpretation of the Electrocardiogram (12). In this context, we used the Framingham linear regression formula: [QTcFram = QT + 154 (1 − 60/heart rate)], where QTcFram is QTc calculated using the Framingham formula (13). QTcFram values of ≥460 ms in women and ≥450 ms in men were considered abnormal (i.e., prolonged QTcFram) (12). As secondary analysis to confirm the results and to provide comparability with previous studies, we also used other traditional QTc correction methods including those of Hodge (14) [QTcHod = QT + 1.75 (heart rate − 60)], where QTcHod is QTc calculated using the Hodge formula; Bazett (15) [QTcBaz= QT (heart rate/60)1/2], where QTcBaz is QTc calculated using the Bazett formula; and Fridericia [QTcFrid = QT (heart rate/60)1/3], where QTcFrid is QTc calculated using the Fridericia formula (16).
Report of a possible stroke/transient ischemic attack or a positive response to the stroke symptoms on the Questionnaire for Verifying Stroke-Free Status (17), resulting in hospitalization, during follow-up generated a request for retrieval of medical records that were centrally adjudicated by a panel of stroke expert physicians. Stroke events were defined according to the World Health Organization definition as “rapidly developing clinical signs of focal, at times global, disturbance of cerebral function, lasting more than 24 hours or leading to death with no apparent cause other than that of vascular origin” (18). Events not meeting the World Health Organization definition but characterized by symptoms lasting <24 h with neuroimaging consistent with acute ischemia or hemorrhage were classified as clinical strokes. Strokes were further classified as ischemic or hemorrhagic. This analysis included World Health Organization–defined as well as clinical ischemic or hemorrhagic fatal and nonfatal stroke cases. As secondary analysis, we used ischemic stroke only excluding hemorrhagic strokes. Further details on stroke identification and adjudication in the REGARDS study are available elsewhere (19).
Standardized physical measures that included height, weight, and blood pressure were collected at the in-home physical examination. Demographics (age, sex, and race) were defined by self-report. Traditional stroke risk factors were selected based on the components of the Framingham Stroke Risk Score, which includes antihypertensive medication use, systolic blood pressure, current smoking, diabetes, LVH, atrial fibrillation (AF), and previous CVD (20). History of stroke was defined by self-report of a physician diagnosis, and previous CVD was similarly defined by self-report (myocardial infarction or heart attack, coronary artery bypass surgery, coronary angioplasty, or stenting) or by ECG evidence of a previous myocardial infarction. LVH was defined using the electrocardiographic Sokolow-Lyon criteria (21). AF was defined based on ECG diagnosis and/or self-report of a previous physician diagnosis, as detailed elsewhere (22). Use of antihypertensive medications, current warfarin treatment, aspirin use, and use of QTc-prolonging drugs were defined using an inventory of current medications that was conducted during the in-home visits; all prescription and over-the-counter medications taken in the past 2 weeks were recorded.
Frequency distributions of all variables were first inspected to identify anomalies and outliers possibly caused by measurement artifacts. Continuous data were described by their mean and SD and categorical data as proportions (percentage). Differences in characteristics by QTc-prolongation status were assessed by chi-square (for categorical variables) and unpaired t (for continuous variables) tests.
Cox proportional hazards analysis was used to estimate the hazard ratios (HRs) for incident stroke associated with QTcFram per 1-SD increase, as well as prolonged versus normal, separately, in a series of incremental models as follows: first unadjusted (model 1); then adjusted for demographics (age, sex, and race) (model 2); then additionally adjusted for traditional stroke risk factors (antihypertensive medication use, systolic blood pressure, current smoking, diabetes, LVH, AF, and previous CVD) (model 3); and finally additionally adjusted for QRS duration, QTc-prolonging drugs, warfarin use, and aspirin use (model 4). The assumptions of the Cox proportional hazards models were examined by plotting the natural log of the cumulative hazard of stroke by the natural log of time. Multiple imputation techniques for incident stroke were used in the analysis to reduce the potential bias introduced through either failure to retrieve medical records or from records remaining in the adjudication process at the time of analysis. Additional details of the application of multiple imputation techniques in the REGARDS study are provided elsewhere (23).
Secondary analyses included: 1) examining the association between QTcFram and incident stroke across different subgroups of the study participants stratified by age, sex, race, smoking status, hypertension, diabetes, LVH, previous CVD, AF, and QRS duration; 2) examining interaction between each of sex and race with QTcFram for prediction of stroke; 3) using ischemic stroke only as an outcome instead of both ischemic and hemorrhagic; and finally 4) using QTcHod, QTcBaz, and QTcFrid, separately, instead of QTcFram in the proportional hazards models.
At baseline, the average QTcFram interval duration was 407 ± 23 ms, with 740 of the participants (2.7%) having prolonged QTcFram. Table 1 shows the characteristics of the study population, overall and stratified by presence of prolonged QTcFram. Compared with those with normal QTcFram, participants with prolonged QTcFram were older, with fewer blacks and more males. Previous CVD, diabetes, AF, LVH, and use of QTc-prolonging drugs were more prevalent in the prolonged QTcFram group.
During up to 8.2 years of follow-up (median 5.1 years), 608 total strokes occurred, of which 491 were ischemic strokes. Stroke developed in ∼5.4% of participants with prolonged QTcFram compared with only 2.8% of those with normal QTcFram (p < 0.0001). Figure 1 shows the event-free survival curves of participants with and without prolonged QTcFram.
As shown in Table 2, for every 1-SD increase in QTcFram, there was 24% increase in the risk of incident stroke (HR [95% confidence interval (CI)]: 1.24 [1.16 to 1.33], p < 0.0001). This association remained statistically significant after adjustment for demographics, traditional stroke risk factors, warfarin use, aspirin use, QRS duration, and use of QTc-prolonging drugs (HR [95% CI]: 1.12 [1.03 to 1.21], p = 0.0053). Similar results were observed when QTcHod, QTcBaz, and QTcFrid separately were used instead of the QTcFram in the proportional hazards models (Table 2).
The risk of stroke in study participants with prolonged QTcFram was almost 3 times the risk in those with normal QTcFram (HR [95% CI]: 2.88 [2.12 to 3.92], p < 0.0001). After adjustment for demographics, traditional stroke risk factors, warfarin use, aspirin use, QRS duration, and use of QTc-prolonging drugs, the risk of stroke remained significantly high (HR [95% CI]: 1.67 [1.16 to 2.41], p = 0.0061). Similar results were observed in the unadjusted and demographics-adjusted models of the QTcHod, QTcBaz, and QTcFrid. However, after further adjustment for stroke risk factors, warfarin use, aspirin use, QRS duration, and use of QTc-prolonging drugs, the HRs associated with QTcBaz were no longer statistically significant and were marginal with QTcHod (Table 2).
Figure 2 shows the multivariable-adjusted HRs for incident stroke associated with prolonged versus normal QTcFram in several subgroups of REGARDS study participants stratified by age, race, sex, smoking status, hypertension, diabetes, LVH, AF, and QRS duration. As shown, in a model adjusted for demographics, traditional stroke risk factors, warfarin use, aspirin use, QRS duration, and use of QTc-prolonging drugs, prolonged QTcFram (vs. normal) was consistently associated with significantly increased stroke risk across all subgroups with nonsignificant probability values for interaction.
Demographics adjusted uncorrected QT was marginally predictive of incident stroke (HR [95% CI]: 1.08 [1.00 to 1.16], p = 0.0446 for every 1-SD increase; 1.40 [1.01 to 1.93], p = 0.0423] for prolonged vs. normal). However, these associations were no longer significant after further adjustment for traditional stroke risk factor (HR [95% CI]: 1.06 [0.99 to 1.15], p = 0.1122 for every 1-SD increase and 1.21 [0.86 to 1.70], p = 0.2709 for prolonged vs. normal) and further adjustment for warfarin use, aspirin use, QRS duration, and use of QTc-prolonging drugs (HR [95% CI]: 1.06 [0.98 to 1.15], p = 0.1575 for every 1-SD increase; 1.19 [0.84 to 1.68], p = 0.3367 for prolonged vs. normal). Similarly, in models similar to those used for QTc, heart rate alone was not predictive of stroke after adjusting for traditional stroke risk factors (HR [95% CI]: 1.04 [0.96 to 1.12], p = 0.3309 for every 1-SD increase; 0.97 [0.81 to 1.15), p = 0.7021 for abnormal vs. normal [60 to 90 beats/min]) and further adjustment for warfarin use, aspirin use, QRS duration, and use of QTc-prolonging drugs (HR [95% CI]: 1.04 [0.96 to 1.12], p = 0.3886 for every 1-SD increase, and 0.97 [0.81 to 1.15], p = 0.7182 for abnormal vs. normal [60 to 90 beats/min]).
There were no meaningful differences in the observed patterns of associations assessing ischemic stroke only (data not shown). Also, there was no significant interaction between each of sex and race subgroups with QTcFram for prediction of stroke in the fully adjusted models.
In this analysis from a national, U.S. general population, we showed that QTc prolongation is associated with a significantly increased risk of incident stroke independent of traditional stroke risk factors and consistently across different demographic and clinical subgroups. These findings add further concern regarding the consequences of QTc prolongation. In addition to increased cardiovascular morbidity and mortality (1–4), stroke seems to be another serious outcome. With the increasing number of QTc-prolonging drugs (24) and in light of our results, examining the risk of stroke associated with QTc-prolonging drugs may be warranted. To our knowledge, no previous studies examined the association between QTc-prolonging drugs and stroke. Nevertheless, the PALLAS (Permanent Atrial Fibrillation Outcome Study Using Dronedarone on Top of Standard Therapy) trial (25) gives an indirect clue of a possible link between QTc-prolonging drugs and risk of stroke. In the PALLAS trial, stroke occurred in 23 patients in the dronedarone group and in only 10 in the placebo group (HR [95% CI]: 2.32 [1.11 to 4.88], p = 0.02). Although it was not clear how many of the stroke cases in the PALLAS trial could be explained by the QTc prolonging effect of dronedarone, it has been noticed that after 1 month of treatment, there was 8 ± 40 ms increase in the QTc duration in the dronedarone group versus 2 ± 38 ms in the placebo group (p < 0.001), which is in accord with the known QTc-prolonging properties of dronedarone. In contrast to the PALLAS trial results, however, the ATHENA (A placebo-controlled, double-blind, parallel arm Trial to assess the efficacy of dronedarone 400 mg bid for the prevention of cardiovascular Hospitalization or death from any cause in patiENts with Atrial fibrillation/atrial flutter) trial showed that dronedarone was associated with a lower stroke risk (26). Whether this discrepancy between PALLAS and ATHENA could be explained by the type of AF (being permanent in PALLAS and paroxysmal in ATHENA) or by differences in the QTc-prolongation is just a speculation at this stage. Another clue of a potential link between QTc-prolonging drugs and risk of stroke comes from our study. In an additional analysis, we observed a 19% increase in the risk of stroke in participants taking QTc-prolonging drugs compared with those not taking these drugs, after adjusting for age, sex, and race (HR [95% CI]: 1.19 [0.99 to 1.42], p = 0.059). However, this needs to be investigated further in a study designed specifically to address this question.
Two previous studies (9,10), 1 from Brazil on diabetic population and 1 from Japan, showed a significant relationship between prolongation of QTc and incident stroke, which is in accord with our results. However, both studies did not include whites (Caucasians) or blacks (African Americans), used only the debatable Bazett formula for calculating QTc, and at least 1 of them was lacking data on AF, smoking status, and/or QTc-prolonging drugs, which makes it difficult to reach a convincing conclusion.
In our analysis, the association between QTc and stroke remained highly significant despite adjustment for traditional stroke risk factors. Noteworthy, we decided a priori to focus on traditional stroke risk factors (i.e., components of the Framingham Stroke Risk Score) and major potential confounders. Nevertheless, in an additional analysis, we added other possibly related risk factors to model 4 including family history of CVD, chronic kidney disease, and hypertension (as a categorical variable in addition to systolic blood pressure and antihypertensive medications, which were already included in model 4). Further adjustment for these variables did not result in any significant change in the risk estimates (results not shown). This means that the association of QTc with CVD risk factors does not fully explain the prognostic significance of QTc as a stroke predictor. It is possible, however, that prolonged QTc interval is a marker of silent undetected atherosclerotic vascular disease (9). In 1 study, QTc was significantly associated with carotid intima media thickness (27) and in another study with activated factor XII levels (28). In both studies, the associations of QTc with these markers of atherosclerotic vascular disease remained significant after adjustment for other CVD risk factors. This reinforces the hypothesis that QTc prolongation may be a surrogate indicator of subclinical atherosclerosis and subsequently can be predictive of future atherosclerotic vascular events such as stroke. Studies aimed at clarifying the mechanism by which QTc is predictive of stroke are needed. Interestingly, the mechanistic relationship between stroke and LVH (which is one of the well-established traditional stroke risk factors) is unclear as well. All that we know is that LVH is associated with several CVD risk factors (which is the same situation with QTc). Therefore, what has been stated about LVH and risk of stroke (29) may also be applicable to QTc; that is, “it is not yet entirely clear whether LVH (or QTc in our case) represents a marker, a limited adaptive process or a pathological process.”
The QT interval is heart rate dependent; the faster the heart rate is, the shorter the QT interval and vice versa. Therefore, using QTc rather than the uncorrected QT interval is mandatory. This is further supported by our findings of a lack of significant stroke risk with uncorrected QT interval while observing a strong association with QTc. Many formulas have been proposed to calculate QTc from the uncorrected QT interval and heart rate. The most widely used is the nonlinear formula of Bazett (15). However, recent guidelines of ECG standardization and interpretation (12) recommend using linear regression formulas, avoiding nonlinear formulas, especially that of Bazett, and incorporating QRS duration in the models. Subsequently, we decided to use QTcFram and adjust for QRS duration in the full model. Nevertheless, to confirm our results and to provide comparability with other studies, we also used 3 other QTc formulas including the traditional QTcBaz, and the results were largely consistent. We also examined the association between heart rate and stroke in models similar to those we used for QTc, and we did not find significant associations. This precludes the possibility that the observed association between QTc and stroke was driven by heart rate.
As shown, the risk of stroke associated with 1-SD increase in QTc was consistent across the 4 QTc correction formulas that we used in our study. However, when we examined the risk of stroke associated with prolonged QTc (vs. normal), QTcBaz was not as significantly predictive as other formulas in the multivariable models. This observation is in accord with the current general agreement that QTcBaz can erroneously estimate QTc, which could affect its prognostic significance (12). In our study the prevalence of prolonged QTc (defined as QTc ≥460 ms in women and ≥450 ms in men) was approximately 5% with the Bazett formula and between 2.7% and 3% with the other 3 formulas. This means that at least 2% of our study participants were misclassified as having prolonged QTc by the Bazett formula, which might have led to the null findings that we observed with QTcBaz. The lack of strong prognostic significance of QTcBaz compared with the other QTc formulas supports the explicit recommendation of the current guidelines to avoid using the Bazett formula (12). Nevertheless, because the prognostic significance of QTcBaz as a continuous variable (i.e., per 1-SD increase) was as good as other QTc formulas, using different (possibly higher cut points) to define prolonged QTcBaz may improve its prognostic significance. In other words, our findings suggest that the cut points defining prolonged QTc need to be formula specific to avoid masking important relationships. Examining the impact of differences in the cut points that define prolonged QTc on the prognostic significance is beyond the scope of this paper, which is the reason we decided to use the cut points suggested by the current guidelines (12).
Only whites and blacks were included in the REGARDS study; hence, our results may not be applicable to other racial/ethnic groups. We could not differentiate between congenital and acquired (drug-induced) QTc prolongation. Nevertheless, given the age of REGARDS study population acquired QTc prolongation is a more likely etiology.
It remains possible that AF was underdetected in some cases. Because the antiarrhythmic drugs used in AF can often prolong the QT interval, 1 potential explanation for these findings may have been that more participants with undetected/unreported AF had drug-induced prolongation of QTc and subsequently an increased risk of stroke. However, given that AF in our study was ascertained by 2 methods (self-report of a previous physician diagnosis and study scheduled ECG; both have similar stroke predictive value ), most of AF cases must have been captured. Also, we adjusted for QTc-prolonging drugs in our analysis, which preclude the possibility of the confounding effect of antiarrhythmic drugs with QTc-prolonging properties.
Data on the use of medications (from which we identified QTc-prolonging drugs) is based on review of pill bottles brought by participants during the study baseline. Reporting medications by the participants may have been incomplete or may have changed before the incident event leading to misclassification. However, such inaccuracies or misclassification should be randomly distributed across groups and should not affect the overall conclusions.
Despite these limitations, this is the first report examining the relationship between QTc prolongation and risk of stroke in one of the largest biracial, population-based, longitudinal cohort studies in the United States, the REGARDS study. Other strengths include central ECG reading, using multiple QTc correction formulas to confirm the results, and the substantial accumulating number of physician-adjudicated stroke events.
Prolongation of QTc is associated with a significantly increased risk of incident stroke independent of traditional stroke risk factors. These findings suggest that important predictive information may be derived from such a simple ECG marker. With the increasing number of QTc-prolonging drugs and in light of our results, examining the risk of stroke associated with QTc-prolonging drugs may be warranted.
The authors thank the investigators, staff, and participants of the REGARDS study for their valuable contributions. A full list of participating REGARDS investigators and institutions can be found at http://www.regardsstudy.org.
The REGARDS study is supported by a cooperative agreement U01 NS041588 from the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Department of Health and Human Services. Dr. Kissela has received speaker honoraria from Allergan. Dr. Kleindorfer is on the speaker's bureau of Genentech. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Abbreviations and Acronyms
- atrial fibrillation
- confidence interval
- cardiovascular disease
- hazard ratio
- left ventricular hypertrophy
- QT interval corrected for heart rate
- QT interval corrected for heart rate using the Bazett formula
- QT interval corrected for heart rate using the Framingham formula
- QT interval corrected for heart rate using the Fridericia formula
- QT interval corrected for heart rate using the Hodge formula
- Received September 28, 2011.
- Revision received December 20, 2011.
- Accepted January 3, 2012.
- American College of Cardiology Foundation
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