High Prevalence of Altered Cardiac Repolarization in COPD
COPD patients 157 patients aged between 40 and 75 years with objectively confirmed COPD according to GOLD-guidelines were assessed for eligibility in the pulmonary outpatient clinic at the University Hospital of Zurich, Switzerland between October 2009 and January 2013. Patients were excluded if they had suffered from a COPD exacerbation within the last 6 weeks or if they suffered from mental or physical disability precluding informed consent or compliance with the protocol.
Matched control subjects The patient database of the Pulmonary Division of the University Hospital Zurich, Switzerland was screened for control subjects with normal lung function and matched for age, Pocock risk score use of beta blockers and medication affecting QT duration.
Healthy control subjects Subjects were eligible for the study if they were between 18 and 75 years old and healthy. Exclusion criteria were a previous diagnosis of any lung disease, arterial hypertension, any aortic or cardiac disease.
The study was conducted in accordance with the declaration of Helsinki of the World Medical Association. The Ethics Committee of the Canton of Zurich approved the study (EK-ZH-NR: 1734) and all subjects gave written informed consent to participate when data were obtained for research purposes.
Cardiovascular risk and medication The Pocock risk score was used to predict the individuals' 5-year risk of death due to a cardiovascular cause. The Pocock risk score is calculated from 11 known cardiovascular risk factors, including sex, age, smoking status, systolic blood pressure, cholesterol, creatinine, height, diabetes, previous myocardial infarction, stroke and left ventricular hypertrophy.
Patients and control subjects who were included in the study were asked if they used medications affecting the QT interval according to the International Registry of Drug-induced Arrhythmias maintained by the Georgetown University.
All participants underwent standard pulmonary functional testing according to American Thoracic Society guidelines to measure forced expiratory volume in one second (FEV1) and forced vital capacity (FVC).
Oxygen saturation (SaO2) was measured with a fingertip oximeter PC-60C after the participants rested 5min in supine position.
Patients and control subjects were asked to abstain from alcohol, tobacco, or caffeine on the day the measurements were performed. Room temperature and lighting were set at the same level for all measurements. The patients rested for five minutes in supine position before measurements were performed. For all electrocardiographic recordings a commercially available 12-lead ECG (AT 104 PC, Schiller-Reomed AG, Switzerland) was used and set at 25-mm/s paper speed and 10-mm/mV amplitude. Measurements of the ECG intervals were performed in duplicate with dedicated ECG analysis software (DatInf® Measure 2.1d, DatInf GmbH, Tübingen, Germany) by two investigators who were blinded to the patient's data as previously described. The mean of the ECG interval measurements by the two investigators was calculated and used for statistical analysis. Four consecutive heart cycles were analysed for each lead. The mean value for each lead of the twelve leads was calculated. Measures of cardiac repolarization were determined as indicated in Figure 1. The QT interval was defined as the time from the earliest onset of the QRS complex to the end of the T wave. The end of the T wave was defined as the cutting point of the tangent to the downward slope of the T-wave and the isoelectric line. As a measurement of dispersion of repolarization, QT dispersion was defined as the difference between the lead with the maximal and the lead with the minimal QT interval duration.
(Enlarge Image)
Figure 1.
The length of the QT interval was obtained by identifying the QRS onset and the point at which the downward slope of the T wave returns to baseline.
QTc (QT interval corrected for heart rate) was corrected for heart rate by using the Bazett formula.
All results are shown as mean values and standard deviation (SD) unless otherwise stated. Statistical analysis was performed with Statistica V6.0 (StatSoft, Tulsa, OK, USA) and STATA 12 (StataCorp, Texas, USA). Differences in QTc interval duration, cardiovascular risk factors, respiratory variables and use of medications between COPD patients, matched controls and healthy control subjects respectively were assessed by one-way ANOVA and χ tests. Kruskal Wallis test was used to compare QT dispersion between groups. Post hoc analysis was assessed for variables that showed a p-value of <0.1 across the three groups. For QTc, altered cardiac repolarization was defined as a value of >450ms and for QT dispersion of >60ms.
Univariate regression analysis was used to investigate associations between repolarization duration (dependent variable) and cardiovascular risk factors as well as respiratory variables and medications. Multivariate analysis involved regression of variables that showed a univariate regression p-value of <0.1 with adjustment for potential confounders (age). Residual analysis of the model was performed to check the regression assumptions. A two-sided p-value of <0.05 was considered to be statistically significant.
Methods
Subjects
COPD patients 157 patients aged between 40 and 75 years with objectively confirmed COPD according to GOLD-guidelines were assessed for eligibility in the pulmonary outpatient clinic at the University Hospital of Zurich, Switzerland between October 2009 and January 2013. Patients were excluded if they had suffered from a COPD exacerbation within the last 6 weeks or if they suffered from mental or physical disability precluding informed consent or compliance with the protocol.
Matched control subjects The patient database of the Pulmonary Division of the University Hospital Zurich, Switzerland was screened for control subjects with normal lung function and matched for age, Pocock risk score use of beta blockers and medication affecting QT duration.
Healthy control subjects Subjects were eligible for the study if they were between 18 and 75 years old and healthy. Exclusion criteria were a previous diagnosis of any lung disease, arterial hypertension, any aortic or cardiac disease.
The study was conducted in accordance with the declaration of Helsinki of the World Medical Association. The Ethics Committee of the Canton of Zurich approved the study (EK-ZH-NR: 1734) and all subjects gave written informed consent to participate when data were obtained for research purposes.
Measurements
Cardiovascular risk and medication The Pocock risk score was used to predict the individuals' 5-year risk of death due to a cardiovascular cause. The Pocock risk score is calculated from 11 known cardiovascular risk factors, including sex, age, smoking status, systolic blood pressure, cholesterol, creatinine, height, diabetes, previous myocardial infarction, stroke and left ventricular hypertrophy.
Patients and control subjects who were included in the study were asked if they used medications affecting the QT interval according to the International Registry of Drug-induced Arrhythmias maintained by the Georgetown University.
Respiratory Variables
All participants underwent standard pulmonary functional testing according to American Thoracic Society guidelines to measure forced expiratory volume in one second (FEV1) and forced vital capacity (FVC).
Oxygen saturation (SaO2) was measured with a fingertip oximeter PC-60C after the participants rested 5min in supine position.
Electrocardiography
Patients and control subjects were asked to abstain from alcohol, tobacco, or caffeine on the day the measurements were performed. Room temperature and lighting were set at the same level for all measurements. The patients rested for five minutes in supine position before measurements were performed. For all electrocardiographic recordings a commercially available 12-lead ECG (AT 104 PC, Schiller-Reomed AG, Switzerland) was used and set at 25-mm/s paper speed and 10-mm/mV amplitude. Measurements of the ECG intervals were performed in duplicate with dedicated ECG analysis software (DatInf® Measure 2.1d, DatInf GmbH, Tübingen, Germany) by two investigators who were blinded to the patient's data as previously described. The mean of the ECG interval measurements by the two investigators was calculated and used for statistical analysis. Four consecutive heart cycles were analysed for each lead. The mean value for each lead of the twelve leads was calculated. Measures of cardiac repolarization were determined as indicated in Figure 1. The QT interval was defined as the time from the earliest onset of the QRS complex to the end of the T wave. The end of the T wave was defined as the cutting point of the tangent to the downward slope of the T-wave and the isoelectric line. As a measurement of dispersion of repolarization, QT dispersion was defined as the difference between the lead with the maximal and the lead with the minimal QT interval duration.
(Enlarge Image)
Figure 1.
The length of the QT interval was obtained by identifying the QRS onset and the point at which the downward slope of the T wave returns to baseline.
QTc (QT interval corrected for heart rate) was corrected for heart rate by using the Bazett formula.
Data Analysis and Statistics
All results are shown as mean values and standard deviation (SD) unless otherwise stated. Statistical analysis was performed with Statistica V6.0 (StatSoft, Tulsa, OK, USA) and STATA 12 (StataCorp, Texas, USA). Differences in QTc interval duration, cardiovascular risk factors, respiratory variables and use of medications between COPD patients, matched controls and healthy control subjects respectively were assessed by one-way ANOVA and χ tests. Kruskal Wallis test was used to compare QT dispersion between groups. Post hoc analysis was assessed for variables that showed a p-value of <0.1 across the three groups. For QTc, altered cardiac repolarization was defined as a value of >450ms and for QT dispersion of >60ms.
Univariate regression analysis was used to investigate associations between repolarization duration (dependent variable) and cardiovascular risk factors as well as respiratory variables and medications. Multivariate analysis involved regression of variables that showed a univariate regression p-value of <0.1 with adjustment for potential confounders (age). Residual analysis of the model was performed to check the regression assumptions. A two-sided p-value of <0.05 was considered to be statistically significant.
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