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Original Research: COPD |

Relation Between COPD Severity and Global Cardiovascular Risk in US AdultsGlobal Cardiovascular Risk in COPD FREE TO VIEW

Hwa Mu Lee, MD, FCCP; Janet Lee, BS; Katherine Lee; Yanting Luo, MS; Don D. Sin, MD, FCCP; Nathan D. Wong, PhD
Author and Funding Information

From the Heart Disease Prevention Program (Drs Lee and Wong and Mss J. Lee, K. Lee, and Luo), Division of Cardiology, School of Medicine, and Division of Pulmonary Medicine (Dr Lee), Department of Medicine, University of California, Irvine, CA, and The James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research (Dr Sin), St. Paul’s Hospital, Vancouver, BC, Canada.

Correspondence to: Hwa Mu Lee, MD, FCCP, Heart Disease Prevention Program, 112 Sprague Hall, University of California, Irvine, CA 92697-4101; e-mail: leehwamumd@gmail.com


Funding/Support: The authors have reported to CHEST that no funding was received for this study.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2012;142(5):1118-1125. doi:10.1378/chest.11-2421
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Background:  COPD is associated with the risk of cardiovascular events (CVEs), but its impact on overall mortality has not been well quantified. We determined the impact of global CVE risk assessment on CVE and total mortality in subjects with COPD.

Methods:  We examined the severity of COPD in 6,266 US adult patients aged ≥ 40 years in relation to the estimated 10-year risk of CVEs. COPD was defined by spirometry, and severity was classified as mild (FEV1 ≥ 80%), moderate (50% ≤ FEV1 < 80%), or severe (FEV1 < 50%). Cox proportional hazards regression was used to evaluate the relationship of global CVE risk combined with COPD status to CVE and all-cause mortality over a mean follow-up of 98.8 ± 51.3 months.

Results:  The proportion of individuals at high risk for CVEs ranged from 25% (without COPD) to > 50% (with moderate to severe COPD) (P < .05). When global CVE risk scores were low, CVE mortality was also low (< 10/1,000 person-years) regardless of COPD severity, and CVE mortality was high when CVE global risk was high (> 40/1,000 person-years). Global CVE risk improved prediction for both CVEs and total mortality in patients with COPD (P < .0001), with a net reclassification improvement of 17.1% (P < .0001) and 13.0% (P < .0001), respectively, beyond lung function measures.

Conclusions:  The addition of global CVE risk scores to lung function data significantly improves risk stratification of patients with COPD for CVE and total mortality and, thus, adds to predicting long-term survival of these patients.

Figures in this Article

COPD affects an estimated 64 million people worldwide and is now the third leading cause of death in the United States.15 There is a close connection between COPD and cardiovascular events (CVEs), with each condition complicating the prognosis of the other.2,6 For instance, among 4,284 patients with coronary heart disease, patients with COPD were found to have a 3-year mortality rate that was more than double that of patients without COPD (21% vs 9%).6 In another large cohort study, those with vs without COPD were two to four times more likely to die of a CVE over 3 years of follow-up.7 A longitudinal, population-based study of 1,861 participants from National Health and Nutrition Examination Survey I reported that reduced FEV1 was a marker for CVE mortality.8 Thus, we hypothesized that by accurately quantifying CVE risk, we will be able to better predict long-term CVE and total mortality of patients with COPD.

One well-accepted and validated tool for CVE risk estimation is the Framingham Risk Score (FRS).9,10 Although very easy to use even in a busy clinical setting, this global risk assessment instrument is rarely used in patients with COPD. One reason is that there is a paucity of data relating global CVE risk scores with COPD.11 The aims of the present study were to determine the relationship of global CVE risk to COPD and whether global CVE risk assessment significantly improves risk prediction beyond lung function for CVE and total mortality in patients with COPD.

Study Sample

We used data from 6,266 individuals (projected to 66.8 million) aged ≥ 40 years who participated in the National Health and Nutrition Examination Survey III (1988-1994) in whom spirometry and CVE risk factor data were available and who did not have asthma (self-reported or physician diagnosed). The clinical and demographic data of these patients were then linked with National Death Index-linked mortality data through 2006. CVE mortality was defined by International Classification of Diseases, Ninth Revision, codes 390 to 460, and lung-related mortality was defined by codes 18, 33, 162, 466, and 480 to 519. There was no patient interaction. All data were publicly available and, thus, were exempt from review by our institutional review board.

Definition of CVE and Measurement of Risk Factors and Global Risk

We defined prevalent CVE based on physician diagnosis of myocardial infarction, stroke, or heart failure on the baseline assessment. Family history of CVE was determined to be present if immediate relatives of the patients had a heart attack before age 50 years. Measures of systolic and diastolic BP were defined from the average of up to six measurements (three each at the end of the home interview and at the medical examination).12 Low-density lipoprotein cholesterol was calculated using the direct value or from the Friedwald equation (low-density lipoprotein cholesterol = total cholesterol − high-density lipoprotein cholesterol [HDL-C] − 1/5 triglycerides) if the triglyceride values were < 400 mg/dL. HDL-C levels were measured through a precipitation method with a heparin-manganese chloride mixture on a Hitachi 704 Analyzer (Roche Diagnostics, Inc). Total cholesterol and triglycerides were measured enzymatically after hydrolyzation to glycerol on the Hitachi 704 Analyzer. BP was measured with a mercury sphygmomanometer over an average of four readings. The global risk score for total CVEs was obtained using the D’Agostino equation, which includes age, sex, total cholesterol, HDL-C, systolic BP and treatment of hypertension, history of smoking, and diabetes (fasting glucose of ≥ 126 mg/dL or ≥ 200 mg/dL if not fasting).9 Global risk was categorized as low (< 10%), intermediate (10%-20%), or high (> 20%) in patients without prevalent CVE. Regardless of the global risk score, all patients with prevalent CVE were categorized into a very-high-risk group.

Spirometry and Definition of COPD

Each patient was asked to perform at least five FVC maneuvers, with an additional goal of meeting the American Thoracic Society (ATS) acceptability and reproducibility criteria.13 FEVs were measured using a dry rolling-seal spirometer. The spirometer used a digital shaft encoder to measure volume, with a volume resolution of 2.6 mL and a sampling interval of 10 milliseconds. All of the digital volume-time curves were saved on digital tape (as much as 20 s of exhalation), allowing recalculation of all parameters and test performance regarding ATS acceptability and reproducibility criteria. The spirometry system was independently tested and exceeded the ATS spirometry equipment recommendations.14 The 1979 and updated 1987 National Institute for Occupational Safety and Health and ATS spirometric system measures were used, which follow the recommendations of the American Heart Association. Expected FVC values were determined using equations develop by Hankinson et al.1416 From prebronchodilator spirometric data, we used FEV1 and FEV1/FVC ratios for categorizing patients with COPD.17 Of those with a FEV1/FVC < 70%, severities were categorized as mild (FEV1 ≥ 80%), moderate (50% ≤ FEV1 ≤ 80%), or severe (FEV1 < 50%) (GOLD [Global Initiative for Chronic Obstructive Lung Disease] criteria).

Statistical Analyses

The χ2 test and analysis of variance were performed to compare proportions and means of risk factors, respectively, between patients with and without COPD and across severity of COPD. The χ2 test of proportions compared the distribution of CVE risk groups across COPD severity. Unadjusted bivariate logistic regression was performed to determine the relationship between the presence of COPD and the global CVE risk groups. For all these analyses, the low global risk group was the reference. We also calculated the total mortality rate per 1,000 person-years for all COPD severity groups, stratified by CVE global risk. Logistic regression was used to examine risk factors common to both CVE and COPD. Cox proportional hazards regression was performed to calculate hazard ratios adjusted for possible confounders in the relationship among global risk groups, COPD severity, and mortality. The area under the curve (C statistic) was obtained by calculating receiver operating characteristic statistics using STATA 10 (StataCorp LP) in models with COPD alone and after the inclusion of global CVE risk groups. We also calculated a net reclassification improvement (NRI) value, which evaluates the proportion of individuals who with the addition of the global CVE risk groups were correctly reclassified (eg, patients who subsequently died would be reclassified into a higher risk group). This value, if sufficiently large, confirms the improvement between the two models in question. The cutoff points were 0.05 (ie, 5%), 0.1 (10%), and 0.6 (60%).18 SAS version 9.0.3 (SAS Institute Inc) and SUDAN version 9.0.1 (RTI International) were used for statistical analysis as well as to obtain computations of weighted estimates for projection to the US population.

The prevalence of mild, moderate, and severe COPD was 12.1%, 8.7%, and 1.7%, respectively. Patients with vs without COPD had a higher mean age, systolic BP, history of smoking, and FRS, and those with severe COPD were more likely to have a family history of CVEs. They were also more likely to belong to intermediate and high global risk groups and to die of pulmonary events and CVEs. With increasing severity of COPD, FEV1, FEV1/FVC, and diastolic BP, the proportion of patients at low global risk and the proportion of women decreased, whereas the proportion with elevated C-reactive protein (CRP) levels increased (Table 1). Although it was also observed that HDL-C levels were higher in patients with severe COPD compared with the COPD categories, when adjusting for age, sex, and BMI, this difference was no longer significant.

Table Graphic Jump Location
Table 1 —Lung Function, Demographic and Cardiovascular Risk Factor Measures, and Mortality End Points According to Severity of COPD

Data are presented as mean ± SD or % (No.), unless otherwise indicated. CRP = C-reactive protein, CVE = cardiovascular event; HDL = high-density lipoprotein, LDL = low-density lipoprotein.

Among patients without COPD, one-half (50.8%) had low global CVE risk and one-fourth (24.5%) were at intermediate risk. The proportions of patients at intermediate risk were lower, whereas the proportion at high risk progressively increased with greater COPD severity. In those with moderate or severe COPD, more than one-half had high or very high global risk (P < .0001) (Fig 1).

Figure Jump LinkFigure 1. Distribution of global risk groups according to severity of COPD (P < .0001). FRS = Framingham Risk Score.Grahic Jump Location

In an unadjusted logistic regression analysis, patients with intermediate global risk (compared with low global risk) were 2.5 times more likely to also have COPD (P = .02); those who had high global risk were 4.5 times more likely to have COPD (Fig 2). Figures 3 and 4 show a progressive increase in CVE and total mortality per 1,000 person-years across different severity categories of COPD among patients with higher global risk.

Figure Jump LinkFigure 2. ORs for COPD across varying global risk groups. The reference group was the low global risk group and was set to equal 1 (intermediate vs low risk, P < .05; high vs low risk, P < .0001; very-high risk vs low risk, P < .0001). Bar lines indicate 95% CI.Grahic Jump Location
Figure Jump LinkFigure 3. CVE mortality per 1,000 person-y across global FRS risk group within each COPD group (P < .0001) across all groups. CVE = cardiovascular event. See Figure 1 legend for expansion of other abbreviation.Grahic Jump Location
Figure Jump LinkFigure 4. Total mortality per 1,000 person-y by global FRS risk group within each COPD group (P < .0001). See Figure 1 legend for expansion of abbreviation.Grahic Jump Location

From logistic regression examining possible overlapping risk factors for both prevalent COPD and CVE, age (P = .0205), CRP level (P = .0120), and smoking status (P = .0010) were associated with COPD. Age (P = .0015), CRP level (P = .0023), total cholesterol level (P = .0012), diastolic BP (P = .0101), and sex (P = .0001) were associated with prevalent CVE.

The results of the Cox proportional hazards regression showed that with increasing global risk scores, there was a significant increase in the risk of CVE and total mortality. For patients with COPD who also had a low global risk score as the reference group, the risk of CVE and total mortality increased across global risk and COPD severity groups (Table 2).

Table Graphic Jump Location
Table 2 —Cox Regression for Association of COPD and FRS Category With CVE and Total Mortality

FRS = Framingham Risk Score; HR = hazard ratio. See Table 1 legend for expansion of other abbreviation.

a. 

Reference group.

Receiver operating characteristic analyses were performed to determine whether adding global risk scores to lung function data improved the prediction of all-cause mortality. The C statistic for lung function data only was 0.62 (P < .0001). The addition of global risk scores to lung function increased the C statistic to 0.79 (P < .0001 compared with lung function data only). For CVE mortality, a C statistic of 0.57 (P < .0001) was obtained for COPD alone as a predictor of mortality, whereas the addition of global risk scores increased this value to 0.76 (P < .0001 for improvement in the C statistic) (Fig 5).

Figure Jump LinkFigure 5. ROC curves for CVE and total mortality. For CVE mortality, the C statistic was 0.57 for COPD alone (model 1); the addition of global risk scores increased this value to 0.76 (model 2) (P < .0001 for improvement). For total mortality, the C statistic was 0.62 (P < .0001) for COPD alone and 0.79 with the addition of global risk scores (P < .0001 for improvement). ROC = receiver operating characteristic. See Figure 3 legend for expansion of other abbreviation.Grahic Jump Location

The addition of global risk scores to COPD severity resulted in a substantial NRI of 17.1% (P < .0001) for CVE mortality, indicating that by using the global risk scores, about 17% of patients were correctly reclassified into higher (among those who subsequently experienced CVE mortality) or lower (among those who survived) risk categories. Of note, among the subset with moderate COPD, NRI was highest at 20.5% (P < .0001). The total mortality analysis resulted in an NRI of 13.0% (P < .0001), which indicates that by adding global risk scores above lung function data, about 13% of patients were correctly reclassified into higher or lower risk categories. As seen in Table 3, in all of the COPD severities (mild, moderate, and severe), there was a significant improvement from the addition of global risk to the original model (P < .05).

Table Graphic Jump Location
Table 3 —Net Reclassification Index From the Addition of Global CVE Risk to COPD Based on Pulmonary Function Overall and by COPD Severity Group

See Table 1 legend for expansion of abbreviation.

a. 

P < .05, otherwise P < .0001.

The most important and novel finding in this study was that the addition of global CVE risk scores to lung function data significantly improved prognostic classification of individuals with COPD and, thus, should be used in risk stratification of patients with COPD. The findings also support previous observations that impaired lung function is a significant predictor of CVEs and mortality.19 However, by itself, measures of lung function have relatively poor resolution in predicting these events in patients with COPD and, thus, should not be used on their own for risk stratification. Resolution may be enhanced by the use of a multidimensional index such as the BMI, airflow obstruction, dyspnea, and exercise capacity (BODE) index.20 However, in contrast to the BODE index, which requires a 6-min walk test that is not routinely performed in primary-care clinics, global CVE risk assessment is based on simple blood tests and medical history that are widely available, making this approach an attractive alternative to multidimensional risk assessment tools for risk stratification for specialists and especially for primary-care physicians.

Although the present study indicates that cardiovascular risk factors strongly influence overall morbidity and mortality of patients with COPD, the mechanism by which COPD enhances the risk of CVEs is unknown. Previous studies have implicated systemic inflammation in this process, and many have used CRP levels as biomarkers to link COPD with cardiac injury.19 Consistent with previous studies, the present study showed that CRP levels relate to the severity of COPD.21 An alternative, but not mutually exclusive mechanistic pathway is that COPD and CVEs are related because of shared risk factors (eg, smoking, advanced age). Regardless of the mechanism, the findings suggest that the use of the global risk score can lead to the early identification of patients at high or very-high risk of CVE and total mortality, which will enable physicians to aggressively treat these patients’ underlying COPD and CV risk factors and alter their prognosis.

There were several limitations to the present study. First, not all patients had both spirometry and global risk data, which reduced the overall sample size. Second, we defined COPD on the basis of prebronchodilator spirometry (because postbronchodilator data were unavailable), so there is the possibility that some patients also had asthma. To reduce this misclassification error, we excluded patients with self-reported or physician-diagnosed asthma. Third, we had data only on total and CVE mortality end points and not on other manifestations of cardiovascular disease, such as subclinical carotid intimal medial thickening or angiographic findings of early coronary artery disease, which could have further increased the power of the study. Fourth, we did not include information about medications, particularly the use of β-blockers, because of the uncertain reliability of this information in the study database. Because β-blockers are underused in patients with COPD, this may be one of the underlying mechanisms by which COPD confers increased risk of CVEs. Future (prospective) studies will be needed to validate this concept. Fifth, the study only included whites, Hispanics, and non-Hispanic blacks; thus, the findings may not be generalizable to other racial groups. Finally, the data set did not include information on physiologic parameters of exercise capacity, such as the 6-min walk test; thus, we could not determine the incremental benefits of the global risk scores to multidimensional prognostic instruments in COPD, such as the BODE index.20 Future studies will be needed to address this important question as well as to determine whether global risk scores, such as the FRS, should incorporate lung function parameters, such as FEV1, for a more-accurate assessment of CVE.

The practical implications of the study findings are that patients with COPD at intermediate or high global CVE risk, in addition to their anti-COPD therapy, may require aggressive and early treatment of CVE risk reduction, such as statin therapy. Interestingly and consistent with this notion, reviews suggested that statin treatment may also improve outcomes in COPD independent of their lipid-lowering effects.2225 Increasing evidence indicates that COPD is a complex disease involving more than airflow limitation.26,27 Because there are no known ways to cure or reverse COPD, risk factor modification is essential in reducing the CVE-related burden of COPD. In COPD management to date, the focus has been primarily on smoking cessation and prevention of exacerbations. However, the present findings suggest that in addition to these conventional COPD management strategies, treatments used to modify CVEs may also be very useful in preventing early mortality in patients with COPD. Further, indiscriminate use of these treatment strategies is likely to be cost-prohibitive and, more importantly, cause undue harm in patients. Thus, we believe that the use of global risk scores (in addition to lung function) for risk stratification by physicians to distinguish patients who will most likely benefit from CVE risk modification strategies from those who will not will make this approach more cost-effective and safe for patients. It is important to note that in the present study, cardiovascular risk assessment was used to predict mortality not solely based on pulmonary function. Additionally, the study combined global cardiovascular risk assessment using FRS with pulmonary function data, which is not typically done among patients with COPD.

In summary, the findings indicate that global risk scores powerfully and significantly add to the prediction of CVE and total mortality over knowledge of COPD status from pulmonary function measurements alone, with global risk scores significantly adding to risk prediction from improvement in discrimination. Dissimilar to multidimensional instruments such as the BODE index, which requires physiologic testing that may not be available in every clinical setting, global risk scores rely on data that are widely and routinely collected by primary-care physicians, making it possible for busy clinicians to use this tool in to stratify risk in their patients with COPD. In conclusion, the findings indicate that global risk scores provide incremental prognostic information beyond lung function and, thus, should be used to classify risk in patients with COPD.

Author contributions: Dr Lee had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Dr Lee: contributed to the study design, supervision of all project activities, and writing of the manuscript.

Ms J. Lee: contributed to the majority of analyses, interpretation of the results, and writing of the manuscript.

Ms K. Lee: contributed to additional analyses and editing of the manuscript.

Ms Luo: contributed to performing, reviewing, and revising the statistical analysis for the manuscript.

Dr Sin: contributed to the study design and writing of the manuscript.

Dr Wong: contributed to the study design, conceptual aspects of the manuscript, and writing and editing of the manuscript.

Financial/nonfinancial disclosures: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

ATS

American Thoracic Society

BODE

BMI, airflow obstruction, dyspnea, and exercise capacity

CRP

C-reactive protein

CVE

cardiovascular event

FRS

Framingham Risk Score

HDL-C

high-density lipoprotein cholesterol

NRI

net reclassification improvement

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Sin DD, Anthonisen NR, Soriano JB, Agusti AG. Mortality in COPD: role of comorbidities. Eur Respir J. 2006;28(6):1245-1257. [CrossRef] [PubMed]
 
Shavelle RM, Paculdo DR, Kush SJ, Mannino DM, Strauss DJ. Life expectancy and years of life lost in chronic obstructive pulmonary disease: findings from the NHANES III Follow-up Study. Int J Chron Obstruct Pulmon Dis. 2009;4(:137-148. [CrossRef] [PubMed]
 
World Health OrganizationWorld Health Organization. Chronic obstructive pulmonary disease (COPD) fact sheet. World Health Organization website.www.who.int/mediacentre/factsheets/fs315/en/index.html. Published November 2011. Accessed March 13, 2012.
 
Martin JA, Hamilton BE, Sutton PD, Ventura SJ, Mathews TJ, Osterman MJ. Births: final data for 2008. Natl Vital Stat Rep. 2010;59(1):1-3-71.. [PubMed]
 
Berger JS, Sanborn TA, Sherman W, Brown DL. Effect of chronic obstructive pulmonary disease on survival of patients with coronary heart disease having percutaneous coronary intervention. Am J Cardiol. 2004;94(5):649-651. [CrossRef] [PubMed]
 
Curkendall SM, DeLuise C, Jones JK, et al. Cardiovascular disease in patients with chronic obstructive pulmonary disease, Saskatchewan Canada cardiovascular disease in COPD patients. Ann Epidemiol. 2006;16(1):63-70. [CrossRef] [PubMed]
 
Sin DD, Wu L, Man SF. The relationship between reduced lung function and cardiovascular mortality: a population-based study and a systematic review of the literature. Chest. 2005;127(6):1952-1959. [CrossRef] [PubMed]
 
D’Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117(6):743-753. [CrossRef] [PubMed]
 
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Figures

Figure Jump LinkFigure 1. Distribution of global risk groups according to severity of COPD (P < .0001). FRS = Framingham Risk Score.Grahic Jump Location
Figure Jump LinkFigure 2. ORs for COPD across varying global risk groups. The reference group was the low global risk group and was set to equal 1 (intermediate vs low risk, P < .05; high vs low risk, P < .0001; very-high risk vs low risk, P < .0001). Bar lines indicate 95% CI.Grahic Jump Location
Figure Jump LinkFigure 3. CVE mortality per 1,000 person-y across global FRS risk group within each COPD group (P < .0001) across all groups. CVE = cardiovascular event. See Figure 1 legend for expansion of other abbreviation.Grahic Jump Location
Figure Jump LinkFigure 4. Total mortality per 1,000 person-y by global FRS risk group within each COPD group (P < .0001). See Figure 1 legend for expansion of abbreviation.Grahic Jump Location
Figure Jump LinkFigure 5. ROC curves for CVE and total mortality. For CVE mortality, the C statistic was 0.57 for COPD alone (model 1); the addition of global risk scores increased this value to 0.76 (model 2) (P < .0001 for improvement). For total mortality, the C statistic was 0.62 (P < .0001) for COPD alone and 0.79 with the addition of global risk scores (P < .0001 for improvement). ROC = receiver operating characteristic. See Figure 3 legend for expansion of other abbreviation.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 —Lung Function, Demographic and Cardiovascular Risk Factor Measures, and Mortality End Points According to Severity of COPD

Data are presented as mean ± SD or % (No.), unless otherwise indicated. CRP = C-reactive protein, CVE = cardiovascular event; HDL = high-density lipoprotein, LDL = low-density lipoprotein.

Table Graphic Jump Location
Table 2 —Cox Regression for Association of COPD and FRS Category With CVE and Total Mortality

FRS = Framingham Risk Score; HR = hazard ratio. See Table 1 legend for expansion of other abbreviation.

a. 

Reference group.

Table Graphic Jump Location
Table 3 —Net Reclassification Index From the Addition of Global CVE Risk to COPD Based on Pulmonary Function Overall and by COPD Severity Group

See Table 1 legend for expansion of abbreviation.

a. 

P < .05, otherwise P < .0001.

References

Petty TL. Scope of the COPD problem in North America: early studies of prevalence and NHANES III data: basis for early identification and intervention. Chest. 2000;117(5)(suppl 2):326S-331S. [CrossRef] [PubMed]
 
Sin DD, Anthonisen NR, Soriano JB, Agusti AG. Mortality in COPD: role of comorbidities. Eur Respir J. 2006;28(6):1245-1257. [CrossRef] [PubMed]
 
Shavelle RM, Paculdo DR, Kush SJ, Mannino DM, Strauss DJ. Life expectancy and years of life lost in chronic obstructive pulmonary disease: findings from the NHANES III Follow-up Study. Int J Chron Obstruct Pulmon Dis. 2009;4(:137-148. [CrossRef] [PubMed]
 
World Health OrganizationWorld Health Organization. Chronic obstructive pulmonary disease (COPD) fact sheet. World Health Organization website.www.who.int/mediacentre/factsheets/fs315/en/index.html. Published November 2011. Accessed March 13, 2012.
 
Martin JA, Hamilton BE, Sutton PD, Ventura SJ, Mathews TJ, Osterman MJ. Births: final data for 2008. Natl Vital Stat Rep. 2010;59(1):1-3-71.. [PubMed]
 
Berger JS, Sanborn TA, Sherman W, Brown DL. Effect of chronic obstructive pulmonary disease on survival of patients with coronary heart disease having percutaneous coronary intervention. Am J Cardiol. 2004;94(5):649-651. [CrossRef] [PubMed]
 
Curkendall SM, DeLuise C, Jones JK, et al. Cardiovascular disease in patients with chronic obstructive pulmonary disease, Saskatchewan Canada cardiovascular disease in COPD patients. Ann Epidemiol. 2006;16(1):63-70. [CrossRef] [PubMed]
 
Sin DD, Wu L, Man SF. The relationship between reduced lung function and cardiovascular mortality: a population-based study and a systematic review of the literature. Chest. 2005;127(6):1952-1959. [CrossRef] [PubMed]
 
D’Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117(6):743-753. [CrossRef] [PubMed]
 
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    Print ISSN: 0012-3692
    Online ISSN: 1931-3543