Despite being a major public health problem, chronic obstructive pulmonary disease (COPD) remains underdiagnosed, and only 2.4% COPD patients are aware of their disease in Korea. The objective of this study was to estimate the prevalence of COPD detected by spirometry performed as a preoperative screening test and to determine the Global Initiative for Chronic Obstructive Lung Disease (GOLD) group distribution and self-awareness of COPD.
We reviewed the medical records of adults (age, ≥40 years) who had undergone spirometry during preoperative screening between April and August 2013 at a tertiary hospital in Korea. COPD was defined as a postbronchodilator forced expiratory volume in 1 s/forced vital capacity ratio of <0.7. We analyzed self-administered COPD questionnaires for the assessment of the frequency of acute exacerbation over the previous year and dyspnea severity using the modified Medical Research Council dyspnea scale and COPD assessment test.
Among 3029 patients aged >40 years who had undergone spirometry as a preoperative screening test, 474 (15.6%; 404 men; median age, 70 years; range, 44–93 years) were diagnosed with COPD. Only 26 (5.5%) patients reported previous diagnosis of COPD (2.1%), emphysema (0.8%), or chronic bronchitis (2.5%). The GOLD group distribution was as follows: 63.3% in group A, 31.2% in group B, 1.7% in group C, and 3.8% in group D.
Citation: Choi SM, Lee J, Park YS, Lee C-H, Lee S-M, Yim J-J, et al. (2015) Prevalence and Global Initiative for Chronic Obstructive Lung Disease Group Distribution of Chronic Obstructive Pulmonary Disease Detected by Preoperative Pulmonary Function Test. PLoS ONE 10(1): e0115787. https://doi.org/10.1371/journal.pone.0115787
Academic Editor: Konstantinos Kostikas, University of Athens Medical School, GREECE
Received: August 11, 2014; Accepted: November 26, 2014; Published: January 27, 2015
Copyright: © 2015 Choi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Data Availability: All relevant data are within the paper.
Funding: The authors have no support or funding to report.
Competing interests: The authors have declared that no competing interests exist.
Chronic obstructive pulmonary disease (COPD) is characterized by persistent airflow limitation that is usually progressive and associated with an enhanced chronic inflammatory response to noxious particles or gases in the airways and lungs [1–3]. COPD is a major cause of morbidity and mortality, and its prevalence is increasing worldwide. It is associated with a high economic and social burden. Despite being a major public health problem, COPD remains underdiagnosed.
The prevalence of COPD varies among reports. A previous meta-analysis reported pooled prevalence estimates of 7.6% , and a recent report showed an estimated population prevalence [Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade II and higher] of 10.1% . COPD prevalence based on self-reporting is the lowest estimate. A recent meta-analysis showed that less than 6% of the adult population were aware of their COPD . In Korea, only 2.4% COPD patients in a community population were aware of their disease .
Disease prevalence largely depends on the studied population. Several studies have reported the prevalence of COPD among patients with cardiovascular diseases , respiratory tract infections , and other conditions  that require medical management. The prevalence of COPD in these patients is 10.5–27%, which is higher than that reported in a field survey . Because COPD, a systemic inflammatory disease, has been shown to be associated with many diseases that require medical management, the higher prevalence in such patients could be explained by a selection bias for COPD patients with comorbidities. For example, patients with conditions that require regular medical attention have more contact with physicians; therefore, they are more likely to be diagnosed with COPD.
Spirometry is mandatory for the diagnosis of COPD. A considerable number of patients is diagnosed with COPD by spirometry performed not for respiratory symptoms but for various other reasons. For example, although guidelines for preoperative screening do not recommend spirometry as a routine test , many surgeons perform spirometry for preoperative screening because COPD is one of the most important risk factors for postoperative pulmonary complications . Nevertheless, there is limited data on the prevalence and severity of COPD among surgical candidates, and the numbers vary from 5% to 40% [3, 11, 12].
While diagnostic methods for COPD have remained unchanged, management strategies have significantly improved, particularly with regard to therapeutic intervention and disease assessment. Specifically, COPD assessment must consider all of the following four aspects: 1) patient’s symptoms, 2) severity of the airflow limitation measured by spirometry, 3) exacerbation risk, and 4) presence of comorbidities. As a result, the 2011 GOLD guideline suggested a new assessment method for COPD that considers the current level of symptoms and the exacerbation risk, with the ultimate goal to achieve better therapeutic outcomes [1, 13]. The guideline suggests that patients in groups B, C, and D should receive regular treatment .
The objective of this study was to estimate the prevalence of COPD among surgical candidates, determine the distribution of various COPD types based on the new classification defined in the 2011 GOLD guidelines, and assess patients’ self-awareness of COPD.
We screened all patients who had undergone spirometry at a tertiary hospital in Korea, Seoul National University Hospital, between April 2013 and August 2013. We reviewed the departments that had administered spirometry tests and included patients referred from surgical departments, because spirometry was likely administered as part of preoperative screening. Finally, we reviewed medical records in order to identify patients who planned to undergo elective surgery.
We defined COPD as a postbronchodilator (post-BD) forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ratio of <0.7 in patients aged ≥40 years, according to the GOLD guideline . Spirometry results were expressed as percentages of the predicted values and were calculated using Morris’s predictive equations as follows: predicted FEV1 for men = 0.092 × height − 0.032 × age − 1.26, predicted FEV1 for women = 0.089 × height − 0.025 × age − 1.932, predicted FVC for men = 0.148 × height − 0.025× age − 4.241, predicted FVC for women = 0.115 × height − 0.024× age − 2.852 (height in inches) .
Spirometry was performed using spirometers (Model: VMAX229, VMAX22, and VMAX 20; SensorMedics, Yorba Linda, CA) by five trained technicians according to the 2005 American Thoracic Society (ATS)/European Respiratory Society (ERS) recommendations .
Data collected included demographic characteristics; surgery-related factors such as type of surgery, surgical duration, and anesthesia type; and whether the patient began to visit a pulmonologist after surgery. We also analyzed two different self-administered questionnaires collected at the time of the pulmonary function test (PFT). One questionnaire focused on the past medical and smoking histories. Specifically, the patients were asked to identify whether they had previously been diagnosed with a respiratory disease, and, if yes, which specific disease, namely COPD, chronic bronchitis, emphysema, asthma, bronchiectasis, tuberculosis, pneumonia, and others. The other questionnaire was completed by COPD patients (postbronchodilator FEV1/FVC < 0.7) to evaluate the risk of acute exacerbation of COPD and dyspnea severity. Patients were asked to identify the frequency and severity of acute exacerbation in the preceding year. The resulting data were used to assess the exacerbation risk according to the GOLD guideline, i.e., one or more hospitalizations for COPD exacerbations or two or more COPD exacerbations indicated a high risk . We also evaluated dyspnea severity using the modified Medical Research Council (mMRC) dyspnea scale and the COPD assessment test (CAT) score.
COPD patients who completed the second questionnaire were classified into the following four groups based on the results of spirometry and questionnaires: group A, low risk of exacerbations and low level of symptoms; group B, low risk of exacerbations and high level of symptoms; group C, high risk of exacerbations and low level of symptoms; and group D, high risk of exacerbations and high level of symptoms .
Statistical analyses were performed using SPSS 17.0 (Chicago, IL, USA). Variables were compared between patients with and without COPD using Student’s t-test or the Mann—Whitney U test for continuous variables and the χ2 test or Fisher’s exact test for categorical variables in univariate analyses.
This study was approved by the Seoul National University Institutional Review Board for Clinical Research (IRB number: 1308–084–514). The informed consent requirement was waived because of the retrospective study design. All patient records and information were anonymized and deidentified prior to analysis.
A total of 8240 patients underwent PFT during the study period (see Fig. 1 for the patient selection process). After a review of medical records, we excluded 726 patients aged <40 years and 3618 patients who had undergone PFT for other medical conditions and not for preoperative screening. We also excluded 812 patients who did not complete the questionnaires. Among the remaining 3084 patients, 656 had a pre-BD FEV1/FVC of <0.7. We excluded 55 patients who did not undergo post-BD spirometry. Among the remaining 601 patients, 127 had a post-BD FEV1/FVC of ≥0.7. Eventually, 474 (15.6%) patients were found to have COPD with a post-BD FEV1/FVC of <0.7.
BD: bronchodilator, FEV1/FVC: forced expiratory volume in 1 s/forced vital capacity, COPD: chronic obstructive pulmonary disease.
The median age of patients was 64 years, and 53.9% were men. Surgeries were performed in the following departments: General Surgery (41.5%), Thoracic and Cardiovascular Surgery (3.2%), Orthopedic Surgery (13.4%), Urology (19.1%), Neurosurgery (9.7%), Plastic and Reconstructive Surgery (3.6%), Otorhinolaryngology (5.8%), Obstetrics and Gynecology (5.9%), and Ophthalmology (0.5%) departments. Among the COPD patients, 85.2% were men, and the median age was 70 years. Table 1 shows the baseline characteristics of the COPD and non-COPD patients. COPD patients were older than non-COPD patients (p < 0.001) and were predominantly men (p < 0.001). The number of patients who underwent surgeries under general anesthesia was higher in the non-COPD group than in the COPD group (p = 0.011), while a higher number of patients in the COPD group underwent surgeries under spinal anesthesia (p = 0.001). The number of patients referred to a pulmonologist for preoperative evaluation was higher in the COPD group than in the non-COPD group (p < 0.001).
Although preoperative arterial blood gas analysis (ABGA) was not performed for all patients, it showed a lower partial pressure of oxygen in arterial blood (PaO2), which was still within the normal range (74–108 mmHg), in COPD patients (p < 0.001). On the other hand, the partial pressure of carbon dioxide in arterial blood (PaCO2) did not differ between the two groups (Table 1). The number of patients with a history of smoking was higher in the COPD group than in the non-COPD group (p < 0.001).
Awareness of COPD
Among the 474 COPD patients, 61.2% reported undergoing spirometry at least once. However, only 26 (5.5%) patients reported a previous diagnosis of COPD (2.1%), emphysema (0.8%), or chronic bronchitis (2.5%) by a physician (Table 2). On the other hand, 54 (11.3%) patients declared that they had been diagnosed with asthma. Among them, 20 showed a positive bronchodilator response, defined as a ≥12% increase and 200 mL of pre-BD FEV1 after inhalation of the short-acting bronchodilator salbutamol. Sixty-one (12.9%) of the 474 patients reported the use of an inhaler for their respiratory disease. Only nine patients among the 31 who had been followed by a pulmonologist in the same hospital were aware of their COPD; 11.1% COPD patients began visiting a pulmonologist after their surgeries.
Past medical history
Table 2 shows the results of self-administered questionnaires on past medical histories. The number of patients with a history of asthma (p < 0.001), bronchiectasis (p = 0.001), and tuberculosis (p = 0.001) was higher in the COPD group than in the non-COPD group. The rate of other comorbidities, including hypertension, diabetes mellitus, liver disease, renal disease, cardiovascular disease, cerebrovascular disease, and malignant disease, was similar in both groups. Thyroid disease was more common in the non-COPD group (p = 0.006), probably because there were more females in this group. The number of patients who underwent regular health screenings was similar in both groups (p = 0.932).
Results of spirometry
The majority of COPD patients (78.5%) had mild airflow limitation with a post-BD FEV1 of ≥0.8, followed by moderate (18.4%), severe (3.05), and very severe (0.2%) airflow limitation (Table 3). Sixty-eight (14.3%) COPD patients showed a positive bronchodilator response.
Assessment of risk of exacerbation and level of symptoms
All 474 COPD patients completed the second questionnaire assessing the risk of acute exacerbation of COPD and dyspnea severity. Of these, 18 (3.8%) reported at least one exacerbation in the preceding year. Nine (1.9%) patients were identified to have a high risk of exacerbation, as explained in the Methods section (Table 3). The median mMRC dyspnea and CAT scores were 1 (interquartile range [IQR], 0–1) and 6 (IQR, 3–10), respectively.
The GOLD group distribution of COPD patients based on the mMRC score was 79.7% (378) in group A, 14.8% (70) in group B, 3.4% (16) in group C, and 2.1% (10) in group D. The distribution was significantly different (p < 0.001) when the CAT score was used, i.e., 69.0% (327) in group A, 25.5% (121) in group B, 2.3% (11) in group C, and 3.2% (15) in group D (Table 4). The GOLD group distribution using either the mMRC or CAT score, whichever indicated a higher level of symptoms, was as follows: 63.3% in group A, 31.2% in group B, 1.7% in group C, and 3.8% in group D.
In the current study, 474 patients (15.6%) were identified to have COPD among surgical candidates in a tertiary hospital, with the GOLD group distribution as follows: 63.3% in group A, 31.2% in group B, 1.7% in group C, and 3.8% in group D. Only 26 (5.5%) patients reported awareness of their disease.
The COPD prevalence rate of 15.6% among the surgical candidates in this study was similar to that in a community population in Korea. Two previous studies reported on the prevalence of COPD in Korea, which was 13.4% among patients aged >40 years and 17.2% among those aged >45 years according to population-based spirometry surveys performed in 2008 and 2001, respectively [6, 17].
A recent study reported a COPD prevalence rate of 4.82% among surgical patients , which was lower than that in this study. However, that study defined COPD using more stringent criteria, such as a predicted FEV1 of <75% or hospitalization. On the other hand, we applied the criteria established by the GOLD guideline and included the milder form of disease, which resulted in the higher prevalence.
Patients with COPD in our study were older (p < 0.001) and predominantly male (p < 0.001), consistent with the well-known characteristics of COPD patients. Weight loss is often observed in COPD patients [18, 19]; however, the body mass index (BMI) did not differ between patients with and without COPD in the present study. Similarly, several other studies have reported similar or even higher BMI values for COPD patients than for healthy controls [20, 21].
Smoking is the most important risk factor for COPD. The number of patients with a smoking history was significantly higher among COPD patients than among non-COPD patients in this study (p < 0.001). In total, 23% COPD patients were never smokers, similar to the findings in previous reports on large populations in the US, UK, and Spain [22–24].
When assessing surgery-related parameters, we found that the surgical duration was similar between the two groups. However, a significantly higher number of patients with COPD had undergone surgeries under spinal anesthesia, while a higher number of patients without COPD had undergone surgeries under general anesthesia. Old age and COPD are important risk factors for postoperative pulmonary complications, particularly in patients undergoing surgery under general anesthesia. Therefore, surgeons are likely to opt less frequently for surgery under general anesthesia in COPD patients. This notion is further supported by the fact that a higher number of patients with COPD was referred to pulmonologists prior to surgery (p < 0.001).
Compared with non-COPD patients, a significantly higher number of COPD patients reported respiratory diseases, including asthma, bronchiectasis, and tuberculosis (Table 2). Various respiratory diseases, including asthma and tuberculosis, could be risk factors for COPD [25, 26], and vice versa. In addition, a previous study addressing the overlap between various obstructive airway diseases showed that 17–19% patients had more than one condition, with the overlap increasing with advancing age .
Among several conditions, asthma–COPD overlap syndrome (ACOS) was the most common in older patients . ACOS is characterized by persistent airflow limitation with clinical features associated with asthma. In the current study, 54 (11.3%) COPD patients reported a previous diagnosis of asthma, and an additional 48 (10.1%) patients showed a positive bronchodilator response. Thus, 21.4% COPD patients may be considered to have ACOS in the present study.
The severity of airflow limitation is considered a very important factor related to the prognosis of COPD. Similarly, symptoms such as dyspnea are recognized as important predictors of future mortality risk . In addition, COPD exacerbations not only induce a decline in lung function but also increase the risk of death. However, the correlation between FEV1, symptoms and the health-related quality of life was relatively weak (r = −0.23, p < 0.0001) . Based on these findings, the 2011 GOLD guideline proposed a new classification system for COPD according to symptoms, risk of exacerbation, and airflow limitation.
In our study, 78.4%, 18.4%, 3.9%, and 0.2% COPD patients had mild, moderate, severe, and very severe airflow limitation, respectively, according to the GOLD guideline (Table 3). Table 3 also shows the proportion of patients with a high level of symptoms when the mMRC and CAT scores were used for each grade of airflow limitation. For the severe and very severe grades of COPD, the mMRC and CAT scores identified a similar number of patients with a high level of symptoms, while the CAT score identified a higher number of such patients in the mild and moderate COPD groups than that identified by the mMRC score.
The 2011 GOLD guideline recommends the selection of one measure, either the mMRC or CAT score, to assess symptom severity. The mMRC score is easy to apply in practice; however, it only evaluates dyspnea severity. On the other hand, the CAT score may be used to evaluate the effects of COPD on the patients’ quality of life, and it is a multidimensional tool that assesses not only dyspnea but also other respiratory symptoms, general condition, and performance status.
A previous study reported a similar distribution of GOLD groups when the mMRC and St George’s Respiratory Questionnaire (SGRQ) were used . In the current study, however, the distribution of GOLD groups differed depending on the method of symptom assessment, i.e., the mMRC or CAT score (Table 4). More patients were identified to belong to group B with the CAT score than with the mMRC (p < 0.001). Although the number of patients in groups C and D was relatively smaller than that in groups A and B, we further stratified patients in groups C and D as suggested in the previous study; C1 and D1 showed an FEV1 of <50% only, C2 and D2 met the exacerbation criteria only, and C3 and D3 met both the exacerbation and FEV1 criteria . The number of patients in groups C1 and D1 was not higher than that in groups C2–3 and D2–3, while most patients classified into groups C and D in the previous study were classified into C1 and D1 groups, respectively. One possible explanation for this difference is the fact that the study excluded patients with a history of recent exacerbation of COPD treated with antibiotics or steroids, contributing fewer patients to the C2–3 and D2–3 groups than to the C1 and D1 groups .
When we used both measures and chose the higher score between mMRC and CAT, the GOLD group distribution was as follows: 63.3% in group A, 31.2% in group B, 1.7% in group C, and 3.8% in group D. According to this classification, 6.1% group B patients and 16.7% group D patients were aware of their COPD, while 3.7% group A patients and 37.5% group C patients were aware of their condition (p = 0.221). Considering the fact that patients in groups B and D had a high level of symptoms, the awareness of COPD was not related to the level of symptoms.
Several studies have described the underdiagnosis and under-recognition of COPD [24, 33, 34]. Recently, a study reported that only 2.4% COPD patients in Korea were aware of their condition . In the present study, 5.5% COPD patients were aware of their COPD. In addition, even among patients who were followed up by a pulmonologist in the same medical center where this study was performed, only 30% reported a previous diagnosis of COPD, emphysema, or chronic bronchitis. One possible explanation is that the majority of these patients only had mild airflow limitation that did not require treatment.
The present study has several limitations. First, it was a retrospective, single-center analysis, and some selection bias may have occurred. For example, we excluded patients who had not completed the questionnaires, which might have introduced a selection bias. However, the retrospective design most likely did not affect the outcomes, because the objective was to assess the prevalence and group distribution rather than the efficacy of an intervention. Second, we used a fixed FEV1/FVC ratio to define airflow limitation, which may have resulted in a false positive diagnosis of COPD in our study, particularly in elderly subjects, rather than using a cutoff level based on the lower limit of normal values for FEV1/FVC. Third, the number of patients in groups B, C, and D was too small to draw general conclusions. Fourth, some data for surgery-related parameters were missing, because some patients had not yet undergone surgery. Fifth, we included patients with overlap syndromes that would usually be excluded from clinical trials for COPD. Sixth, the medical histories were evaluated primarily through self-reported questionnaires. With regard to the diagnosis of asthma, information on the history of allergic disease or atopy, IgE levels, results of the skin prick test, or fractional exhaled nitric oxide levels was not available because of the retrospective study design.
Despite the abovementioned limitations, to our knowledge, this is the first study to describe the prevalence of COPD using a GOLD group distribution analysis for surgical candidates. We also evaluated patient self-awareness of COPD and the ACOS.
In conclusion, the prevalence of COPD among surgical candidates aged ≥40 years was 15.6% in this study, with 78.5% patients having mild airflow limitation according to the GOLD grade. Approximately one-third of the COPD patients belonged to GOLD groups B, C, and D, requiring regular treatment. Only a small number of patients with COPD (5.5%) were aware of their condition, and COPD awareness was not related to symptom severity. Further research is required to identify the reasons for the low awareness of COPD and to thereby develop approaches for better management of the disease.
Conceived and designed the experiments: CGY SMC CHL. Analyzed the data: YSP JL. Wrote the paper: SMC CGY. Data collection: JJY SML. Data interpretation: YWK SKH.
- 1. Vestbo J, Hurd SS, Agusti AG, Jones PW, Vogelmeier C, et al. (2013) Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 187: 347–365.
- 2. Sandelowsky H, Stallberg B, Nager A, Hasselstrom J (2011) The prevalence of undiagnosed chronic obstructive pulmonary disease in a primary care population with respiratory tract infections—a case finding study. BMC Fam Pract 12: 122. pmid:22047519
- 3. Licker M, Schweizer A, Ellenberger C, Tschopp JM, Diaper J, et al. (2007) Perioperative medical management of patients with COPD. Int J Chron Obstruct Pulmon Dis 2: 493–515. pmid:18268924
- 4. Halbert RJ, Natoli JL, Gano A, Badamgarav E, Buist AS, et al. (2006) Global burden of COPD: systematic review and meta-analysis. Eur Respir J 28: 523–532. pmid:16611654
- 5. Buist AS, Vollmer WM, McBurnie MA (2008) Worldwide burden of COPD in high- and low-income countries. Part I. The burden of obstructive lung disease (BOLD) initiative. Int J Tuberc Lung Dis 12: 703–708. pmid:18544191
- 6. Yoo KH, Kim YS, Sheen SS, Park JH, Hwang YI, et al. (2011) Prevalence of chronic obstructive pulmonary disease in Korea: the fourth Korean National Health and Nutrition Examination Survey, 2008. Respirology 16: 659–665. pmid:21342331
- 7. Wada H, Nakano Y, Nagao T, Osawa M, Yamada H, et al. (2010) Detection and prevalence of chronic obstructive pulmonary disease in a cardiovascular clinic: evaluation using a hand held FEV(1)/FEV(6) meter and questionnaire. Respirology 15: 1252–1258. pmid:20920134
- 8. Lokke A, Ulrik CS, Dahl R, Plauborg L, Dollerup J, et al. (2012) Detection of previously undiagnosed cases of COPD in a high-risk population identified in general practice. COPD 9: 458–465. pmid:22643016
- 9. Qaseem A, Snow V, Fitterman N, Hornbake ER, Lawrence VA, et al. (2006) Risk assessment for and strategies to reduce perioperative pulmonary complications for patients undergoing noncardiothoracic surgery: a guideline from the American College of Physicians. Ann Intern Med 144: 575–580. pmid:16618955
- 10. Smetana GW, Lawrence VA, Cornell JE, American College of P (2006) Preoperative pulmonary risk stratification for noncardiothoracic surgery: systematic review for the American College of Physicians. Ann Intern Med 144: 581–595. pmid:16618956
- 11. McAlister FA, Khan NA, Straus SE, Papaioakim M, Fisher BW, et al. (2003) Accuracy of the preoperative assessment in predicting pulmonary risk after nonthoracic surgery. American Journal of Respiratory and Critical Care Medicine 167: 741–744. pmid:12598217
- 12. Licker MJ, Widikker I, Robert J, Frey JG, Spiliopoulos A, et al. (2006) Operative mortality and respiratory complications after lung resection for cancer: impact of chronic obstructive pulmonary disease and time trends. Ann Thorac Surg 81: 1830–1837. pmid:16631680
- 13. Vestbo J, Hurd SS, Rodriguez-Roisin R (2012) The 2011 revision of the global strategy for the diagnosis, management and prevention of COPD (GOLD)—why and what? Clin Respir J 6: 208–214. pmid:22906068
- 14. Vestbo J, Hurd SS, Agustí AG, Jones PW, Vogelmeier C, et al. (2013) Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine 187: 347–365. pmid:22878278
- 15. Morris JF, Koski A, Johnson LC (1971) Spirometric standards for healthy nonsmoking adults. Am Rev Respir Dis 103: 57–67. pmid:5540840
- 16. Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, et al. (2005) Standardisation of spirometry. European Respiratory Journal 26: 319–338. pmid:16055882
- 17. Kim DS, Kim YS, Jung KS, Chang JH, Lim CM, et al. (2005) Prevalence of chronic obstructive pulmonary disease in Korea: a population-based spirometry survey. Am J Respir Crit Care Med 172: 842–847. pmid:15976382
- 18. Gupta H, Ramanan B, Gupta PK, Fang X, Polich A, et al. (2013) Impact of COPD on postoperative outcomes: results from a national database. Chest 143: 1599–1606. pmid:23287892
- 19. Gray-Donald K, Gibbons L, Shapiro SH, Macklem PT, Martin JG (1996) Nutritional status and mortality in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 153: 961–966. pmid:8630580
- 20. Calikoglu M, Sahin G, Unlu A, Ozturk C, Tamer L, et al. (2004) Leptin and TNF-alpha levels in patients with chronic obstructive pulmonary disease and their relationship to nutritional parameters. Respiration 71: 45–50. pmid:14872110
- 21. Takabatake N, Nakamura H, Minamihaba O, Inage M, Inoue S, et al. (2001) A novel pathophysiologic phenomenon in cachexic patients with chronic obstructive pulmonary disease: the relationship between the circadian rhythm of circulating leptin and the very low-frequency component of heart rate variability. Am J Respir Crit Care Med 163: 1314–1319. pmid:11371394
- 22. Behrendt CE (2005) Mild and moderate-to-severe COPD in nonsmokers: distinct demographic profiles. Chest 128: 1239–1244. pmid:16162712
- 23. Birring SS, Brightling CE, Bradding P, Entwisle JJ, Vara DD, et al. (2002) Clinical, radiologic, and induced sputum features of chronic obstructive pulmonary disease in nonsmokers: a descriptive study. Am J Respir Crit Care Med 166: 1078–1083. pmid:12379551
- 24. Pena VS, Miravitlles M, Gabriel R, Jimenez-Ruiz CA, Villasante C, et al. (2000) Geographic variations in prevalence and underdiagnosis of COPD: results of the IBERPOC multicentre epidemiological study. Chest 118: 981–989. pmid:11035667
- 25. Menezes AM, Hallal PC, Perez-Padilla R, Jardim JR, Muino A, et al. (2007) Tuberculosis and airflow obstruction: evidence from the PLATINO study in Latin America. Eur Respir J 30: 1180–1185. pmid:17804445
- 26. Lam KB, Jiang CQ, Jordan RE, Miller MR, Zhang WS, et al. (2010) Prior TB, smoking, and airflow obstruction: a cross-sectional analysis of the Guangzhou Biobank Cohort Study. Chest 137: 593–600. pmid:19820078
- 27. Soriano JB, Davis KJ, Coleman B, Visick G, Mannino D, et al. (2003) The proportional Venn diagram of obstructive lung disease: two approximations from the United States and the United Kingdom. Chest 124: 474–481. pmid:12907531
- 28. Marsh SE, Travers J, Weatherall M, Williams MV, Aldington S, et al. (2008) Proportional classifications of COPD phenotypes. Thorax 63: 761–767. pmid:18728201
- 29. Celli BR, Cote CG, Marin JM, Casanova C, Montes de Oca M, et al. (2004) The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med 350: 1005–1012. pmid:14999112
- 30. Jones PW (2009) Health status and the spiral of decline. COPD 6: 59–63. pmid:19229709
- 31. Han MK, Muellerova H, Curran-Everett D, Dransfield MT, Washko GR, et al. (2013) GOLD 2011 disease severity classification in COPDGene: a prospective cohort study. Lancet Respir Med 1: 43–50. pmid:24321803
- 32. Regan EA, Hokanson JE, Murphy JR, Make B, Lynch DA, et al. (2010) Genetic epidemiology of COPD (COPDGene) study design. COPD 7: 32–43. pmid:20214461
- 33. Lindstrom M, Jonsson E, Larsson K, Lundback B (2002) Underdiagnosis of chronic obstructive pulmonary disease in Northern Sweden. Int J Tuberc Lung Dis 6: 76–84. pmid:11931405
- 34. Brekke PH, Omland T, Smith P, Soyseth V (2008) Underdiagnosis of myocardial infarction in COPD—Cardiac Infarction Injury Score (CIIS) in patients hospitalised for COPD exacerbation. Respir Med 102: 1243–1247. pmid:18595681