Effect of a New Spirometric Reference Equation on the Interpretation of Spirometric Patterns and Disease Severity

Yeon-Mok Oh; Sang-Bum Hong; Tae Sun Shim; Chae-Man Lim; Younsuck Koh; Woo Sung Kim; Dong-Soon Kim; Won Dong Kim; Young Sam Kim; Sang Do Lee

doi:10.4046/trd.2006.60.2.215

Journal List > Tuberc Respir Dis > v.60(2) > 1000912

Go to TopGo to Top Go to BottomGo to Bottom

TOOLS

Oh, Hong, Shim, Lim, Koh, Kim, Kim, Kim, Kim, and Lee: Effect of a New Spirometric Reference Equation on the Interpretation of Spirometric Patterns and Disease Severity

Original Article

Tuberculosis and Respiratory Diseases

Tuberculosis and Respiratory Diseases 2006; 60(2): 215-220.

Published online: 28 February 2006

DOI: https://doi.org/10.4046/trd.2006.60.2.215

Effect of a New Spirometric Reference Equation on the Interpretation of Spirometric Patterns and Disease Severity

Yeon-Mok Oh, M.D., Sang-Bum Hong, M.D., Tae Sun Shim, M.D., Chae-Man Lim, M.D., Younsuck Koh, M.D., Woo Sung Kim, M.D., Dong-Soon Kim, M.D., Won Dong Kim, M.D., Young Sam Kim, M.D.¹, Sang Do Lee, M.D.

Department of Internal Medicine and Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.

¹Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea.

Address for correspondence: Sang Do Lee, M.D. Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine and Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, 388-1 Pungnap-dong, Sonpa-gu, Seoul 138-736, South Korea. Phone: 02-3010-3140, Fax: 02-3010-6968, sdlee@amc.seoul.kr

Received 2 January 2006 Accepted 2 February 2006

Abstract

Background

A spirometric reference equation was recently developed for the general population in Korea. The applicability of the new Korean equation to clinical practice was examined by comparing it with the Morris equation, which is one of the most popular reference equations used for interpreting the spirometric patterns and for grading the disease severity in Korea.

Methods

Spirometry was performed on 926 men and 694 women, aged 20 years or older, in November 2004 at the Asan Medical Center, Seoul, Korea. The subjects' age, gender, height, weight, and spirometric values (FEV₁ [forced expiratory volume in one second], FVC [forced vital capacity], and FEV₁/FVC) were obtained. The spirometric patterns and disease severity were evaluated using both equations, and the results of the Korean equation were compared with the Morris equation. The spirometric patterns were defined as normal, restrictive, obstructive, and undetermined according to the level of FEV₁/FVC and FVC. The disease severity was defined according to the level of FEV₁ level for subjects with an airflow limitation, and according to the FVC level for those subjects without an airflow limitation.

Results

Spirometric patterns were differently interpreted in 22.5% (208/926) of the men and 24.8% (172/694) of the women after the application of the Korean equation compared with the Morris equation. Of the subjects with airflow limitation, disease severity was differently graded in 30.2% (114/378) of the men and 39.4% (37/94) of the women after the application of the Korean equation. Of the subjects without airflow limitation, disease severity was differently graded in 27.9% (153/548) of the men and 30.2% (181/600) of the women after the application of the Korean equation.

Conclusion

Achange in the reference equation for spirometry could have an effect on the interpretation of spirometric patterns and on the grading of disease severity.

Keywords: Spirometry, reference equation, interpretation

Figures and Tables

Figure 1

Effect of different reference equations on the interpretation of spirometric patterns. Spirometric patterns were differently interpreted after the change in reference equation from the Morris to the new Korean equation (P<0.001 in both males and females by the chi-square test). Definition: normal pattern, FEV₁/ FVC ≥0.7 & FVC ≥80% predicted value; restrictive pattern, FEV₁/FVC ≥0.7 & FVC <80% predicted value; obstructive pattern, FEV₁/FVC <0.7 & FVC ≥80% predicted value; undetermined pattern, FEV₁/FVC <0.7 & FVC <80% predicted value. The number inside each block represents the number of subjects showing each spirometric pattern.

Figure 2

Effect of different reference equations on disease severity in subjects with airflow limitation (FEV₁/FVC <0.7). Disease severity was differently interpreted after the change in reference equation from the Morris to the new Korean equation (P<0.001 in both males and females by the chi-square test). Disease se verity was defined as mild, moderate, severe, and very severe according to FEV₁ (% predicted value) of ≥80%, <80% & ≥50%, <50% & ≥30%, and <30%, respectively. The number inside each block represents the number of subjects showing each grade of disease severity.

Figure 3

Effect of different reference equations on disease severity in subjects without airflow limitation (FEV₁/FVC ≥0.7). Disease severity was differently interpreted after the change in reference equation from the Morris to the new Korean equation (P<0.001 in both males and females, by the chi-square test). Disease severity was defined as mild, moderate, and severe according to FVC (% predicted value) of <80% & ≥60%, <60% & >50%, and ≤50%, respectively. The number inside each block represents the number of subjects showing each grade of disease severity.

Table 1

Reference equations3,4

^*Height in centimeters; ^†a conversion factor from inches to centimeters; ^‡Age in years; ^§Weight in kilograms

Table 2

Characteristics of the subjects

^*mean ± standard deviation

Table 3

Number of subjects showing spirometric pattern shift in each age group by the change in reference equations from the Morris to the Korean equation3,4

^*No other types of the pattern shift were observed other than the above four types.

^†The numbers in parentheses represent the percentage of subjects showing each pattern shift among each age group.

References

1. Gold WM. Murray JF, Nadel JA, editors. Pulmonary function testing. Textbook of respiratory medicine. 2000. 3rd ed. W.B. Philadelphia: Saunders;781–881.

2. American Thoracic Society. Lung function testing: selection of reference values and interpretative strategies. Am Rev Respir Dis. 1991. 144:1202–1218.

3. Choi JK, Paek D, Lee JO. Normal predictive values of spirometry for Korean population. Tuberc Respir Dis. 2005. 58:230–242.

4. Morris JF, Koski A, Johnson LC. Spirometric standards for healthy nonsmoking adults. Am Rev Respir Dis. 1971. 103:57–67.

5. American Thoracic Society. Standardization of Spirometry: 1994 update. Am J Respir Crit Care Med. 1995. 152:1107–1136.

6. Global initiative for chronic obstructive lung disease: global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease. National Heart, Lung, and Blood Institute and World Health Organization. revised 2003; cited 20 August 2004. Bethesda, MD, USA: National Heart, Lung, and Blood Institute, National Institutes of Health;Available from: URL: http://www.goldcopd.com.

7. American Medical Association. Guides to the evaluation of permanent impairment. 1993. 4th ed. Chicago: American Medical Association.

8. Standards for the diagnosis and treatment of patients with chronic obstructive pulmonary disease. American Thoracic Society and European Respiratory Society. cited 10 June 2004. New York, USA: American Thoracic Society;Available from URL: http://www.thoracic.org/COPD/.

9. Dykstra BJ, Scanlon PD, Kester MM, Beck KC, Enright PL. Lung volumes in 4,774 patients with obstructive lung disease. Chest. 1999. 115:68–74.

TOOLS

Similar articles