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Lung

, Volume 192, Issue 5, pp 661–668 | Cite as

The Ability of Volumetric Capnography to Distinguish between Chronic Obstructive Pulmonary Disease Patients and Normal Subjects

  • Guang-Sheng Qi
  • Wen-Chao Gu
  • Wen-Lan Yang
  • Feng Xi
  • Hao Wu
  • Jin-Ming LiuEmail author
Article

Abstract

Purpose

The aim of our study was to evaluate volumetric capnography (VCap) in the differentiation between chronic obstructive pulmonary disease (COPD) patients and normal subjects.

Patients and Methods

Thirty-nine healthy male volunteers and 60 male COPD patients were enrolled. Regression equations between VCap indices and age, weight, height, and tidal volume in healthy volunteers were established by stepwise regression analysis. Predicted normal values of VCap indices in COPD patients were calculated. A paired t test was used to compare the difference between observed and predicted values for VCap indices in COPD patients. Receiver operating characteristic (ROC) curve analysis was used to evaluate the power of each VCap index alone in differentiating COPD patients and normal subjects. The power of the combination of VCap indices was assessed by discriminant analysis.

Results

All regression equations were significant (P < 0.01) as were the differences between the observed and predicted normal VCap indices in COPD patients (P < 0.001). ROC curve analysis showed that the volume between 25 and 50 % of F CO2et (Vm25-50), slope of Phase II (dC2/dV), and slope of Phase III (dC3/dV) were valuable predictors. Nearly all (90.9 %) subjects were correctly classified by discriminant analysis.

Conclusion

Vm25-50, dC2/dV, or dC3/dV alone are valuable for differentiating COPD patients and normal subjects, but more powerful are the combinations of Vm25-50, dC2/dV, and dC3/dV, the ratio of dC2/dV to dC3/dV (SR23), dead space according to the Bohr method (VDB), and dead space according to the Wolff and Brunner methods (PIE).

Keywords

Chronic obstructive pulmonary disease Volumetric capnography Dead space Lung function Expired carbon dioxide 

Notes

Acknowledgments

We thank Wei Zheng, Yingmin Wang, Liqing Xu, and Cailiu Huang for their technical guidance and help with data collection. We also thank Hua Yang, Weiju Zhou, Shanshan Li, Zhijun Tang, Linxuan Wang, Guoping Deng, Xiaolong Gu, and Xuanbo Chen for the selection of subjects.

Conflict of interest

This study was supported by the Chinese Medical Association. The authors report no conflicts of interest. The authors alone are responsible for the creation and content of this paper. Funded by Outstanding Young Medical Talents Training Project of Pudong Health Bureau of Shanghai, and Key Discipline Construction Project of Pudong Health Bureau of Shanghai.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Guang-Sheng Qi
    • 1
  • Wen-Chao Gu
    • 1
  • Wen-Lan Yang
    • 2
  • Feng Xi
    • 1
  • Hao Wu
    • 1
  • Jin-Ming Liu
    • 3
    Email author
  1. 1.Department of Respiratory MedicineShanghai Pudong New Area People’s HospitalShanghaiChina
  2. 2.Department of Pulmonary Function TestShanghai Pulmonary Hospital Affiliated to Tongji UniversityShanghaiChina
  3. 3.Department of Pulmonary CirculationShanghai Pulmonary Hospital Affiliated to Tongji UniversityShanghaiChina

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