Presented at the 28th International Symposium on Intensive Care and Emergency Medicine, March 2008, Brussels, Belgium.
Original Research Contribution
Lung Sound Patterns Help to Distinguish Congestive Heart Failure, Chronic Obstructive Pulmonary Disease, and Asthma Exacerbations
Article first published online: 17 JAN 2012
© 2012 by the Society for Academic Emergency Medicine
Academic Emergency Medicine
Volume 19, Issue 1, pages 79–84, January 2012
How to Cite
Wang, Z. and Xiong, Y. X. (2012), Lung Sound Patterns Help to Distinguish Congestive Heart Failure, Chronic Obstructive Pulmonary Disease, and Asthma Exacerbations. Academic Emergency Medicine, 19: 79–84. doi: 10.1111/j.1553-2712.2011.01255.x
The authors have no relevant financial information or potential conflicts of interest to disclose.
Supervising Editor: Scott Wilber, MD.
- Issue published online: 17 JAN 2012
- Article first published online: 17 JAN 2012
- Received March 21, 2011; revisions received June 28 and July 24, 2011; accepted July 25, 2011.
ACADEMIC EMERGENCY MEDICINE 2012; 19:79–84 © 2012 by the Society for Academic Emergency Medicine
Objectives: Although congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), and asthma patients typically present with abnormal auscultatory findings on lung examination, respiratory sounds are not normally subjected to rigorous analysis. The aim of this study was to evaluate in detail the distribution of respiratory sound intensity in CHF, COPD, and asthma patients during acute exacerbation.
Methods: Respiratory sounds throughout the respiratory cycle were captured and displayed using an acoustic-based imaging technique. Breath sound distribution was mapped to create a gray-scale sequence of two-dimensional images based on intensity of sound (vibration). Consecutive CHF (n = 22), COPD (n = 19), and asthma (n = 18) patients were imaged at the time of presentation to the emergency department (ED). Twenty healthy subjects were also enrolled as a comparison group. Geographical area of the images and respiratory sound patterns were quantitatively analyzed.
Results: In healthy volunteers and COPD patients, the median (interquartile range [IQR]) geographical areas of the vibration energy images were similar, at 75.6 (IQR = 6.0) and 75.8 (IQR = 10.8) kilopixels, respectively (p > 0.05). Compared to healthy volunteers and COPD patients, areas for CHF and asthma patients were smaller, at 66.9 (IQR = 9.9) and 53.9 (IQR = 15.6) kilopixels, respectively (p < 0.05). The geographic area ratios between the left and right lungs for healthy volunteers and CHF and COPD patients were 1.0 (IQR = 0.2), 1.0 (IQR = 0.2), and 1.0 (IQR = 0.1), respectively. Compared to healthy volunteers, the geographic area ratio between the left and right lungs for asthma patients was 0.5 (IQR = 0.4; p < 0.05). In healthy volunteers and CHF patients, the ratios of vibration energy values at peak inspiration and expiration (peak I/E ratio) were 4.6 (IQR = 4.4) and 4.7 (IQR = 3.5). In marked contrast, the peak I/E ratios of COPD and asthma patients were 3.4 (= 2.1) and 0.1 (IQR = 0.3; p < 0.05), respectively.
Conclusions: The pilot data generated in this study support the concept that relative differences in respiratory sound intensity may be useful in distinguishing acute dyspnea caused by CHF, COPD, or asthma.