Lung Sound Analysis Is Useful for Monitoring Therapy in Patients With Bronchial Asthma

Wheezing Characteristics and Predicting Reactivity to Inhaled β2-Agonist in Children for Home Medical Care

Background: Given that wheezing is treated with inhaled β2-agonists, their effect should be reviewed before the condition becomes severe; however, few methods can currently predict reactivity to inhaled β2-agonists. We investigated whether preinhalation wheezing characteristics identified by lung sound analysis can predict reactivity to inhaled β2-agonists. Methods: In 202 children aged 10-153 months, wheezing was identified by auscultation. Lung sounds were recorded for 30 s in the chest region on the chest wall during tidal breathing. We analyzed the wheezing before and after β2-agonist inhalation. Wheezing was displayed as horizontal bars of intensity defined as a wheeze power band, and the wheezing characteristics (number, frequency, and maximum intensity frequency) were evaluated by lung sound analysis. The participants were divided into two groups: non-disappears (wheezing did not disappear after inhalation) and disappears (wheezing disappeared after inhalation). Wheezing characteristics before β2-agonist inhalation were compared between the two groups. The characteristics of wheezing were not affected by body size. The number of wheeze power bands of the non-responder group was significantly higher than those of the responder group (P < 0.001). The number of wheeze power bands was a predictor of reactivity to inhaled β2-agonists, with a cutoff of 11.1. The 95% confidence intervals of sensitivity, specificity, and positive and negative predictive values were 88.8, 42, 44, and 81.1% (P < 0.001), respectively. Conclusions: The number of preinhalation wheeze power bands shown by lung sound analysis was a useful indicator before treatment. This indicator could be a beneficial index for managing wheezing in young children.

[Lung sounds can be used as an indicator for assessing severity of chronic obstructive pulmonary disease at the initial diagnosis]

OBJECTIVE

To assess the value of pulmonary auscultation for evaluating the severity of chronic obstructive pulmonary disease (COPD) at the initial diagnosis.

METHODS

The patients with newly diagnosed COPD in our hospital between May, 2016 and May, 2019 were enrolled in this study. According to the findings of pulmonary auscultation, the lung sounds were classified into 5 groups: normal breathing sounds, weakened breathing sounds, weakened breathing sounds with wheezing, obviously weakened breathing sounds, and obviously weakened breathing sounds with wheezing. The pulmonary function of the patients was graded according to GOLD guidelines, and the differential diagnosis of COPD from asthmatic asthma COPD overlap (ACO) was made based on the GOLD guidelines and the European Respiratory Criteria.

RESULTS

A total of 1046 newly diagnosed COPD patients were enrolled, including 949 male and 97 female patients with a mean age of 62.6± 8.71. According to the GOLD criteria, 88.1% of the patients were identified to have moderate or above COPD, 50.0% to have severe or above COPD; a further diagnosis of ACO was made in 347 (33.2%) of the patients. ANOVA analysis showed significant differences in disease course, FEV1, FEV1%, FEV1/FVC, FVC, FVC% and mMRC among the 5 auscultation groups (P < 0.001), but FENO did not differ significantly among them (P=0.097). The percentage of patients with wheezing in auscultation was significantly greater in ACO group than in COPD group (P < 0.001). Spearman correlation analysis showed that lung sounds was significantly correlated with disease severity, FEV1, FEV1%, FVC and FVC% of the patients (P < 0.001); Multiple linear regression analysis showed that a longer disease course, a history of smoking and lung sounds were all associated with poorer lung functions and a greater disease severity.

CONCLUSIONS

Lung sounds can be used as an indicator for assessing the severity of COPD at the initial diagnosis.

Lung Sound Analysis Provides A Useful Index For Both Airway Narrowing And Airway Inflammation In Patients With Bronchial Asthma

Background

The expiration-to-inspiration sound power ratio in a midfrequency range (E/I MF), a parameter of lung sound analysis (LSA), has been reported to be useful as an index of airway inflammation in patients with bronchial asthma. However, the E/I MF reflects airway narrowing caused by airway inflammation, and there is thus concern that it may not be an index of airway eosinophilic inflammation itself.

Methods

A total of 131 patients with bronchial asthma were classified into four groups according to the presence or absence of airway narrowing and airway inflammation to examine whether the E/I MF could serve as an index of airway inflammation.

Results

The E/I MF was significantly higher in patients with a normal forced expiratory volume in one second (FEV₁) and high fractional exhaled nitric oxide (FeNO), those with a low FEV₁ and normal FeNO, and those with a low FEV₁ and high FeNO than in those with a normal FEV₁ and normal FeNO (p < 0.05–0.01). In particular, the E/I MF was high even in the patients who had no airway narrowing but had airway inflammation (p < 0.01). The results of multivariate analysis of factors involved in FeNO in patients with a normal FEV₁ revealed that the E/I MF was an independent factor (p = 0.0281).

Conclusion

The E/I MF is a useful index of airway inflammation in the treatment of asthma, regardless of the presence or absence of airway narrowing.

A Lung Sound Category Recognition Method Based on Wavelet Decomposition and BP Neural Network

In this paper, a method of characteristic extraction and recognition on lung sounds is given. Wavelet de-noised method is adopted to reduce noise of collected lung sounds and extract wavelet characteristic coefficients of the de-noised lung sounds by wavelet decomposition. Considering the problem that lung sounds characteristic vectors are of high dimensions after wavelet decomposition and reconstruction, a new method is proposed to transform the characteristic vectors from reconstructed signals into reconstructed signal energy. In addition, we use linear discriminant analysis (LDA) to reduce the dimension of characteristic vectors for comparison in order to obtain a more efficient way for recognition. Finally, we use BP neural network to carry out lung sounds recognition where comparatively high-dimensional characteristic vectors and low- dimensional vectors are set as input and lung sounds categories as output with a recognition accuracy of 82.5% and 92.5%.

Phenotype classification using the combination of lung sound analysis and fractional exhaled nitric oxide for evaluating asthma treatment

BACKGROUND

We report the utility of combining lung sound analysis and fractional exhaled nitric oxide (FeNO) for phenotype classification of airway inflammation in patients with bronchial asthma. We investigated the usefulness of the combination of the expiration-to-inspiration sound power ratio in the mid-frequency range (E/I MF) of 200-400 Hz and FeNO for comprehensively classifying disease type and evaluating asthma treatment.

METHODS

A total of 233 patients with bronchial asthma were included. The cutoff values of FeNO and E/I MF were set to 38 ppb and 0.36, respectively, according to a previous study. The patients were divided into 4 subgroups based on the FeNO and E/I MF cutoff values. Respiratory function, the percentages of sputum eosinophils and neutrophils, and patient background characteristics were compared among groups.

RESULTS

Respiratory function was well controlled in the FeNO low/E/I MF low group (good control). Sputum neutrophil was higher and FEV₁,%pred was lower in the FeNO low/E/I MF high group (poor control). History of childhood asthma and atopic asthma were associated with the FeNO high/E/I MF low group (insufficient control). The FeNO high/E/I MF high group corresponded to a longer disease duration, increased blood or sputum eosinophils, and lower FEV₁/FVC (poor control).

CONCLUSIONS

The combination of FeNO and E/I MF assessed by lung sound analysis allows the condition of airway narrowing and the degree of airway inflammation to be assessed in patients with asthma and is useful for evaluating bronchial asthma treatments.