Does wheezing worsen when in a supine position?

Answer from top 1 papers

Based on the provided context, there is limited specific information about wheezing when lying down. However, we can draw some relevant insights from the papers:
Wheezing is a key indicator for diagnosing pulmonary illnesses like asthma and pneumonia (). It is often considered a symptom of potential respiratory disease and is associated with various factors, including smoking and vaping (). Wheezing can be triggered by multiple factors such as exercise, exposure to smoke, allergens, cold air, and viral infections ().
Interestingly, while the papers don't directly address wheezing when lying down, they highlight some important aspects of wheezing patterns. For instance, describes different wheezing phenotypes in infants, including persistent and incident wheezing. notes that wheezing following respiratory syncytial virus (RSV) lower respiratory tract infection has a seasonal pattern, suggesting that viral upper respiratory tract infections are a predominant trigger.
In conclusion, while the provided information doesn't specifically address wheezing when lying down, it's clear that wheezing can be influenced by various factors and can occur in different patterns. The position-specific aspect of wheezing when lying down might be related to changes in airway dynamics or increased mucus accumulation in this position, but further research would be needed to confirm this. For individuals experiencing wheezing when lying down, it would be advisable to consult with a healthcare professional for proper diagnosis and management.

Source Papers

125
10.3390/s17010171

Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection

Jan 17, 2017
Sensors (Basel, Switzerland)
Shih-Hong Li + 4 more +4

In the clinic, the wheezing sound is usually considered as an indicator symptom to reflect the degree of airway obstruction. The auscultation approach is the most common way to diagnose wheezing sounds, but it subjectively depends on the experience of the physician. Several previous studies attempted to extract the features of breathing sounds to detect wheezing sounds automatically. However, there is still a lack of suitable monitoring systems for real-time wheeze detection in daily life. In this study, a wearable and wireless breathing sound monitoring system for real-time wheeze detection was proposed. Moreover, a breathing sounds analysis algorithm was designed to continuously extract and analyze the features of breathing sounds to provide the objectively quantitative information of breathing sounds to professional physicians. Here, normalized spectral integration (NSI) was also designed and applied in wheeze detection. The proposed algorithm required only short-term data of breathing sounds and lower computational complexity to perform real-time wheeze detection, and is suitable to be implemented in a commercial portable device, which contains relatively low computing power and memory. From the experimental results, the proposed system could provide good performance on wheeze detection exactly and might be a useful assisting tool for analysis of breathing sounds in clinical diagnosis.