Respiratory diseases are a common cause of mortality and disability at the worldwide and national levels. Many of them are characterized by underdiagnosis and diagnosis in advanced stages of the disease, and in most of them, forced spirometry is one of the fundamental tools to assess the diagnosis and seriousness of the disease. To help in improving the detection of respiratory diseases and the understanding of the respiratory health of the general population, one possible solution would be to develop a mobile application that could assess respiratory health by using the sound signal of exhaled air recorded by a mobile microphone. This project will aim to validate a mobile application (WebApp) for the detection of pulmonary function disorders. It is planned to recruit 267 subjects, with and without respiratory disease, who are attended in pulmonary function laboratories of 10 Spanish hospitals, to compare the sensitivity of this application in the diagnosis of pulmonary function disorders (either obstructive patterns or PRISm) versus the gold standard (spirometry). Ease of use and user satisfaction with the application will also be assessed.
Study Type
OBSERVATIONAL
Enrollment
275
all participants will undergo an assessment of respiratory health by analyzing the sound of exhaled air recorded by the participant's mobile phone
Hospital Universitario Virgen de las Nieves
Granada, Spain
RECRUITINGHospital Universitario La Paz
Madrid, Spain
RECRUITINGMain Outcome
Proportion of lung function abnormalities (defined as FEV1/FVC\<0.7 or LLN) detected with the mobile app
Time frame: At the time of assessment
Secondary Outcome
To analize the diagnostic performance from web app to detect different lung function abnormalities
Time frame: At the time of assessment
Secondary Outcome
To evaluate concordancy between lung function estimates obtained with a mobile app and spirometers
Time frame: At the time of assessment
Secondary Outcome
Proportion of lung function abnormalities (defined as FVC \<80% predicted or LLN) detected with the mobile app
Time frame: At the time of assessment
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