A Diagnostic Accuracy Study: N-Tidal Assessment for Respiratory Diagnosis Compared to Using Standard Testing

The diagnosis of either asthma or chronic obstructive pulmonary disease (COPD) is currently based on a combination of symptoms, different lung tests and sometimes a 'trial by treatment'. Both COPD and Asthma tests currently include forced breathing using a test known as spirometry which can be difficult and uncomfortable for people to perform and needs expert interpretation. Asthma can require multiple tests in sequence which can make the process of diagnosis long and inconvenient for patients. In the UK, there have been challenges providing enough testing for COPD and asthma, in part because the tests are challenging to provide in the community to everyone who needs one.

The STARDUST study aims to test and develop new ways of diagnosing asthma and COPD that are quick, accurate and easy for patient and healthcare professionals to perform. People who have been referred for routine lung testing will breathe normally in and out into a handheld device called the N-Tidal Handset for 75 seconds. This device measures how the level of carbon dioxide (CO2) changes in the breath as people breath through it. The information gathered on the N-Tidal Handsets, called breath records or capnograms, will not be used to alter the diagnosis of any participants in the study.

After the capnograms have been collected, the research team will test 'algorithms' that have been developed using artificial intelligence, to see if they can accurately identify the correct diagnosis. Information collected in the study will also be used to make improvements in these algorithms.

If confirmed to be accurate, these algorithms could be used in clinical practice to help healthcare professionals make faster, more accessible and accurate diagnoses, especially in settings like GP clinics in the community where access to specialist tests may be limited.