AzTrials
AzTrials

Asthma (Diagnosis)STARDUSTNCT07253883

A Study to Understand the Accuracy of a New Breathing Device Compared to Standard Testing for Asthma and COPD

An observational study of Asthma (Diagnosis) and COPD (Chronic Obstructive Pulmonary Disease), run by Liverpool Heart and Chest Hospital NHS Foundation Trust at 1 site in United Kingdom.

Recruiting

Looking for participants now. Contact the study team or a site below to ask about taking part.

Sites and contacts
Official record

Search all trials

Trial summary

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'. Read more about this study

Who is it for?
Ages 18 to 110 years
What is being tested?
Partial pressure of CO2 during tidal breathing, FENO and Spirometry
How many people
1,200 participants
Where
1 siteUnited Kingdom
Study dates
15 Sep 2026to 19 May 2027
Phase
Observational

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 to 110 years
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Study population: Participants with a suspicion of asthma and/or COPD

Who may be able to join

  • Age ≥ 18 years
  • Referred for respiratory diagnostic testing with a clinical suspicion of asthma or COPD
  • Participant is willing and able to provide informed consent

Who cannot join

  • Referred for respiratory diagnostic testing for a condition other than asthma or COPD, with no mention in the referral of a clinical suspicion of COPD or asthma
  • Participants who, in the opinion of the chief investigator, or their delegate, are unlikely to comply with the requirements of the study
  • Inability to give written informed consent
  • Participants who are acutely unwell
  • Patients unable to breathe through their mouths e.g. tracheostomy patients

Trial locations and contacts

1 site in 1 country. Contact the study team or a site near you to ask about taking part.

Hassan Burhan, MBChB FRCP contact

0151 254 3036

Hassan.Burhan@liverpoolft.nhs.uk

Thomas FitzMaurice, MBChB BSc PGCME MRCP(UK) PhD contact

0151 254 3055

United Kingdom1 site, 1 recruiting
  • Liverpool Heart and Chest Hospital NHS Foundation Trust

    Liverpool, Merseyside, L14 3PE

    Freddy Frost, BMedSci BMBS MRCP MD, 0151 600 1616, freddy.frost@lhch.nhs.uk

    Recruiting

Other trials in United Kingdom

About this study

Official title: 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.

Read more

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.

Read the detailed description

COPD is one of the leading causes of disability and in the top five causes of death worldwide. Early diagnosis and treatment are essential to slow the decline of lung function and improve quality of life.

The current standard for diagnosing COPD is spirometry; an effort-dependent test that requires supervised use, by a specifically trained medical professional, in a clinic-based environment. It is estimated that up to 2/3 of cases are undiagnosed suggesting that there is a significant care gap in the ability to accurately diagnose COPD.

Asthma is a chronic respiratory disease, characterised by airway inflammation and hyper-responsiveness. In 2019 affected an estimated 262 million people. Early diagnosis and treatment are important to reduce symptoms, exacerbations and mortality and to improve overall quality of life. The confirmation of reversible airflow obstruction using pre- and post-bronchodilator (BD) spirometry is needed to confirm a diagnosis in those suspected as having asthma without evidence of inflammation in the airways or blood.

Spirometry can be challenging for patients to perform, is time consuming and can be challenging to deliver at the scale required by the population.

TidalSense have been developing respiratory diagnostic devices that could offer simpler, safe, fast, reliable and precise tests to diagnose both COPD and asthma.

It is anticipated that successfully meeting the primary objectives of this study will result in data on the diagnostic accuracy of the COPD diagnostic models and could lead to the development and improvement of all diagnostic algorithms used in the study. This may contribute to a range of future clinical benefits:

  • Accurate diagnosis of asthma and/or COPD
  • Accurate detection of severe COPD in patients who are likely or highly likely to have COPD
  • Improved ease of testing for asthma and/or COPD for patients and healthcare professionals
  • Clearer differentiation between asthma and COPD in patients with overlapping symptoms

These benefits could enable quicker testing, improve patient experience (relaxed breathing instead of forced breathing), and improve patient access to testing compared to current diagnostic pathways and reduce misdiagnosis.

Being tested
Partial pressure of CO2 during tidal breathing, FENO, Spirometry
Keywords
Asthma, COPD, End tidal CO2, Diagnostics, Machine learning
Medical subject headings
Asthma, Disease, Pulmonary Disease, Chronic Obstructive

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • Partial pressure of CO2 during tidal breathingDiagnostic test

    Partial pressure of CO2 during tidal breathing for diagnosis of asthma or COPD

  • FENODiagnostic test

    Also called Fractional exhaled nitric oxide

    Fractional exhaled nitric oxide

  • SpirometryDiagnostic test

    Spirometry with or without bronchodilation (if indicated)

Study groups in NCT07253883
Study groupRoleWhat they receive
AsthmaPatients with suspected asthma
Receives: Diagnostic Test: Partial pressure of CO2 during tidal breathing; Diagnostic Test: FENO; Diagnostic Test: Spirometry
COPDPatients with suspected COPD
Receives: Diagnostic Test: Partial pressure of CO2 during tidal breathing; Diagnostic Test: FENO; Diagnostic Test: Spirometry

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Diagnostic accuracy of the diagnostic algorithms of N-Tidal Diagnose 1

    PPV, NPV, Sensitivity, Specificity compared to clinician diagnosis of COPD

    Measured: At time of testing

  2. Diagnostic accuracy of prototype diagnostic algorithms

    Prototype asthma diagnostic algorithms (index test; PPV, NPV, Sensitivity, Specificity) trained using a combined capnogram dataset from this and previous studies, compared to clinician diagnosis of asthma

    Measured: At time of testing

Secondary outcomes (2)
  1. Diagnostic accuracy of the N-Tidal Diagnose 1 severity algorithm

    Diagnostic accuracy (PPV, NPV, Sensitivity, Specificity) of the N-Tidal Diagnose 1 severity algorithm in those with a confirmed diagnosis of COPD. Diagnostic accuracy (PPV, NPV, Sensitivity, Specificity) of the diagnostic algorithms embedded in NTidal Diagnose 1 v1.0 in relevant subgroups. Diagnostic accuracy (PPV, NPV, Sensitivity, Specificity) of the pre-production asthma diagnostic algorithms trained using a combined capnogram dataset from this and previous studies in relevant prespecified subgroups. Exploratory analysis of novel machine learning diagnostic algorithms for COPD and asthma.

    Measured: At time of diagnosis

  2. Feasibility and acceptability outcomes

    Visual Analogue Score (VAS) following N-Tidal, spirometry and FeNO (ease of use and comfort for participants, ease of use only for administering healthcare professionals) in a subset of participants. Percentage of participants with a clinical suspicion of COPD with adequate N-Tidal Handset breath record capture, sufficient to generate a diagnostic output using N-Tidal Diagnose 1 v1.0 diagnostic algorithms. Percentage of participants with a clinical suspicion of asthma with adequate N-Tidal Handset breath record capture, sufficient to generate a diagnostic output using prototype asthma diagnostic algorithms.

    Measured: At time of diagnosis

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted28 Nov 2025
  2. Study start15 Sep 2026
  3. Primary completion19 May 2027 (estimated)
  4. Study completion19 May 2027 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Prospective
Enrolment
1,200 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT07253883
Sponsor's protocol ID
1694
Acronym
STARDUST
Status last verified
Oct 2026
First submitted
19 Nov 2025
Last updated
15 Oct 2026
Results posted
No
Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
Yes: Data may be shared for future research under appropriate governance as per the terms of the collaboration agreement between TidalSense and the Liverpool Heart and Chest Hospital NHS Foundation Trust.

Free account

Keep searching with a free account

You’ve used your 3 free searches for this session. Log in or create a free AzTrials account to keep searching clinical trials and save the ones you want to follow.

Create a free accountLog in