Lung DiseaseSPIRO-AIDNCT05933694
Spirometry Interpretation Performance of Primary Care Clinicians With/Without AI Software
A study testing Artificial Intelligence-powered Spirometry Interpretation Report in people with Lung Disease, run by Royal Brompton & Harefield NHS Foundation Trust at 1 site in United Kingdom.
Trial summary
To evaluate whether an artificial intelligence decision support software (ArtiQ.Spiro) improves the diagnostic accuracy of spirometry interpreted by primary care clinicians, as measured by Clinician Diagnostic Accuracy (vs Reference Standard). Read more about this study
- Who is it for?
- Ages 18 to 99 yearsHealthy volunteers can take part
- Conditions the study is for
- Lung Disease
- What is being tested?
- Artificial Intelligence-powered Spirometry Interpretation Report
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 228 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 27 Jun 2023to 30 Sep 2024
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 99 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Clinicians working in primary care (for at least 50% of their job plan) in the UK, who refer for or perform spirometry (typically GP, practice nurse)
- Able to access spirometry traces on study platform
- Provide written informed consent via study platform
Who cannot join
- 1. Clinicians who have completed specialist training in respiratory medicine and recognised by the General Medical Council with a right to practise as a NHS consultant in respiratory medicine
Trial locations and contacts
1 site in 1 country.
United Kingdom1 site, 1 recruiting
- Recruiting
Royal Brompton & Harefield Hospitals
Uxbridge, UB9 6JH
Ethaar El-Emir, PhD, 01895 823737 ext. 85952, e.el-emir@rbht.nhs.uk
George Edwards, MSc, 01895 823737, G.Edwards2@rbht.nhs.uk
About this study
Official title: A Randomized Controlled Trial Comparing Performance of Primary Care Clinicians in the Interpretation of SPIROmetry With or Without Artificial Intelligence Decision Support Software
To evaluate whether an artificial intelligence decision support software (ArtiQ.Spiro) improves the diagnostic accuracy of spirometry interpreted by primary care clinicians, as measured by Clinician Diagnostic Accuracy (vs Reference Standard).
Read the detailed description
This is a randomised controlled study to evaluate the effects of AI support software on the performance of primary care clinicians in the interpretation of spirometry. Clinicians will be provided with a clinical dataset of 50 entirely anonymous, previously recorded real-world spirometry records to interpret and will be asked to complete specific questions about diagnosis and quality assessment. The records will be randomly selected from a database comprising spirometry records from 1122 patients undergoing spirometry in primary care and community -based respiratory clinics in Hillingdon borough between 2015-2018.
Participating clinicians will be allocated at random to receive either spirometry records alone or spirometry records with the addition of an AI spirometry interpretation eport. The clinical spirometry records will be de-identified (name, date of birth, address, postcode, occupation, GP, medications data removed), by a member of the clinical care team.
Study participants (participating clinicians) will independently examine the same 50 spirometry records through an online platform. For each spirometry record, the primary care clinician participant will answer questions about technical quality, pattern interpretation, preferred diagnosis, differential diagnosis and self-rated confidence with these answers.
The study statistician will be blinded to treatment allocation up to completion of analysis and interpretation.
The reference standards for spirometry technical quality and pattern interpretation will be made by a senior experienced respiratory physiologist but without access to AI report.
The reference standard for diagnosis will be made by a panel of three respiratory specialists from the clinical care team with access to medical notes and results of relevant investigations but without access to AI report.
- Conditions
- Lung Disease
- Being tested
- Artificial Intelligence-powered Spirometry Interpretation Report
- Medical subject headings
- Lung Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence-powered Spirometry Interpretation ReportOther
Also called ArtiQ.Spiro
A report generated by artificial intelligence powered software that assessed technical quality of spirometry and estimates the diagnostic probability of six categories: COPD/Asthma/ILD/ Normal/Other obstructive/Other Unidentified
| Study group | Role | What they receive |
|---|---|---|
| Control | No intervention | Participants to report 50 spirometry records alone |
| Intervention | Experimental | Participants report the same 50 spirometry records provided in the control arm with an artificial intelligence-powered spirometry interpretation report Receives: Other: Artificial Intelligence-powered Spirometry Interpretation Report |
What is being measured
The primary outcome is the main question the study is designed to answer.
Preferred Diagnostic Performance
A correct case is where the preferred diagnosis matches the reference final diagnosis. Units will be percentage of total cases that are correct.
Measured: Six months
Secondary outcomes (6)
Pattern interpretation
A correct case is where the participants' selected pattern matches the reference pattern. Options are: Normal, Airflow obstruction, Possible restriction or non-specific pattern, Possible Mixed Disorder. Units will be percentage of total cases that are correct.
Measured: Six months
Differential diagnostic performance
A correct case is where the preferred or differential diagnosis matches the reference final diagnosis. Units will be percentage of total cases that are correct.
Measured: Six months
Quality assessment performance
A correct case is where the participant's quality grade matches the reference quality grade. Options are: Acceptable (Grade A/B) or Not Acceptable (Grades C/D/E/F/U). Units will be percentage of total cases that are correct.
Measured: Six months
Pattern interpretation self-rated confidence
Pattern interpretation self-rated confidence will be measured on a visual analogue scale (0-10) where 0 = not confident at all; 10= very confident)
Measured: Six months
Diagnostic self-rated confidence
Diagnostic self-rated confidence will be measured on a visual analogue scale (0-10) where 0 = not confident at all; 10= very confident)
Measured: Six months
Quality Assessment self-rated confidence
Quality Assessment self-rated confidence will be measured on a visual analogue scale (0-10) where is 0 = not confident at all; 10= very confident)
Measured: Six months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Jul 2023
- Study start27 Jun 2023
- Primary completion27 Jun 2024 (estimated)
- Study completion30 Sep 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Lung DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Investigator, Outcomes assessor
- Enrolment
- 228 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Royal Brompton & Harefield NHS Foundation Trust
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute for Health Research, United Kingdom
- Responsible party
- Sponsor
- Investigators
- William Man, Principal investigator, Royal Brompton & Harefield Hospitals
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05933694
- Sponsor's protocol ID
- 323361
- Acronym
- SPIRO-AID
- Status last verified
- Feb 2024
- First submitted
- 27 Jun 2023
- Last updated
- 16 Feb 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Doe G, Banya W, Edwards G, Topalovic M, El-Emir E, Evans RA, Russell R, Smets E, Van Orshoven K, Sylvester KP, Sunjaya AP, Scott DA, De Vos M, Elmahy A, Taylor SJC, Hutchinson A, Hopkinson NS, Morgan M, Kon SS, Patel S, Jarrold I, Kennington E, Sehdev S, Spain N, Toby Prevost A, Man WD. AI-Assisted Spirometry Interpretation in Primary Care: A Randomized Controlled Trial. NEJM AI. 2025 Aug;2(8):AIoa2400804. doi: 10.1056/AIoa2400804. Epub 2025 Jul 24.
PubMed 42932578Doe G, El-Emir E, Edwards GD, Topalovic M, Evans RA, Russell R, Sylvester KP, Van Orshoven K, Sunjaya AP, Scott DA, Prevost AT, Harvey J, Taylor SJ, Hopkinson NS, Kon SS, Jarrold I, Spain N, Banya W, Man WD. Comparing performance of primary care clinicians in the interpretation of SPIROmetry with or without Artificial Intelligence Decision support software (SPIRO-AID): a protocol for a randomised controlled trial. BMJ Open. 2024 Jul 1;14(6):e086736. doi: 10.1136/bmjopen-2024-086736.
PubMed 38950987
Study at a glance
From the registry record, last updated by the sponsor on 16 Feb 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Randomized Controlled Trial Comparing Performance of Primary Care Clinicians in the Interpretation of SPIROmetry With or Without Artificial Intelligence Decision Support Software
- ClinicalTrials.gov ID
- NCT05933694
- Acronym / sponsor ID
- SPIRO-AID / 323361
- Conditions
- Lung Disease
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 228 participants (estimated)
- Lead sponsor
- Royal Brompton & Harefield NHS Foundation TrustUniversity, hospital or other
- Collaborators
- National Institute for Health Research, United Kingdom
- Study start
- 27 Jun 2023 (actual)
- Primary completion
- 27 Jun 2024 (estimated)
- Study completion
- 30 Sep 2024 (estimated)
- First posted
- 6 Jul 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
To evaluate whether an artificial intelligence decision support software (ArtiQ.Spiro) improves the diagnostic accuracy of spirometry interpreted by primary care clinicians, as measured by Clinician Diagnostic Accuracy (vs Reference Standard).
Detailed description
This is a randomised controlled study to evaluate the effects of AI support software on the performance of primary care clinicians in the interpretation of spirometry. Clinicians will be provided with a clinical dataset of 50 entirely anonymous, previously recorded real-world spirometry records to interpret and will be asked to complete specific questions about diagnosis and quality assessment. The records will be randomly selected from a database comprising spirometry records from 1122 patients undergoing spirometry in primary care and community -based respiratory clinics in Hillingdon borough between 2015-2018.
Participating clinicians will be allocated at random to receive either spirometry records alone or spirometry records with the addition of an AI spirometry interpretation eport. The clinical spirometry records will be de-identified (name, date of birth, address, postcode, occupation, GP, medications data removed), by a member of the clinical care team.
Study participants (participating clinicians) will independently examine the same 50 spirometry records through an online platform. For each spirometry record, the primary care clinician participant will answer questions about technical quality, pattern interpretation, preferred diagnosis, differential diagnosis and self-rated confidence with these answers.
The study statistician will be blinded to treatment allocation up to completion of analysis and interpretation.
The reference standards for spirometry technical quality and pattern interpretation will be made by a senior experienced respiratory physiologist but without access to AI report.
The reference standard for diagnosis will be made by a panel of three respiratory specialists from the clinical care team with access to medical notes and results of relevant investigations but without access to AI report.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (investigator, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Control | No intervention | –Participants to report 50 spirometry records alone |
| Intervention | Experimental | Other: Artificial Intelligence-powered Spirometry Interpretation ReportParticipants report the same 50 spirometry records provided in the control arm with an artificial intelligence-powered spirometry interpretation report |
Who may qualify
- Ages
- 18 to 99 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Clinicians working in primary care (for at least 50% of their job plan) in the UK, who refer for or perform spirometry (typically GP, practice nurse)
- Able to access spirometry traces on study platform
- Provide written informed consent via study platform
Key exclusion criteria (1 listed)
- 1. Clinicians who have completed specialist training in respiratory medicine and recognised by the General Medical Council with a right to practise as a NHS consultant in respiratory medicine
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence-powered Spirometry Interpretation ReportAlso: ArtiQ.SpiroA report generated by artificial intelligence powered software that assessed technical quality of spirometry and estimates the diagnostic probability of six categories: COPD/Asthma/ILD/ Normal/Other obstructive/Other Unidentified | Other | Intervention |
Primary outcome
Preferred Diagnostic Performance
Time frame: Six months
A correct case is where the preferred diagnosis matches the reference final diagnosis. Units will be percentage of total cases that are correct.
6 secondary outcomes
Pattern interpretation
Time frame: Six months
Differential diagnostic performance
Time frame: Six months
Quality assessment performance
Time frame: Six months
Pattern interpretation self-rated confidence
Time frame: Six months
Diagnostic self-rated confidence
Time frame: Six months
Quality Assessment self-rated confidence
Time frame: Six months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 Feb 2024.
- Derived from this study: PubMed 42932578Doe G, Banya W, Edwards G, Topalovic M, El-Emir E, Evans RA, Russell R, Smets E, Van Orshoven K, Sylvester KP, Sunjaya AP, Scott DA, De Vos M, Elmahy A, Taylor SJC, Hutchinson A, Hopkinson NS, Morgan M, Kon SS, Patel S, Jarrold I, Kennington E, Sehdev S, Spain N, Toby Prevost A, Man WD. AI-Assisted Spirometry Interpretation in Primary Care: A Randomized Controlled Trial. NEJM AI. 2025 Aug;2(8):AIoa2400804. doi: 10.1056/AIoa2400804. Epub 2025 Jul 24.
- Derived from this study: PubMed 38950987Doe G, El-Emir E, Edwards GD, Topalovic M, Evans RA, Russell R, Sylvester KP, Van Orshoven K, Sunjaya AP, Scott DA, Prevost AT, Harvey J, Taylor SJ, Hopkinson NS, Kon SS, Jarrold I, Spain N, Banya W, Man WD. Comparing performance of primary care clinicians in the interpretation of SPIROmetry with or without Artificial Intelligence Decision support software (SPIRO-AID): a protocol for a randomised controlled trial. BMJ Open. 2024 Jul 1;14(6):e086736. doi: 10.1136/bmjopen-2024-086736.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
William Man principal investigator
Royal Brompton & Harefield Hospitals
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial Intelligence-powered Spirometry Interpretation Report in people with Lung Disease, run by Royal Brompton & Harefield NHS Foundation Trust at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 16 Feb 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Ethaar El-Emir, PhD (01895 823737 ext. 85952, e.el-emir@rbht.nhs.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Preferred Diagnostic Performance (time frame: Six months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05933694, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 16 Feb 2024.