Chronic Respiratory FailureNCT07428694
From Bench to Bedside: A Machine Learning Tool for the Detection of Inspiratory Leak
An observational study of Chronic Respiratory Failure, run by University of Oslo at 1 site in Norway.
Trial summary
Study of the applicability of machine learning tools in detecting inspiratory leakage in longterm non-invasive ventilation. The study was conducted in two stages. Firstly the ML model was trained on both bench model created scenarios and then ten patients. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Chronic Respiratory Failure
- How many people
- 20 participants
- Where
- 1 siteNorway
- Study dates
- 1 Oct 2025to 1 Oct 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients undergoing treatment with Lumis 100/150 for type 2 chronic resiratory failure
Who may be able to join
- elective hospitalisation for control of non-invasive ventilation
- use of ResMedLumis 100/150 ventilator
- treatment for >3 months
Who cannot join
- current exacerbation
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Norway1 site, 1 recruiting
- Recruiting
Oslo University Hospital
Oslo
Marte Allgot, Cand.med, +4799616202, m.s.allgot@medisin.uio.no
S, +4799616202
About this study
Study of the applicability of machine learning tools in detecting inspiratory leakage in longterm non-invasive ventilation. The study was conducted in two stages. Firstly the ML model was trained on both bench model created scenarios and then ten patients. And secondly the success of the model was assessed in a proof of concept pilot study of ten patients.
- Conditions
- Chronic Respiratory Failure
What is being measured
The primary outcome is the main question the study is designed to answer.
Correct interpretation of inspiratory leak by machine learning tool
Measured in comparison with god standard method of polygraphy
Measured: one year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Feb 2026
- Study start1 Oct 2025
- Primary completion1 Oct 2026 (estimated)
- Study completion1 Oct 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Chronic Respiratory FailureStudies 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
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 20 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Oslo
- Sponsor type
- University, hospital or other
- Collaborators
- Oslo University Hospital
- Responsible party
- Principal investigator, Marte Skogstad Allgot, University of Oslo
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07428694
- Sponsor's protocol ID
- 878631
- Status last verified
- Feb 2026
- First submitted
- 17 Feb 2026
- Last updated
- 24 Feb 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- From Bench to Bedside: A Machine Learning Tool for the Detection of Inspiratory Leak
- ClinicalTrials.gov ID
- NCT07428694
- Acronym / sponsor ID
- 878631
- Conditions
- Chronic Respiratory Failure
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 20 participants (estimated)
- Lead sponsor
- University of OsloUniversity, hospital or other
- Collaborators
- Oslo University Hospital
- Study start
- 1 Oct 2025 (actual)
- Primary completion
- 1 Oct 2026 (estimated)
- Study completion
- 1 Oct 2026 (estimated)
- First posted
- 24 Feb 2026 (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.
Study of the applicability of machine learning tools in detecting inspiratory leakage in longterm non-invasive ventilation. The study was conducted in two stages. Firstly the ML model was trained on both bench model created scenarios and then ten patients. And secondly the success of the model was assessed in a proof of concept pilot study of ten patients.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients undergoing treatment with Lumis 100/150 for type 2 chronic resiratory failure
Key inclusion criteria (3 listed)
- elective hospitalisation for control of non-invasive ventilation
- use of ResMedLumis 100/150 ventilator
- treatment for >3 months
Key exclusion criteria (1 listed)
- current exacerbation
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Correct interpretation of inspiratory leak by machine learning tool
Time frame: one year
Measured in comparison with god standard method of polygraphy
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Feb 2026.
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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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Chronic Respiratory Failure, run by University of Oslo at 1 site in Norway.
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: looking for participants now, as of the sponsor's last update on 24 Feb 2026. 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 Norway. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Correct interpretation of inspiratory leak by machine learning tool (time frame: one year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 24 Feb 2026.