Machine learning to detect inspiratory leak in long-term non-invasive ventilation

From Bench to Bedside: A Machine Learning Tool for the Detection of Inspiratory Leak

Observational University of Oslo · NCT07428694

This project tries to use a machine-learning program to detect inspiratory leaks in people with chronic respiratory failure who use long-term non-invasive ventilation.

Quick facts

Study typeObservational
Enrollment20 (estimated)
Ages18 Years and up
SexAll
SponsorUniversity of Oslo Academic / other
Locations1 site (Oslo)
Trial IDNCT07428694 on ClinicalTrials.gov

What this trial studies

This observational project developed a machine-learning model to spot inspiratory leaks during long-term non-invasive ventilation. The model was first trained using a bench model with created leak scenarios plus data from ten patients. The trained model was then tested in a proof-of-concept pilot involving ten additional patients during elective hospital visits. Participants used ResMed Lumis 100/150 ventilators and were on treatment for more than three months.

Who should consider this trial

Good fit: Ideal candidates are people with chronic respiratory failure who have been on long-term non-invasive ventilation for over three months, use a ResMed Lumis 100/150 ventilator, and can attend elective hospitalization for NIV control without a current exacerbation.

Not a fit: People experiencing an acute exacerbation, those who use other ventilator models, or those unable to attend hospitalization are unlikely to benefit from this specific project.

Why it matters

Potential benefit: If successful, the tool could help clinicians identify and reduce inspiratory leaks more quickly, improving ventilation effectiveness and patient comfort.

How similar studies have performed: Similar machine-learning approaches have shown limited, preliminary success in bench and small pilot studies, but broad clinical validation is still limited.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* elective hospitalisation for control of non-invasive ventilation
* use of ResMedLumis 100/150 ventilator
* treatment for \>3 months

Exclusion Criteria:

* current exacerbation

Where this trial is running

Oslo

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Chronic Respiratory Failure
Last reviewed 2026-06-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.