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

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

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.

Why it matters

Who can join: the full rules

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 it's running

• Oslo University Hospital
  Oslo, Norway Recruiting

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.