Predicting COPD flare-ups from data recorded by home non-invasive ventilators
SAGE-NIV: Surveillance and Artificial Intelligence Guidance for Exacerbations in COPD Patients With Home Non-Invasive Ventilation
This will try to use an AI program to find early signs of worsening COPD from data collected by people’s home non-invasive ventilators.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 75 (estimated) |
| Ages | 40 Years to 80 Years |
| Sex | All |
| Sponsor | Corporacion Parc Tauli Academic / other |
| Locations | 1 site (Sabadell, Barcelona) |
| Trial ID | NCT07267104 on ClinicalTrials.gov |
What this trial studies
This is an observational, longitudinal analysis of detailed pressure, flow and leak data recorded by home non-invasive ventilation (NIV) devices in people with COPD who meet adherence criteria. Participants continue their usual treatment and devices' archived data (from ResMed LUMIS 150 units) are decrypted, converted to an open format, and analyzed. Machine learning methods such as random forests and neural networks will be used to identify patterns that predict exacerbations and detect patient–ventilator asynchrony. The goal is to develop an automated predictive tool to improve remote monitoring and personalise home NIV management.
Who should consider this trial
Good fit: People aged 40–80 with COPD who have used home NIV (specifically the ResMed LUMIS 150) for at least 6 months with good adherence (≥5 hours/day) and who are experiencing an acute exacerbation requiring hospital admission or home care.
Not a fit: People who do not use home NIV, use other ventilator models, have poor adherence, or had recent antibiotic or steroid treatment that confounds the data may not benefit from this approach.
Why it matters
Potential benefit: If successful, the tool could provide earlier warnings of COPD exacerbations and improve remote monitoring and ventilator synchrony to reduce complications and hospital visits.
How similar studies have performed: Related machine-learning work on respiratory device and remote-monitoring data has shown promising pilot results, but robust, validated predictive tools specifically using home NIV data in COPD are still limited.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age between 40 and 80 years. * COPD diagnosed by pulmonary function tests. * Home NIV therapy with good adherence (minimum daily compliance \> 5 hours) for at least 6 months. * Users of the ResMed LUMIS 150 ventilator. This is due to the presence of the decoding tool and a larger storage capacity (more than 100 nights) in the removable device of the ventilator. * Acute exacerbation requiring hospital admission or home care. Exclusion Criteria: * Lack of informed consent. * Previous clinical instability defined by the need for antibiotics and/or systemic corticosteroids in the two months prior to the inclusion exacerbation, excluding the 48 hours prior to admission, as this was considered part of the inclusion clinical picture.
Where this trial is running
Sabadell, Barcelona
- Corporation Parc Tauli de Sabadell — Sabadell, Barcelona, Spain (Recruiting)
Study contacts
- Study coordinator: Manel Lujan, Professor MD pHD
- Email: mlujan@tauli.cat
- Phone: +34 937231010
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.