Wearable sensors and AI to detect chest infection flare-ups in adults with cystic fibrosis or bronchiectasis
Official title: Novel Sensors and Artificial Intelligence for Detection of Acute Pulmonary Exacerbations in Cystic Fibrosis and Non-Cystic Fibrosis Bronchiectasis
Run by Papworth Hospital NHS Foundation Trust · NCT07289100 · Data updated 2026-11-12
This study will try wearable sensors and AI to see if changes in breathing or heart rate can spot chest infection flare-ups early in adults with cystic fibrosis or bronchiectasis who are starting IV antibiotics.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 50 (estimated) |
| Sponsor | Papworth Hospital NHS Foundation Trust Government |
| Locations | 1 site (Cambridge, Cambridgeshire) |
| Status | Recruiting |
| Started | September 30, 2025 |
| Main results expected | March 31, 2026 |
| Study ends | April 30, 2026 |
| Registry record updated | December 17, 2025 |
| Trial ID | NCT07289100 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are adults (18+) under the care of Royal Papworth Hospital with a confirmed diagnosis of cystic fibrosis or CT-proven non-CF bronchiectasis who are starting IV antibiotics for an acute pulmonary exacerbation.
✕Probably not a fit
People who have had a lung transplant, are on the transplant waiting list, use long-term oxygen or non-invasive ventilation, are unwilling/unable to consent or to allow anonymised home monitoring data use, or who are admitted for elective (non-acute) antibiotic treatment are unlikely to benefit or be eligible.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study enrolls adults with cystic fibrosis or CT-confirmed non-CF bronchiectasis who are starting intravenous antibiotics for an acute pulmonary exacerbation. Participants will use novel sensors that record physiologic signals such as breathing rate and heart rate while clinical data are collected at the start and end of treatment. Artificial intelligence methods will be applied to the sensor data to look for measurable changes that correlate with the exacerbation and its resolution. There are no scheduled follow-up visits beyond the treatment episode and home monitoring data will be linked anonymised for research.
Why it matters
Potential benefit: If successful, the approach could enable earlier detection of pulmonary exacerbations so treatment can begin sooner and potentially reduce lung damage.
How similar studies have gone: Early research using wearables and AI in other respiratory conditions has shown promise, but applying these sensors to predict exacerbations in CF and bronchiectasis is still largely novel and unproven.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * ≥ 18 years old * Diagnosis of CF based on genetic testing and /or sweat chloride levels or CT confirmed diagnosis of non-CF bronchiectasis * Under the care of Royal Papworth Hospital * Starting IV antibiotics for treatment of APE as defined by the Hill Criteria ² Exclusion Criteria: * Patients unable to provide written informed consent * Lung transplant recipients or on lung transplant waiting list * Use of long-term oxygen therapy (LTOT) or non-invasive ventilation to manage respiratory failure * Patients unwilling to consent to their link anonymised data from home monitoring being used for research * Considered unsuitable for home monitoring in the opinion of the investigator * Patients being admitted for elective antibiotic treatment (i.e. not being admitted for acute APE treatment)
Where it's running
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Royal Papworth Hospital NHS Foundation Trust
Cambridge, Cambridgeshire, United Kingdom Recruiting
Study contacts
- Principal investigator: Andres Floto — University of Cambridge
- Study coordinator: Lucy E Gale
- Email: lucy.gale1@nhs.net
- Phone: +44 1223 638000
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.