Clinical trial Recruiting at 1 site Observational Ages 18 and up

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.

More Cystic Fibrosis (CF) trials

Quick facts

Study typeObservational
Ages18 Years and up
SexAll
Enrollment50 (estimated)
SponsorPapworth Hospital NHS Foundation Trust
Government
Locations1 site (Cambridge, Cambridgeshire)
StatusRecruiting
StartedSeptember 30, 2025
Main results expectedMarch 31, 2026
Study endsApril 30, 2026
Registry record updatedDecember 17, 2025
Trial IDNCT07289100 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

  • Royal Papworth Hospital NHS Foundation Trust
    Cambridge, Cambridgeshire, United Kingdom
    Recruiting

Study contacts

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

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.
Last reviewed 2026-11-14 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.