Remote monitoring to predict asthma attacks in children and young people
Remote Monitoring of Asthma in Children and Young People - Reducing Risk of Asthma Attack Using a Connected Patient Approach
This project will test whether combining routine health records with home monitoring data can predict and reduce asthma attacks in children and young people aged 5-17.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 900 (estimated) |
| Ages | 5 Years to 17 Years |
| Sex | All |
| Sponsor | University of Edinburgh Academic / other |
| Locations | 1 site (Edinburgh) |
| Trial ID | NCT07129616 on ClinicalTrials.gov |
What this trial studies
The study will continuously monitor routine healthcare data for children and young people with asthma and apply machine-learning models to identify those at increased risk of an attack. A subset of participants flagged as high risk will be invited to provide additional remotely collected data such as symptom reports, inhaler use, and environmental measures from home devices and apps. Researchers will compare the rate of asthma attacks after using this prediction system with a historic average to see if attacks are reduced. The observational study is led by the University of Edinburgh and runs within NHS Lothian.
Who should consider this trial
Good fit: Children and young people aged 5-17 with a coded diagnosis or suspected asthma, or a prescription for inhaled corticosteroid in the prior two years, especially those identified as higher risk and living in the NHS Lothian area.
Not a fit: Patients with alternative lung diagnoses (cystic fibrosis, bronchiectasis, primary ciliary dyskinesia), those living outside the study region, or those unable or unwilling to use remote monitoring are unlikely to benefit from this program.
Why it matters
Potential benefit: If successful, the system could reduce asthma attacks and related hospital visits by giving earlier warning and enabling targeted support.
How similar studies have performed: Prior small studies and pilots using remote monitoring and machine-learning to predict asthma exacerbations have shown promising signals but evidence remains limited and not yet widely validated in large pediatric populations.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Children and Young People with a diagnosis of asthma (coded as asthma or suspected asthma) or a prescription of inhaled corticosteroid in the prior 2 years. Exclusion Criteria: * Alternative non-asthma diagnosis that would require inhaled steroid * cystic fibrosis * bronchiectasis * primary ciliary dyskinaesia
Where this trial is running
Edinburgh
- NHS Lothian — Edinburgh, United Kingdom (Recruiting)
Study contacts
- Study coordinator: kenneth a macleod, MbChB, PhD
- Email: Kenneth.Macleod3@nhs.scot
- Phone: +441313120453
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.