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Sponsor: University of Edinburgh
Conditions: Asthma Childhood, Asthma Attack, Remote Monitoring, Risk Assessment, Machine Learning
Countries: United Kingdom
The objective of this study is to determine whether healthcare data and remotely collected patient data can accurately predict asthma attacks in children and young people aged 5-17 years. The main outcome is: when using this new system, is there a reduction in asthma attacks compared with a historic average. The whole population of children and young people with asthma will have routine healthcare data monitored, with a subset of people with high risk asthma asked to participate in a more detail study involving remotely monitored data.
Sex: ALL
Age: 5 Years to 17 Years
Healthy volunteers: No
Study type: OBSERVATIONAL
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
- Edinburgh, United Kingdom