Using AI to predict asthma severity in children
Integrating Deep Learning CT-scan Model, Biological and Clinical Variables to Predict Severity of Asthma in Children
This study is testing whether using artificial intelligence can help doctors predict how severe asthma will be in children so they can provide better care.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 25 (estimated) |
| Ages | 6 Years to 17 Years |
| Sex | All |
| Sponsor | Fondazione IRCCS Policlinico San Matteo di Pavia Academic / other |
| Locations | 1 site (Pavia) |
| Trial ID | NCT05140889 on ClinicalTrials.gov |
What this trial studies
This project aims to leverage artificial intelligence, specifically deep learning techniques, to analyze clinical, biological, and radiological data from pediatric patients diagnosed with severe asthma. By building a comprehensive database and training a predictive model, the study seeks to accurately forecast asthma severity and understand the transition probabilities between different severity levels. The integration of CT imaging data with clinical scores is expected to enhance the precision of asthma severity predictions, ultimately aiding pediatricians in formulating timely intervention strategies.
Who should consider this trial
Good fit: Ideal candidates for this study are children aged 6 to 17 years with a confirmed diagnosis of severe asthma.
Not a fit: Patients with other diseases that may mimic asthma, such as cystic fibrosis or tracheobronchomalacia, may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to more accurate predictions of asthma severity in children, allowing for personalized treatment plans and improved patient outcomes.
How similar studies have performed: Other studies have shown promising results in using AI and deep learning for medical imaging analysis, indicating potential success for this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * age 6-17 years * confirmed diagnosis of severe asthma according to ERS/ATS guidelines Exclusion Criteria: * other diseases that may mimic asthma according to ERS/ATS guidelines (i.e., cystic fibrosis, primary ciliary dyskinesia, tracheobronchomalacia, etc)
Where this trial is running
Pavia
- IRCCS Policlinico San Matteo — Pavia, Italy (Recruiting)
Study contacts
- Principal investigator: Amelia Licari, MD — IRCCS Policlinico San Matteo
- Study coordinator: Amelia Licari, MD
- Email: a.licari@smatteo.pv.it
- Phone: +39(0)382502629
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.