The Use of Machine Learning Techniques for the Differential Diagnosis Between Eosinophilic Granulomatosis With Polyangiitis and Hypereosinophilic Syndrome

Recruiting now · Not applicable

Conditions studied: EGPA - Eosinophilic Granulomatosis With Polyangiitis, HES - Hypereosinophilic Syndrome

In brief

The purpose of this study is to collect clinical, laboratory, and instrumental data from patients with eosinophilic granulomatosis with polyangiitis or hypereosinophilic syndrome, which will then be analyzed using artificial intelligence techniques with the aim of identifying characteristics that differentiate the two diseases and can predict the response to the treatment plan.

Key facts

Study ID

NCT07275190

Run by

Fondazione IRCCS Policlinico San Matteo di Pavia

People needed

60

Starts

2025-06-01

Expected to finish

2026-12-01

Last updated by the study team

2025-12-10

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• 18 years of age or over
• A diagnosis of EGPA or HES
• Willing and able to give informed written consent, or willing to give permission for a nominated friend or relative to provide written informed assent if they are unable to do so because of physical disabilities

You may not qualify if…

• Lack of a confirmed diagnosis of EGPA or HES.
• Other causes of eosinophilia

Where it is running

• Fondazione IRCCS Policlinico San Matteo, SC Reumatologia — Pavia, Italy (enrolling)

Full record on ClinicalTrials.gov

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