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

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

Recruiting
18 years and older
All
Phase N/A
  • Technical (Original)
  • Simplified (AI rewritten)

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Overview

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.

Eligibility

Inclusion Criteria:

  1. 18 years of age or over
  2. A diagnosis of EGPA or HES
  3. 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

Exclusion Criteria:

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

Study details
    EGPA - Eosinophilic Granulomatosis With Polyangiitis
    HES - Hypereosinophilic Syndrome

NCT07275190

Fondazione IRCCS Policlinico San Matteo di Pavia

31 January 2026

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