Clinical Trial: Eosinophilia Diagnosis

Study Status: Recruiting
Recruit Status: Recruiting
Study Type: Interventional

Official Title: Algorithm for the Early Diagnosis and Treatment of Patients With Eosinophilia

Brief Summary:

Eosinophilia, defined by a blood eosinophil granulocytes rate greater than 500 / mm3, is frequently encountered in internal medicine.

Its causes are varied: atopy, drug allergies, parasitic infections, autoimmune diseases and solid neoplasias. Over 200 etiologies have been reported, some difficult to diagnose and can be life-threatening Eosinophilia can be a diagnostic dilemma, as the etiologies are extensive and varied.

The aim of this study is to assess the feasibility of a diagnostic approach based on a decision algorithm in a group of patients with eosinophilia.

We assume that a procedure with a hierarchy of additional tests would increase the frequency of diagnosed cases while decreasing the time to diagnosis.

This procedure defined by an algorithm would even reduce the number of tests necessary to reach a diagnosis.


Detailed Summary:

Eosinophilia, defined by a blood eosinophil granulocytes rate greater than 500 / mm3, is frequently encountered in internal medicine.

Its causes are varied: atopy, drug allergies, parasitic infections, autoimmune diseases and solid neoplasias. Over 200 etiologies have been reported, some difficult to diagnose and can be life-threatening

Eosinophilia can be a diagnostic dilemma, as the etiologies are extensive and varied.

The aim of this study is to assess the feasibility of a diagnostic approach based on a decision algorithm in a group of patients with eosinophilia.

The contribution to the diagnosis of a hierarchical strategy for prescribing additional tests , based on clinical examination as well as some simple diagnostic tests, has never been evaluated

We assume that a procedure with a hierarchy of additional tests would increase the frequency of diagnosed cases while decreasing the time to diagnosis.

This procedure defined by an algorithm would even reduce the number of tests necessary to reach a diagnosis.

All types of patients are tacked into account: those coming from the university hospital, referred by general practitioners or by other hospitals.

In addition we address the internal medicine patients ,but also those of Hematology and Infectious Diseases. A comparison of these various groups would be relevant, since disorders that may be different.

Once enrolled, the patient is drived by the investigator through the various steps and exams imposed by the algorithm.

Sponsor: University Hospital, Limoges

Current Primary Outcome: Number of patients having correctly follow the diagnosis algorithm [ Time Frame: 5 months ]

This outcome measure how many patients have correctly followed the diagnosis algorithm


Original Primary Outcome: Same as current

Current Secondary Outcome:

  • Rate of diagnosis [ Time Frame: 5 months ]
    Evaluate the rate of diagnosis using our diagnosis algorithm
  • Assess the time to diagnosis [ Time Frame: 5 months ]
    Assess the time to diagnosis
  • Description of diagnosis [ Time Frame: 5 months ]
    To compare the diagnosis found in our study to the published cohort.


Original Secondary Outcome: Same as current

Information By: University Hospital, Limoges

Dates:
Date Received: October 19, 2015
Date Started: October 2015
Date Completion: November 2018
Last Updated: June 23, 2016
Last Verified: June 2016