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.
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. Indeed, during 5 months (Day1 5, 43, 71 , 85 , 99 ,113 and month 5), patient is asked to comply to the various exams and assessment imposed by the algorithm and that should lead to a diagnosis
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
53
Scheduled exams and diagnosis circuit as imposed by the algorithm
Médecine Interne A
Limoges, France
RECRUITINGNumber of patients having correctly follow the diagnosis algorithm
This outcome measure how many patients have correctly followed the diagnosis algorithm
Time frame: 5 months
Rate of diagnosis
Evaluate the rate of diagnosis using our diagnosis algorithm
Time frame: 5 months
Assess the time to diagnosis
Assess the time to diagnosis
Time frame: 5 months
Description of diagnosis
To compare the diagnosis found in our study to the published cohort.
Time frame: 5 months
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