CRS
Conditions
Keywords
chronic rhinosinusitis, nasal polyposis
Brief summary
Professor Hossam Haick from the Technion, developed an electronic nose for diagnosis of diseases via breath samples. Biomarkers from nose and sinuses and upper respiratory tract can be detected by electronic nose. Identification of biomarkers from nose and sinuses and upper respiratory tract can differentiate between the subtypes of CRS (Chronic rhinosinusitis) and may serve as markers for disease (vs controls), of disease activity (predicting aggressive disease course, predicting Malignant vs Benign nasal polyps, as inverted papillpma or carcinoma; predicting response to therapy (Steroid , Antibiotics, Nasal wash, Surgery).
Detailed description
Professor Hossam Haick from the Technion, developed an electronic nose for diagnosis of diseases via breath samples. Biomarkers from nose and sinuses and upper respiratory tract can be detected by electronic nose. Identification of biomarkers from nose and sinuses and upper respiratory tract can differentiate between the subtypes of CRS (Chronic rhinosinusitis) and may serve as markers for disease (vs controls), of disease activity (predicting aggressive disease course, predicting Malignant vs Benign nasal polyps, as inverted papillpma or carcinoma; predicting response to therapy (Steroid , Antibiotics, Nasal wash, Surgery). The aim of this study is to evaluate various CRS diseases with the Electronic Nose trying to better differentiate CRSwPolyps , CRS without Polyps, PCD, AFS, Vasculitis (as Wegener Granulomatosis) and Allergic Rhinitis with CRS. For that reason samples were taken from patients from different groups of CRS patients: 1. CRSwPolyps with no Eosonophilia , 2. CRSwPolyps with Eosonopholia, 3. CRS without Polyps, 4. PCD, 5. AFS, 6. allergic rhinitis and 7. Control subjects.
Interventions
None listed
Sponsors
The Technion
Hillel Yaffe Medical Center
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
1. CRS patients that presented in the Rhinologic clinic at the Hillel Yaffe Medical Center. CRS patients that never had FESS - endoscopic sinus surgery. 2. Willing and able to give inform consent Control subjects: 1. Age and gender match control individuals that do not have CRS or any other condition that is defined as nasal disease. These individuals will be recruited as Healthy Population Reference group. 2. Willing and able to give informed consent
Exclusion criteria
1. Patients age 18 or less, pregnant women 2. Presence of HIV, hepatitis or any other potentially severe and infectious disease. Patient that had sinus surgery.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| discrimination between healthy and CRS subtypes based on SNOT 22 questionnaire results | change in score from recruitment and every six month until 3 years after recruitment. | SNOT 22 score (score 0-110) |
| Successful discrimination between healthy and CRS subtypes based on sensor response (electrical resistance measurements) | Change of electrical resistance from recruitment and every six month until 3 years after recruitment. | Electrical resistance-Disease diagnosis based on breath analysis data classification using an artificial olfactory system (AKA, Electronic nose) |
Outcome results
None listed