Clinical trial NCT06474923: Multimodal Data-assisted Primary Screening for Allergic Rhinitis Based on Voice Recognition and Face Recognition
Official title: Multimodal Data-assisted Primary Screening for Allergic Rhinitis Based on Voice Recognition and Face
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Body Image
Speech Sound Disorder
Lead sponsor: Huazhong University of Science and Technology
Sponsor class: OTHER
First posted: 2024-06-26
Enrollment: 1500
Sex: ALL
Minimum age (years): 8
Maximum age (years): 80
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Initial clinical diagnosis of chronic rhinitis, able to perform a basic examination, cooperate with face photography and voice capture

Brief summary: Collect facial images and voice and audio of patients with rhinitis in the department of otolaryngology, and collect the examination results of patients with rhinitis who have received electronic fiber nasopharyngoscopy. Skin prick test to a standard panel of aeroallergens or by using the ImmunoCAP Phadiatop test for detecting immunoglobulin E antibodies against various common inhalant allergenswere detected, and a prediction model for the type of rhinitis was finally established.

Detailed description: The incidence of allergic rhinitis is high and the progression of the disease is serious, but public awareness of the disease is limited. Mistaking allergic rhinitis for the common cold or other respiratory illnesses and purchasing non-specific medications for its treatment not only delays proper diagnosis and treatment, but may also lead to further aggravation of the disease and complications. Such omission, misdiagnosis and mistreatment of allergic rhinitis not only affects the management and control of the disease, but may also result in unnecessary wastage of healthcare resources and increased treatment costs.

In this study, the investigators propose to capture face photographs and audio files of rhinitis patients coming to the otolaryngology clinic using a work cell phone to determine whether the patients are allergic or non-allergic rhinitis by using an allergy detection test. The face photos, audio files and basic clinical information were multimodally fused to construct a prediction model, and the effectiveness of the model was evaluated.

Ultimately, it is expected that the predictive model can simply identify and screen for allergic rhinitis, improve public awareness and understanding of allergic rhinitis, and take proper treatment measures.

Eligibility criteria: Inclusion Criteria:

1. Subjects understood the purpose and procedure of the trial and signed an informed consent form, and voluntarily participated in this study;
2. Subjects were initially clinically diagnosed with chronic rhinitis;
3. Subjects were aged 8-80 years old, limited to Chinese nationality, and were able to perform basic examinations and cooperate with face photography and voice collection.

Exclusion Criteria:

1. Those who received systemic immunotherapy, used systemic or local glucocorticoids as well as leukotriene receptor antagonists within one month;
2. Those who suffer from immune system diseases, autoimmune diseases, allergic diseases or allergies and have a history of food allergy;
3. Other serious systemic diseases, such as active tuberculosis, rheumatic heart disease, congenital heart disease, arthritis, nephritis, hypertension, psychosis, dermatitis, epilepsy and so on;
4. Women during lactation and pregnancy;
5. History of upper respiratory tract infection or more serious infectious diseases within three months;
6. Those who are currently participating in another clinical study or have participated in another clinical study within 90 days;
7. Other patients who, in the judgment of the clinician, are not suitable for inclusion in the study.

Primary outcomes:
measure: Allergen Test Results
timeFrame: 30 minutes
Secondary outcomes:
Other outcomes:
Locations:
city: Wuhan
country: China
facility: Professor of Otolaryngology-Head & Neck Surgery Vice Director Department of ENT Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Affiliation: Huazhong University of Science and Technology
state: Hubei
Study officials:
affiliation: Tongji Hospital
name: Zheng Liu, Doctor
role: STUDY_DIRECTOR
References: