Gastroesophageal Reflux Disease Diagnostic Trial

NCT ID: NCT06504134

Last Updated: 2024-07-16

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 1000 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-07-30
• Study Completion Date: 2027-12-31

Brief Summary

Gastroesophageal reflux disease (GERD) is a very common condition in clinical practice. In China, GERD affects nearly 150 million patients, whose quality of life are seriously impacted. Currently, the diagnosis of GERD primarily depends on the results of 24h reflux monitoring. However, such examination is under a quite low acceptability. As a result, a large number of patients were not diagnosed timely and accurately, and serious social problems are induced, such as drug abuse of proton pump inhibitor. Our team has previously developed a novel device for esophageal cell enrichment and established an internationally pioneering method of cytological screening for esophageal cancer based on cutting-edge deep learning technology. This project aims to develop multiple deep learning algorithms and establish an innovative method for diagnosis of GRED, using the novel esophageal cell enrichment technology. The research includes: 1) constructing deep learning algorithms for automatic esophageal inflammatory cells recognition and classification; 2) mining and extracting the key features of esophageal squamous cells and inflammatory cells under physician-AI interaction; 3) establishing a prediction model for GERD by integrating digital features of squamous cells and inflammatory cells and building a cloud-based automatic diagnosis system; 4) investigating the immuno-infiltration atlas of GERD and its diagnostic value based on the enriched inflammatory cells. The ultimate goal is to solve current clinical problems and realize rapid, convenient, and accurate diagnosis of GERD.

Conditions

Gastroesophageal Reflux Disease

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Interventions

the Novel Esophageal Cell Collection Device

Using the novel cell collection device and the deep learning method to collect and classify esophogeal cell to identify if the participants are GERD patients

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

1. ≥18 years and ≤85 years, male or female;

2. A visit was made for symptoms such as persistent reflux, heartburn, bloating, early satiety, and belching;

3. Patients volunteered to participate in the clinical trial, signed an informed consent form, and were able to cooperate with clinical follow-up.

Exclusion Criteria

1. History of esophageal surgery;

2. Presence of dysphagia, esophagogastric fundal varices, or esophageal stenosis;

3. Presence of coagulation disorders or taking anticoagulant or antiplatelet drugs;

4. Those with a life expectancy of less than 5 years;

5. Persons with mental anomalies who are incapable of behavioral autonomy;

6. Other conditions that, in the judgment of the physician, preclude participation in the trial.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 85 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

West China Hospital

OTHER

Sponsor Role: collaborator

Ruijin Hospital

OTHER

Sponsor Role: collaborator

Tongji Hospital

OTHER

Sponsor Role: collaborator

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

OTHER

Sponsor Role: collaborator

Shanghai Tongji Hospital, Tongji University School of Medicine

OTHER

Sponsor Role: collaborator

The Second Affiliated Hospital of Baotou Medical College

OTHER

Sponsor Role: collaborator

Changhai Hospital

OTHER

Sponsor Role: lead

Responsible Party

Luowei Wang, MD

Clinical Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Central Contacts

Luowei Wang, MD

Role: CONTACT

wangluoweimd@126.com

13901833088

Lei Xin, MD

Role: CONTACT

aip_xin@163.com

13817318134

Other Identifiers

GERDT

Identifier Type: -

Identifier Source: org_study_id