Gastroesophageal Reflux Disease
Conditions
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.
Interventions
DIAGNOSTIC_TESTthe 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
Sponsors
West China Hospital
Ruijin Hospital
Tongji Hospital
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Shanghai Tongji Hospital, Tongji University School of Medicine
The Second Affiliated Hospital of Baotou Medical College
Changhai Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic accuracy | 60 minutes | sensitivity and specificity |
Contacts
Primary ContactLuowei Wang, MD
Backup ContactLei Xin, MD
Outcome results
None listed