Clinical trial NCT06504134: Gastroesophageal Reflux Disease Diagnostic Trial
Official title: Gastroesophageal Reflux Disease Diagnostic Trial
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Gastroesophageal Reflux Disease
Lead sponsor: Changhai Hospital
Sponsor class: OTHER
Collaborators: name: West China Hospital
name: Ruijin Hospital
name: Tongji Hospital
name: Wuhan Union Hospital, China
name: Shanghai Tongji Hospital, Tongji University School of Medicine
name: The Second Affiliated Hospital of Baotou Medical College
First posted: 2024-07-16
Enrollment: 1000
Sex: ALL
Minimum age (years): 18
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Population who underwent testing with the novel esophageal cell collection device due to related symptoms from June 2024 to December 2027

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.


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.

Primary outcomes:
measure: Diagnostic accuracy
timeFrame: 60 minutes
Secondary outcomes:
Other outcomes:
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Study officials:
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