Introduction: Functional gastrointestinal disorders (FGIDs), which include irritable bowel syndrome (IBS) and functional dyspepsia (FD), are common gastrointestinal (GI) diseases that have a large financial impact on patients' quality of life (QoL). Traditional Korean medicine has a particular diagnostic pattern for treating FGIDs. However, FGIDs have not been thoroughly explored because of their complexity. In this proposed study, we will investigate the acupoint selection pattern for FGID patients with various disease patterns, and further determine the best acupoints for treating FGID patients using a machine-learning algorithm.
Methods: We will collect clinical data from 15 multi-center Korean medical clinics that treat FGID as part of an observational study registry. Patients who meet the criteria will be added to the registry after screening. They will receive a maximum 4-week treatment, and they will respond 3 times to a series of questions. We will investigate how doctors of FGID patients with diverse disease patterns choose the acupoints, and we will use a machine learning technique to identify the best acupoints for treating FGID patients.
Discussion: This will be the first multi-center observational registry study to assess how traditional Korean medical practitioners diagnose and treat patients in the real world. The findings will shed light on how traditional Korean medicine treats FGIDs and demonstrate the rationale for the diagnostic and acupuncture treatment flow.
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