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Efficacy Classification Prediction of the Effects of Acupuncture on Abdominal Pain in Patients With Crohn's Disease

Crohn Disease Clinical Trial

Official title:
Predicting the Clinical Efficacy of Acupuncture for Abdominal Pain in Patients With Crohn's Disease Based on Gut Microbiology and Machine Learning

Clinical Trial Summary

Machine learning algorithms are applied to discover gut flora markers that predict the clinical efficacy of acupuncture, so as to screen the appropriate population for acupuncture and optimise the allocation of healthcare resources.

Clinical Trial Description

Crohn's disease is an intestinal inflammatory disease,causing abdominal pain, diarrhea and other symptoms.The intestinal flora disorder is closely related to the occurrence and development of Crohn's disease. Acupuncture can induce remission of Crohn's disease during mild to moderate active period, improve clinical symptoms such as abdominal pain. Acupuncture can affect the gut microbiota. The aim of this study was to apply gut microbiological data and clinical data from subjects at baseline to predict the clinical efficacy of acupuncture by machine learning algorithms, and to classify patients as effective/ineffective in order to screen for suitable subjects for acupuncture. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT06352164
Study type Interventional
Source Shanghai Institute of Acupuncture, Moxibustion and Meridian
Contact
Status Completed
Phase N/A
Start date March 1, 2015
Completion date March 31, 2024
View Details
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