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Clinical Trial Details — Status: Enrolling by invitation

Administrative data

NCT number NCT05501028
Other study ID # 2018P001542
Secondary ID
Status Enrolling by invitation
Phase
First received
Last updated
Start date August 9, 2018
Est. completion date June 1, 2023

Study information

Verified date August 2022
Source Massachusetts General Hospital
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The study has two arms, where the same natural language processing (NLP) and probabilistic graphical modeling technology will be utilized on patients' report of symptoms in both arms. The clinical arm is focused on patients presenting for consultation with a gastroenterologist. The endoscopy arm is focused generally on patients presenting for a diagnostic endoscopy, with the goal of capturing Functional Gastrointestinal Disorder (FGID) patients prior to diagnosis.


Recruitment information / eligibility

Status Enrolling by invitation
Enrollment 700
Est. completion date June 1, 2023
Est. primary completion date June 1, 2023
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - Scheduled for consult in the Motility Clinic in the MGH Gastroenterology Unit or for diagnostic endoscopy in the MGH Gastroenterology Unit - Patient must agree to have their interactions audio-recorded - Informed consent form signed by the subjects Exclusion Criteria: - Non-native English speaker - Patients unable to communicate their own symptoms

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
United States Massachusetts General Hospital Boston Massachusetts

Sponsors (2)

Lead Sponsor Collaborator
Massachusetts General Hospital Massachusetts Institute of Technology

Country where clinical trial is conducted

United States, 

Outcome

Type Measure Description Time frame Safety issue
Primary Latent themes present in patient descriptions of FGIDs symptoms Latent themes present in patient descriptions of FGIDs symptoms as generated by machine learning as well as quantitative comparisons to traditional metrics of patient descriptions including Rome IV criteria and patient descriptions of severity. 08/09/2018-08/09/2023
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