The goal of this observational study is to validate a non-invasive, urine-based diagnostic technology for the detection and differentiation of various gastrointestinal (GI) diseases. This research study intends to enroll participants across a range of demographics and GI disease states including colorectal cancer, small intestinal bacterial overgrowth (SIBO), Crohn\'s disease, and Celiac disease, collect urine samples and clinical data, and use artificial intelligence and machine learning to build disease-specific models which can identify and differentiate a participants' specific GI disease. The main questions it aims to answer are: 1. Does the platform identify a disease signal within each disease cohort, compared to normal controls? 2. How well does the test perform (e.g. sensitivity and specificity/false-positive rate)?
Study Type
OBSERVATIONAL
Enrollment
1,250
Unio Health Partners (Gastroenterology)
Encinitas, California, United States
RECRUITINGDigestive Health Associates
Santa Monica, California, United States
RECRUITINGWestside Gastro Care
Santa Monica, California, United States
RECRUITINGBass Medical Group (Gastroenterology)
Walnut Creek, California, United States
RECRUITINGDisease signal detection
Disease signal detection quantification within each disease cohort, compared to normal controls.
Time frame: From date of enrollment to the end of sample analysis, up to 100 weeks
Test performance measures
Sensitivity and specificity/false-positive rate
Time frame: From date of enrollment to the end of sample analysis, up to 100 weeks
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.