Observational Study of Urine Metabolites in the Diagnosis of Disease

What this Trial Is About

Researchers are conducting an observational study to validate a non-invasive urine-based diagnostic technology that can detect and differentiate various gastrointestinal diseases. These diseases include colorectal cancer, small intestinal bacterial overgrowth syndrome (SIBO), Crohn's disease, and Celiac disease. The study aims to use artificial intelligence and machine learning to develop disease-specific models for accurate identification and differentiation of these conditions. Participants from diverse demographics and with different gastrointestinal diseases will provide urine samples and clinical data. The study will analyze these samples using the new diagnostic platform to determine if it can detect a disease signal within each disease group compared to healthy controls, and to assess the test's performance, including sensitivity and false-positive rates. During the study, participants will provide a one-time urine sample and comply with study procedures. Researchers will monitor outcomes from enrollment up to 100 weeks, focusing on disease signal detection and test performance measures. The study includes consent and authorization for the release of relevant health information under HIPAA and ensures safety by excluding pregnant individuals and those with medical conditions that may interfere with participation.

Urine Metabolites in the Diagnosis of Disease