Condition: Acute Graft Rejection · Sponsor: University Health Network, Toronto
The goal of this observational study is to to identify different causes of liver diseases or damage in liver transplant patients and develop a machine learning algorithm as a non-invasive tool leveraging gene expression and patient clinical information to classify transplant liver diseases We will collect blood samples of the participants who had undergone or will undergo the liver biopsy as part of standard of care, and use this blood in TruGarf. TruGraf is a non-invasive test that measures differentially expressed genes in the blood of transplant recipients to rule out liver damage. Researcher will collect the biopsy result from the medical record and this will be compared with the TruGarf results.
This description comes directly from the study's public registry record.
Sameera Rizvi · 4163404800 · sameera.rizvi@uhn.ca
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| Toronto General Hospital -UHN | Toronto, Ontario, Canada | Recruiting |
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Source record: clinicaltrials.gov/study/NCT06557564