Use of Machine-learning Algorithms, Biomarkers and Measures of Quality of Life to Personalize Medical Management of Liver and Heart Transplant Recipients

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

1000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-01-30

Study Completion Date

2029-12-31

Brief Summary

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This is an observational, low risk tissue based, non-pharmacological, retrospective-prospective study for adults heart and liver transplant patients, related to IRCCS Azienda Ospedaliero-Universitaria di Bologna (IRCCS AOUBO).

This clinical study is part of the national multicentric project DARE. The project has the wide overarching aim to develop digital solutions for personalized healthcare.

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Detailed Description

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This study is structured in two phases: 1) a retrospective phase that aims to develop ML-based scores that can allow to predict at patient level the risk of infections, cardiovascular diseases, new onset malignancies and chronic graft dysfunction, and describing the trajectory of this risk over time; 2) a prospective phase in which we test the association of biomarkers, QoL and frailty assessments with the ML-scores applied prospectively in heart and liver transplant recipients.

Conditions

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Artificial Intelligence (AI) Hepatocellular Carcinoma (HCC) Heart Transplantation Liver Transplantation Machine Learning Major Cardiovascular Event

Study Design

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Observational Model Type

COHORT

Study Time Perspective

OTHER

Eligibility Criteria

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Inclusion Criteria

Surviving at least 6 months after surgery Receiving at least one outpatient clinical assessment, comprising clinical evaluation, standard laboratory tests, and graft ultrasound Older than 18 years old