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

N/ANot Yet RecruitingNCT06774768

IRCCS Azienda Ospedaliero-Universitaria di Bologna1,000 enrolled

Overview

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.

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.

Study Type

OBSERVATIONAL

Enrollment

1,000

Conditions

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

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Retrospective cohort Inclusion criteria Receiving a heart or liver transplantation at IRCCS AOUBO between January 2008 and December 2020. 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 Exclusion criteria Unavailability of medical records in the standard data repositories of IRCCS AOUBO Prospective cohort Inclusion criteria Older thant 18 years old Receiving a heart or liver transplantation at least 6 months before study entry and being in active follow up at IRCCS AOUBO Obtaining informed consent Exclusion criteria None

Outcomes

Primary Outcomes

Infection

Infection, defined as systemic or organ-specific syndrome characterized by evidence of inflammatory response, abnormal organ function, and need for intravenous antimicrobial treatment, with or without microbiological isolate.

Time frame: 4 years

Major Cardiovascular Event (MACE)

Major Cardiovascular Event (MACE) defined as, fatal or non-fatal myocardial infarction, ischemic or hemorrhagic stroke, admission for heart failure, new onset arrhythmia, new onset symptoms for peripheral artery diseases

Time frame: 4 years

New onset malignancy

New onset malignancy, defined as hematopoietic or solid malignant neoplasm, developing after transplantation

Time frame: 4 years

Chronic graft dysfunction

Chronic graft dysfunction; in HTX recipients defined as onset of one or more of the following: CAV grade 2 or greater as diagnosed by standard of care coronary angiography; diffuse fibrosis with signs of diastolic or systolic left ventricle dysfunction. In LTX we define chronic graft dysfunction as progressive fibrosis, cholestasis and reduced protein synthesis, portal hypertension.

Time frame: 4 years

Secondary Outcomes

ML-Scores as Surrogate Endpoints

The ML-scores developed to predict the primary outcomes will be used as secondary study outcomes for the prospective phase of the study, and will be tested as surrogate endpoints for clinical outcomes. In this approach, we will analyze the association between such defined surrogate endpoints and biomarkers, QoL and cognitive scores, and frailty measurements.

Time frame: 4 years

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

Overview

Conditions

Eligibility

Locations (2)

Outcomes

Primary Outcomes

Secondary Outcomes

Central Contacts