Allograft Arteriopathy, Heart Transplantation
Conditions
Brief summary
This project aims: i) to identify Cardiac Allograft Vasculopathy (CAV) trajectories after heat transplantation using latent class mixed modeling, ii) to characterize the global and specific determinants of different trajectories and iii) to provide an easily accessible tool to project individual probability of CAV trajectory belonging.
Detailed description
Background: Cardiac Allograft Vasculopathy (CAV) is the third cause of late mortality and the leading cause of late allograft dysfunction. The field of heart transplantation currently lacks longitudinal description of CAV profiles. Identifying relevant CAV trajectories, or evolution profiles, and their respective determinants is an unmet clinical need. CAV trajectories requires an additional level of understanding and characterization over the current paradigm. Understanding the mechanisms and clinical factors involved in the development of CAV will be useful to provide a more nuanced picture of disease progression, which may ultimately contribute to risk stratification and ultimately guiding the care of HTx patients. Main Outcome(s) and Measure(s): * Identification of CAV trajectories after transplantation using an unsupervised latent class mixed modeling. CAV angiograms were recorded per center protocol for all patients after transplantation. CAV was graded according to the current ISHLT classification as CAV 0 (not significant), 1 (mild), 2 (moderate) and 3 (severe). * Determination of clinical, functional, structural, immunological factors associated with the trajectories. In the derivation cohort, the associations between CAV trajectories and clinical, histological, functional, and immunological parameters at the time of transplantation, during the first year and at one-year post-transplant were assessed using multinomial logistic regression.
Interventions
OTHERLatent class mixed modeling
To identify CAV trajectories after heart transplantation using a contemporary unsupervised trajectory-based approach known as latent class mixed modeling
Sponsors
Groupe Hospitalier Pitie-Salpetriere
European Georges Pompidou Hospital
Universitaire Ziekenhuizen KU Leuven
Cedars-Sinai Medical Center
Paris Translational Research Center for Organ Transplantation
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Heart recipient with at least two coronary angiograms after heart transplantation, * Heart recipient over 18 years of age.
Exclusion criteria
* Patient with \< 2 coronary angiograms during follow-up
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Identification of trajectories of Cardiac Allograft Vasculopathy (CAV) | 10 years post-transplant | Identification of different evolutive profiles of CAV using latent classes mixed models. Each coronary angiogram was graded from 0 (no CAV) to 3 (severe CAV) according to ISHLT classification. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Identification of the specific determinants of CAV trajectories | From transplantation to 1-year post-transplant | Identification of immune and non-immune determinants using multivariable multinomial logistic regression. |
| Early prediction of CAV trajectories | 10 years post-transplant | Probability of belonging to each trajectory according to the baseline angiogram and independent risk factors for CAV |
| Patients and allograft survival probability according the CAV trajectory | 10 years post-transplant | Comparison of prognosis according the CAV trajectory |
Countries
Belgium, France, United States
Outcome results
None listed