{"doi":"10.1111/ctr.15101","title":"Long‐Term outcomes in adult patients with congenital heart disease considered for transplantation: A single center study","abstract":"BACKGROUND: Adult congenital heart disease (ACHD) patients pose unique challenges in identifying the time for transplantation and factors influencing outcomes. OBJECTIVE: To identify hemodynamic, functional, and laboratory parameters that correlate with 1- and 10-year outcomes in ACHD patients considered for transplantation. METHODS: A retrospective chart review of long-term outcomes in adult patients with congenital heart disease (CHD) evaluated for heart or heart + additional organ transplant between 2004 and 2014 at our center was performed. A machine learning decision tree model was used to evaluate multiple clinical parameters correlating with 1- and 10-year survival. RESULTS: We identified 58 patients meeting criteria. D-transposition of the great arteries (D-TGA) with atrial switch operation (20.7%), tetralogy of Fallot/pulmonary atresia (15.5%), and tricuspid atresia (13.8%) were the most common diagnosis for transplant. Single ventricle patients were most likely to be listed for transplantation (39.8% of evaluated patients). Among a comprehensive list of clinical factors, invasive hemodynamic parameters (pulmonary capillary wedge pressure (PCWP), systemic vascular pressure (SVP), and end diastolic pressures (EDP) most correlated with 1- and 10-year outcomes. Transplanted patients with SVP < 14 and non- transplanted patients with PCWP < 15 had 100% survival 1-year post-transplantation. CONCLUSION: For the first time, our study identifies that hemodynamic parameters most strongly correlate with 1- and 10-year outcomes in ACHD patients considered for transplantation, using a data-driven machine learning model.","journal":"Clinical Transplantation","year":2023,"id":373294,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7596,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":617536,"name":"Charith Ratnayake","orcid":"0000-0002-7752-5564","position":1,"is_corresponding":false},{"id":1134627,"name":"Andrea Elliot","orcid":null,"position":2,"is_corresponding":false},{"id":361269,"name":"Tarek Alsaied","orcid":"0000-0002-3777-4822","position":3,"is_corresponding":false},{"id":361552,"name":"Anthony Fabio","orcid":"0000-0002-6808-4939","position":4,"is_corresponding":false},{"id":567443,"name":"Stephen C. Cook","orcid":"0000-0002-3938-6751","position":5,"is_corresponding":false},{"id":568073,"name":"Morgan Hindes","orcid":null,"position":6,"is_corresponding":false},{"id":409478,"name":"Arvind Hoskoppal","orcid":"0000-0002-8497-2477","position":7,"is_corresponding":false},{"id":334112,"name":"Anita Saraf","orcid":"0000-0001-7096-7418","position":8,"is_corresponding":false},{"id":516120,"name":"Gavin Hickey","orcid":"0000-0002-0547-4921","position":0,"is_corresponding":true}],"reference_count":21,"raw_metadata":null,"created_at":"2026-07-19T01:16:02.217046Z","pmid":"37589828","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}