Cargando…
Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis
OBJECTIVES: Congenitally corrected transposition of the great arteries (ccTGA) is a rare and complex congenital heart disease with the characteristics of double discordance. Enormous co-existed anomalies are the culprit of prognosis evaluation and clinical decision. We aim at delineating a novel ccT...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8814104/ https://www.ncbi.nlm.nih.gov/pubmed/35127856 http://dx.doi.org/10.3389/fcvm.2021.781041 |
_version_ | 1784644999377321984 |
---|---|
author | He, Qiyu Shen, Huayan Shao, Xinyang Chen, Wen Wu, Yafeng Liu, Rui Li, Shoujun Zhou, Zhou |
author_facet | He, Qiyu Shen, Huayan Shao, Xinyang Chen, Wen Wu, Yafeng Liu, Rui Li, Shoujun Zhou, Zhou |
author_sort | He, Qiyu |
collection | PubMed |
description | OBJECTIVES: Congenitally corrected transposition of the great arteries (ccTGA) is a rare and complex congenital heart disease with the characteristics of double discordance. Enormous co-existed anomalies are the culprit of prognosis evaluation and clinical decision. We aim at delineating a novel ccTGA clustering modality under human phenotype ontology (HPO) instruction and elucidating the relationship between phenotypes and prognosis in patients with ccTGA. METHODS: A retrospective review of 270 patients diagnosed with ccTGA in Fuwai hospital from 2009 to 2020 and cross-sectional follow-up were performed. HPO-instructed clustering method was administered in ccTGA risk stratification. Kaplan-Meier survival, Landmark analysis, and cox regression analysis were used to investigate the difference of outcomes among clusters. RESULTS: The median follow-up time was 4.29 (2.07–7.37) years. A total of three distinct phenotypic clusters were obtained after HPO-instructed clustering with 21 in cluster 1, 136 in cluster 2, and 113 in cluster 3. Landmark analysis revealed significantly worse mid-term outcomes in all-cause mortality (p = 0.021) and composite endpoints (p = 0.004) of cluster 3 in comparison with cluster 1 and cluster 2. Multivariate analysis indicated that pulmonary arterial hypertension (PAH), atrioventricular septal defect (AVSD), and arrhythmia were risk factors for composite endpoints. Moreover, the surgical treatment was significantly different among the three groups (p < 0.001) and surgical strategies had different effects on the prognosis of the different phenotypic clusters. CONCLUSIONS: Human phenotype ontology-instructed clustering can be a potentially powerful tool for phenotypic risk stratification in patients with complex congenital heart diseases, which may improve prognosis prediction and clinical decision. |
format | Online Article Text |
id | pubmed-8814104 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88141042022-02-05 Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis He, Qiyu Shen, Huayan Shao, Xinyang Chen, Wen Wu, Yafeng Liu, Rui Li, Shoujun Zhou, Zhou Front Cardiovasc Med Cardiovascular Medicine OBJECTIVES: Congenitally corrected transposition of the great arteries (ccTGA) is a rare and complex congenital heart disease with the characteristics of double discordance. Enormous co-existed anomalies are the culprit of prognosis evaluation and clinical decision. We aim at delineating a novel ccTGA clustering modality under human phenotype ontology (HPO) instruction and elucidating the relationship between phenotypes and prognosis in patients with ccTGA. METHODS: A retrospective review of 270 patients diagnosed with ccTGA in Fuwai hospital from 2009 to 2020 and cross-sectional follow-up were performed. HPO-instructed clustering method was administered in ccTGA risk stratification. Kaplan-Meier survival, Landmark analysis, and cox regression analysis were used to investigate the difference of outcomes among clusters. RESULTS: The median follow-up time was 4.29 (2.07–7.37) years. A total of three distinct phenotypic clusters were obtained after HPO-instructed clustering with 21 in cluster 1, 136 in cluster 2, and 113 in cluster 3. Landmark analysis revealed significantly worse mid-term outcomes in all-cause mortality (p = 0.021) and composite endpoints (p = 0.004) of cluster 3 in comparison with cluster 1 and cluster 2. Multivariate analysis indicated that pulmonary arterial hypertension (PAH), atrioventricular septal defect (AVSD), and arrhythmia were risk factors for composite endpoints. Moreover, the surgical treatment was significantly different among the three groups (p < 0.001) and surgical strategies had different effects on the prognosis of the different phenotypic clusters. CONCLUSIONS: Human phenotype ontology-instructed clustering can be a potentially powerful tool for phenotypic risk stratification in patients with complex congenital heart diseases, which may improve prognosis prediction and clinical decision. Frontiers Media S.A. 2022-01-21 /pmc/articles/PMC8814104/ /pubmed/35127856 http://dx.doi.org/10.3389/fcvm.2021.781041 Text en Copyright © 2022 He, Shen, Shao, Chen, Wu, Liu, Li and Zhou. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine He, Qiyu Shen, Huayan Shao, Xinyang Chen, Wen Wu, Yafeng Liu, Rui Li, Shoujun Zhou, Zhou Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis |
title | Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis |
title_full | Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis |
title_fullStr | Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis |
title_full_unstemmed | Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis |
title_short | Cardiovascular Phenotypes Profiling for L-Transposition of the Great Arteries and Prognosis Analysis |
title_sort | cardiovascular phenotypes profiling for l-transposition of the great arteries and prognosis analysis |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8814104/ https://www.ncbi.nlm.nih.gov/pubmed/35127856 http://dx.doi.org/10.3389/fcvm.2021.781041 |
work_keys_str_mv | AT heqiyu cardiovascularphenotypesprofilingforltranspositionofthegreatarteriesandprognosisanalysis AT shenhuayan cardiovascularphenotypesprofilingforltranspositionofthegreatarteriesandprognosisanalysis AT shaoxinyang cardiovascularphenotypesprofilingforltranspositionofthegreatarteriesandprognosisanalysis AT chenwen cardiovascularphenotypesprofilingforltranspositionofthegreatarteriesandprognosisanalysis AT wuyafeng cardiovascularphenotypesprofilingforltranspositionofthegreatarteriesandprognosisanalysis AT liurui cardiovascularphenotypesprofilingforltranspositionofthegreatarteriesandprognosisanalysis AT lishoujun cardiovascularphenotypesprofilingforltranspositionofthegreatarteriesandprognosisanalysis AT zhouzhou cardiovascularphenotypesprofilingforltranspositionofthegreatarteriesandprognosisanalysis |