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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...

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Autores principales: He, Qiyu, Shen, Huayan, Shao, Xinyang, Chen, Wen, Wu, Yafeng, Liu, Rui, Li, Shoujun, Zhou, Zhou
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
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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.
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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
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