Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data
Abstract Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how...
Guardado en:
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/4d9fea8472954db9b2f04ddb9bb12962 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:4d9fea8472954db9b2f04ddb9bb12962 |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:4d9fea8472954db9b2f04ddb9bb129622021-12-02T18:53:18ZDifferential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data10.1038/s41598-021-96616-w2045-2322https://doaj.org/article/4d9fea8472954db9b2f04ddb9bb129622021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96616-whttps://doaj.org/toc/2045-2322Abstract Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how these differing plaque composition profiles impact plaque progression. Patients with coronary atherosclerotic plaque (n = 947; median age, 62 years; 59% male) were enrolled from a prospective multi-national registry of consecutive patients who underwent serial coronary computed tomography angiography (median inter-scan duration, 3.3 years). K-means clustering applied to the percent volume of each plaque component and identified 4 clusters of patients with distinct plaque composition. Cluster 1 (n = 52), which comprised mainly fibro-fatty plaque with a significant necrotic core (median, 55.7% and 16.0% of the total plaque volume, respectively), showed the least total plaque volume (PV) progression (+ 23.3 mm3), with necrotic core and fibro-fatty PV regression (− 5.7 mm3 and − 5.6 mm3, respectively). Cluster 2 (n = 219), which contained largely fibro-fatty (39.2%) and fibrous plaque (46.8%), showed fibro-fatty PV regression (− 2.4 mm3). Cluster 3 (n = 376), which comprised mostly fibrous (62.7%) and calcified plaque (23.6%), showed increasingly prominent calcified PV progression (+ 21.4 mm3). Cluster 4 (n = 300), which comprised mostly calcified plaque (58.7%), demonstrated the greatest total PV increase (+ 50.7mm3), predominantly increasing in calcified PV (+ 35.9 mm3). Multivariable analysis showed higher risk for plaque progression in Clusters 3 and 4, and higher risk for adverse cardiac events in Clusters 2, 3, and 4 compared to that in Cluster 1. Unsupervised clustering algorithms may uniquely characterize patient phenotypes with varied atherosclerotic plaque profiles, yielding distinct patterns of progressive disease and outcome.Yeonyee E. YoonLohendran BaskaranBenjamin C. LeeMohit Kumar PandeyBenjamin GoebelSang-Eun LeeJi Min SungDaniele AndreiniMouaz H. Al-MallahMatthew J. BudoffFilippo CademartiriKavitha ChinnaiyanJung Hyun ChoiEun Ju ChunEdoardo ConteIlan GottliebMartin HadamitzkyYong Jin KimByoung Kwon LeeJonathon A. LeipsicErica MaffeiHugo MarquesPedro de Araújo GonçalvesGianluca PontoneSanghoon ShinJagat NarulaJeroen J. BaxFay Yu-Huei LinLeslee ShawHyuk-Jae ChangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Yeonyee E. Yoon Lohendran Baskaran Benjamin C. Lee Mohit Kumar Pandey Benjamin Goebel Sang-Eun Lee Ji Min Sung Daniele Andreini Mouaz H. Al-Mallah Matthew J. Budoff Filippo Cademartiri Kavitha Chinnaiyan Jung Hyun Choi Eun Ju Chun Edoardo Conte Ilan Gottlieb Martin Hadamitzky Yong Jin Kim Byoung Kwon Lee Jonathon A. Leipsic Erica Maffei Hugo Marques Pedro de Araújo Gonçalves Gianluca Pontone Sanghoon Shin Jagat Narula Jeroen J. Bax Fay Yu-Huei Lin Leslee Shaw Hyuk-Jae Chang Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data |
| description |
Abstract Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how these differing plaque composition profiles impact plaque progression. Patients with coronary atherosclerotic plaque (n = 947; median age, 62 years; 59% male) were enrolled from a prospective multi-national registry of consecutive patients who underwent serial coronary computed tomography angiography (median inter-scan duration, 3.3 years). K-means clustering applied to the percent volume of each plaque component and identified 4 clusters of patients with distinct plaque composition. Cluster 1 (n = 52), which comprised mainly fibro-fatty plaque with a significant necrotic core (median, 55.7% and 16.0% of the total plaque volume, respectively), showed the least total plaque volume (PV) progression (+ 23.3 mm3), with necrotic core and fibro-fatty PV regression (− 5.7 mm3 and − 5.6 mm3, respectively). Cluster 2 (n = 219), which contained largely fibro-fatty (39.2%) and fibrous plaque (46.8%), showed fibro-fatty PV regression (− 2.4 mm3). Cluster 3 (n = 376), which comprised mostly fibrous (62.7%) and calcified plaque (23.6%), showed increasingly prominent calcified PV progression (+ 21.4 mm3). Cluster 4 (n = 300), which comprised mostly calcified plaque (58.7%), demonstrated the greatest total PV increase (+ 50.7mm3), predominantly increasing in calcified PV (+ 35.9 mm3). Multivariable analysis showed higher risk for plaque progression in Clusters 3 and 4, and higher risk for adverse cardiac events in Clusters 2, 3, and 4 compared to that in Cluster 1. Unsupervised clustering algorithms may uniquely characterize patient phenotypes with varied atherosclerotic plaque profiles, yielding distinct patterns of progressive disease and outcome. |
| format |
article |
| author |
Yeonyee E. Yoon Lohendran Baskaran Benjamin C. Lee Mohit Kumar Pandey Benjamin Goebel Sang-Eun Lee Ji Min Sung Daniele Andreini Mouaz H. Al-Mallah Matthew J. Budoff Filippo Cademartiri Kavitha Chinnaiyan Jung Hyun Choi Eun Ju Chun Edoardo Conte Ilan Gottlieb Martin Hadamitzky Yong Jin Kim Byoung Kwon Lee Jonathon A. Leipsic Erica Maffei Hugo Marques Pedro de Araújo Gonçalves Gianluca Pontone Sanghoon Shin Jagat Narula Jeroen J. Bax Fay Yu-Huei Lin Leslee Shaw Hyuk-Jae Chang |
| author_facet |
Yeonyee E. Yoon Lohendran Baskaran Benjamin C. Lee Mohit Kumar Pandey Benjamin Goebel Sang-Eun Lee Ji Min Sung Daniele Andreini Mouaz H. Al-Mallah Matthew J. Budoff Filippo Cademartiri Kavitha Chinnaiyan Jung Hyun Choi Eun Ju Chun Edoardo Conte Ilan Gottlieb Martin Hadamitzky Yong Jin Kim Byoung Kwon Lee Jonathon A. Leipsic Erica Maffei Hugo Marques Pedro de Araújo Gonçalves Gianluca Pontone Sanghoon Shin Jagat Narula Jeroen J. Bax Fay Yu-Huei Lin Leslee Shaw Hyuk-Jae Chang |
| author_sort |
Yeonyee E. Yoon |
| title |
Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data |
| title_short |
Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data |
| title_full |
Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data |
| title_fullStr |
Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data |
| title_full_unstemmed |
Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data |
| title_sort |
differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of paradigm registry data |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/4d9fea8472954db9b2f04ddb9bb12962 |
| work_keys_str_mv |
AT yeonyeeeyoon differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT lohendranbaskaran differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT benjaminclee differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT mohitkumarpandey differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT benjamingoebel differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT sangeunlee differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT jiminsung differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT danieleandreini differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT mouazhalmallah differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT matthewjbudoff differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT filippocademartiri differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT kavithachinnaiyan differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT junghyunchoi differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT eunjuchun differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT edoardoconte differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT ilangottlieb differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT martinhadamitzky differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT yongjinkim differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT byoungkwonlee differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT jonathonaleipsic differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT ericamaffei differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT hugomarques differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT pedrodearaujogoncalves differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT gianlucapontone differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT sanghoonshin differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT jagatnarula differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT jeroenjbax differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT fayyuhueilin differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT lesleeshaw differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata AT hyukjaechang differentialprogressionofcoronaryatherosclerosisaccordingtoplaquecompositionaclusteranalysisofparadigmregistrydata |
| _version_ |
1718377325147455488 |