Unsupervised Cluster Analysis of Patients With Aortic Stenosis Reveals Distinct Population With Different Phenotypes and Outcomes. (16th May 2020)
- Record Type:
- Journal Article
- Title:
- Unsupervised Cluster Analysis of Patients With Aortic Stenosis Reveals Distinct Population With Different Phenotypes and Outcomes. (16th May 2020)
- Main Title:
- Unsupervised Cluster Analysis of Patients With Aortic Stenosis Reveals Distinct Population With Different Phenotypes and Outcomes
- Authors:
- Kwak, Soongu
Lee, Yunhwan
Ko, Taehoon
Yang, Seokhun
Hwang, In-Chang
Park, Jun-Bean
Yoon, Yeonyee E.
Kim, Hack-Lyoung
Kim, Hyung-Kwan
Kim, Yong-Jin
Cho, Goo-Yeong
Sohn, Dae-Won
Won, Sungho
Lee, Seung-Pyo - Abstract:
- Abstract : Background: There is a lack of studies investigating the heterogeneity of patients with aortic stenosis (AS). We explored whether cluster analysis identifies distinct subgroups with different prognostic significances in AS. Methods: Newly diagnosed patients with moderate or severe AS were prospectively enrolled between 2013 and 2016 (n=398, mean 71 years, 55% male). Among demographics, laboratory, and echocardiography parameters (n=32), 11 variables were selected through dimension reduction and used for unsupervised clustering. Phenotypes and causes of mortality were compared between the clusters. Results: Three clusters with markedly different features were identified. Cluster 1 (n=60) was predominantly associated with cardiac dysfunction, cluster 2 (n=86) consisted of elderly with comorbidities, especially end-stage renal disease, whereas cluster 3 (n=252) demonstrated neither cardiac dysfunction nor comorbidities. Although AS severity did not differ, there was a significant difference in adverse outcomes between the clusters during a median 2.4 years follow-up (mortality rate, 13.3% versus 19.8% versus 6.0% for cluster 1, 2, and 3, P <0.001). Particularly, compared with cluster 3, cluster 1 was associated with only cardiac mortality (adjusted hazard ratio, 7.37 [95% CI, 2.00–27.13]; P =0.003), whereas cluster 2 was associated with higher noncardiac mortality (adjusted hazard ratio, 3.35 [95% CI, 1.26–8.90]; P =0.015). Phenotypes and association of clusters withAbstract : Background: There is a lack of studies investigating the heterogeneity of patients with aortic stenosis (AS). We explored whether cluster analysis identifies distinct subgroups with different prognostic significances in AS. Methods: Newly diagnosed patients with moderate or severe AS were prospectively enrolled between 2013 and 2016 (n=398, mean 71 years, 55% male). Among demographics, laboratory, and echocardiography parameters (n=32), 11 variables were selected through dimension reduction and used for unsupervised clustering. Phenotypes and causes of mortality were compared between the clusters. Results: Three clusters with markedly different features were identified. Cluster 1 (n=60) was predominantly associated with cardiac dysfunction, cluster 2 (n=86) consisted of elderly with comorbidities, especially end-stage renal disease, whereas cluster 3 (n=252) demonstrated neither cardiac dysfunction nor comorbidities. Although AS severity did not differ, there was a significant difference in adverse outcomes between the clusters during a median 2.4 years follow-up (mortality rate, 13.3% versus 19.8% versus 6.0% for cluster 1, 2, and 3, P <0.001). Particularly, compared with cluster 3, cluster 1 was associated with only cardiac mortality (adjusted hazard ratio, 7.37 [95% CI, 2.00–27.13]; P =0.003), whereas cluster 2 was associated with higher noncardiac mortality (adjusted hazard ratio, 3.35 [95% CI, 1.26–8.90]; P =0.015). Phenotypes and association of clusters with specific outcomes were reproduced in an independent validation cohort (n=262). Conclusions: Unsupervised cluster analysis of patients with AS revealed 3 distinct groups with different causes of death. This provides a new perspective in the categorization of patients with AS that takes into account comorbidities and extravalvular cardiac dysfunction. Abstract : Supplemental Digital Content is available in the text. … (more)
- Is Part Of:
- Circulation. Volume 13:Number 5(2020)
- Journal:
- Circulation
- Issue:
- Volume 13:Number 5(2020)
- Issue Display:
- Volume 13, Issue 5 (2020)
- Year:
- 2020
- Volume:
- 13
- Issue:
- 5
- Issue Sort Value:
- 2020-0013-0005-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-05-16
- Subjects:
- aortic valve stenosis -- cluster analysis -- demography -- echocardiography -- machine learning
Cardiovascular system -- Imaging -- Periodicals
Heart -- Imaging -- Periodicals
616.1075405 - Journal URLs:
- http://circimaging.ahajournals.org/ ↗
http://journals.lww.com ↗ - DOI:
- 10.1161/CIRCIMAGING.119.009707 ↗
- Languages:
- English
- ISSNs:
- 1941-9651
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3265.262750
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19700.xml