JACC Cardiovasc Imaging. 2022;15(6):974-986.
Network Analysis of Cardiac Remodeling by Primary Mitral Regurgitation Emphasizes the Role of Diastolic Function.
제1저자 최유정, 박재민 · 교신저자 이승표, 임선희
소속 (13)
- Department of Internal Medicine and Cardiovascular Center, Seoul National University Hospital, Seoul, Republic of Korea.
- Department of Mathematical Sciences, Seoul National University, Seoul, Republic of Korea.
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe, Japan.
- Department of Cardiovascular Medicine, Wakayama Medical University, Wakayama, Japan.
- Department of Cardiovascular Medicine and Hypertension, Kagoshima University, Kagoshima, Japan.
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
- Division of Cardiology, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China.
- Division of Cardiology, Department of Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea.
- Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine, Hospital of University of Occupational and Environmental Health, Kitakyushu, Japan.
- Division of Cardiology, Department of Internal Medicine, Asan Medical Center Heart Institute, University of Ulsan College of Medicine, Seoul, Republic of Korea.
- Department of Mathematical Sciences, Seoul National University, Seoul, Republic of Korea. Electronic address: slim@snu.ac.kr.
- Department of Internal Medicine and Cardiovascular Center, Seoul National University Hospital, Seoul, Republic of Korea. Electronic address: sproll1@snu.ac.kr.
Abstract
BACKGROUND Topological data analysis (TDA) can generate patient-patient similarity networks by analyzing large, complex data and derive new insights that may not be possible with standard statistics.
OBJECTIVES The purpose of this paper was to discover novel phenotypes of chronic primary mitral regurgitation (MR) patients and to analyze their clinical implications using network analysis of echocardiographic data.
METHODS Patients with chronic moderate to severe primary MR were prospectively enrolled from 11 Asian tertiary hospitals (n = 850; mean age 56.9 ± 14.2 years, 57.9% men). We performed TDA to generate network models using 14 demographic and echocardiographic variables. The patients were grouped by phenotypes in the network, and the prognosis was compared by groups.
RESULTS The network model by TDA revealed 3 distinct phenogroups. Group A was the youngest with fewer comorbidities but increased left ventricular (LV) end-systolic volume, representing compensatory LV dilation commonly seen in chronic primary MR. Group B was the oldest with high blood pressure and a predominant diastolic dysfunction but relatively preserved LV size, an unnoticed phenotype in chronic primary MR. Group C showed advanced LV remodeling with impaired systolic, diastolic function, and LV dilation, indicating advanced chronic primary MR. During follow-up (median 3.5 years), 60 patients received surgery for symptomatic MR or died of cardiovascular causes. Kaplan-Meier curves demonstrated that although group C had the worst clinical outcome (P < 0.001), group B, characterized by diastolic dysfunction, had an event-free survival comparable to group A despite preserved LV chamber size. The grouping information by the network model was an independent predictor for the composite of MR surgery or cardiovascular death (adjusted HR: 1.918; 95% CI: 1.257-2.927; P = 0.003).
CONCLUSIONS The patient-patient similarity network by TDA visualized diverse remodeling patterns in chronic primary MR and revealed distinct phenotypes not emphasized currently. Importantly, diastolic dysfunction deserves equal attention when understanding the clinical presentation of chronic primary MR.
Copyright © 2022 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Keywords
clinical outcomediastolic dysfunctionmitral valve insufficiencytopological data analysis,
Comment · 정정
Conflict of interest statement
Funding Support and Author Disclosures This work was supported by grants from the National Research Foundation of Korea; a grant funded by the Korean government (Ministry of Science and ICT) (No. 2019R1A2C2084099); and the Seoul National University Hospital research fund (03-2020-0430). The authors have reported that they have no relationships relevant to the contents of this paper to disclose.
그 밖의 정보
- 출판 형태
- Journal Article, Research Support, Non-U.S. Gov't
- 저널
- JACC. Cardiovascular imaging · eISSN 1876-7591
- 전자 출판
- 2022-02-16
- MeSH
- Humans · Mitral Valve · Mitral Valve Insufficiency* · Predictive Value of Tests · Ventricular Dysfunction, Left* / diagnostic imaging / etiology · Ventricular Function, Left · Ventricular Remodeling