Choi You-Jung, Park Jaemin, Hwang Doyeon, Kook Woong, Kim Yong-Jin, Tanaka Hidekazu, Hozumi Takeshi, Yuasa Toshinori, Ling Lieng Hsi, Yu Cheuk-Man, Park Seung Woo, Ha Jong-Won, Otsuji Yutaka, Song Jae-Kwan, Sohn Dae-Won, Lim Seon-Hee, Lee Seung-Pyo
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.
JACC Cardiovasc Imaging. 2022 Jun;15(6):974-986. doi: 10.1016/j.jcmg.2021.12.014. Epub 2022 Feb 16.
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.
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.
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.
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).
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.
拓扑数据分析（TDA）可以通过分析大型复杂数据生成患者-患者相似性网络，并得出标准统计学可能无法获得的新见解。
本文旨在发现慢性原发性二尖瓣反流（MR）患者的新表型，并使用超声心动图数据的网络分析来分析其临床意义。
前瞻性纳入来自11家亚洲三级医院的慢性中重度原发性MR患者（n = 850；平均年龄56.9±14.2岁，男性占57.9%）。我们使用14个人口统计学和超声心动图变量进行TDA以生成网络模型。患者按网络中的表型分组，并比较各组的预后。
TDA生成的网络模型显示出3个不同的表型组。A组最年轻，合并症较少，但左心室（LV）收缩末期容积增加，代表慢性原发性MR中常见的代偿性LV扩张。B组年龄最大，患有高血压且以舒张功能障碍为主，但LV大小相对保留，这是慢性原发性MR中未被注意到的表型。C组显示LV重塑进展，收缩、舒张功能受损且LV扩张，提示晚期慢性原发性MR。在随访期间（中位时间3.5年），60例患者因有症状的MR接受手术或死于心血管原因。Kaplan-Meier曲线表明，尽管C组临床结局最差（P < 0.001），但以舒张功能障碍为特征的B组尽管LV腔大小保留，其无事件生存率与A组相当。网络模型的分组信息是MR手术或心血管死亡复合终点的独立预测因素（校正后HR：1.918；95%CI：1.257 - 2.927；P = 0.003）。
TDA生成的患者-患者相似性网络直观显示了慢性原发性MR中不同的重塑模式，并揭示了目前未被重视的不同表型。重要的是，在理解慢性原发性MR的临床表现时，舒张功能障碍应得到同等关注。
