The Right Heart Network and Risk Stratification in Pulmonary Arterial Hypertension.
The Right Heart Network and Risk Stratification in Pulmonary Arterial Hypertension.
复制标题
肺动脉高压的右心网络和危险分层。
DOI：
10.1016/j.chest.2021.10.045
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发表时间：
2022-05
期刊：
影响因子：
9.6
通讯作者：
Sweatt, Andrew J.
中科院分区：
文献类型：
--
作者：
Haddad, Francois;Contrepois, Kevin;Amsallem, Myriam;Denault, Andre Y.;Bernardo, Roberto J.;Jha, Alokkumar;Taylor, Shalina;Ataam, Jennifer Arthur;Mercier, Olaf;Kuznetsova, Tatiana;Noordegraaf, Anton Vonk;Zamanian, Roham T.;Sweatt, Andrew J.
关键词：
肺动脉高压的预后与右心功能指标密切相关。更好地了解它们之间的关系可能会对PAH的风险分层提供重要的启示。临床网络图能为PAH的风险分层提供信息吗？研究队列包括231名PAH患者，平均随访时间为7.1年。一个非定向的相关网络被用来可视化PAH临床特征之间的关系。这个网络丰富了右心参数，包括N末端激素前体B型利钠肽(NT-proBNP)、综合超声心动图参数和血流动力学，以及6分钟步行距离(6MWD)、生命体征、实验室数据和一氧化碳弥散量(DLCO)。通过使用特征向量和介数中心度来评估连通性，以分别反映全球和区域连通性。COX比例风险回归用于建立死亡或肺移植联合终点的无事件存活率模型。确定了以NT-proBNP为中心的紧密交织的特征网络，其中6MWD作为次要枢纽出现。连接较少的结节包括DLCO、收缩压、白蛋白和钠。在随访期内，92例(39.8%)患者死亡或发生移植。当右心中央特征(NT-proBNP和右室收缩末期重构指数)与6MWD和较少连接的结节(DLCO、收缩压、白蛋白、钠、性别、结缔组织病病因和前列腺素治疗)相结合时，获得了一个强大的预后模型，Harrell‘s C指数为0.81(0.77-0.85)。当加入基线风险模型时，NT-ProBNP的系列变化显著改善了5年后的结果预测(C统计量增加0.071±0.024；P=0.003)。NT-proBNP在相互交织的PAH网络中成为一个中心枢纽。连通性分析为结果模型中的特征选择和组合提供了可解释性。
Prognosis in pulmonary arterial hypertension (PAH) is closely related to indexes of right ventricular function. A better understanding of their relationship may provide important implications for risk stratification in PAH. Can clinical network graphs inform risk stratification in PAH? The study cohort consisted of 231 patients with PAH followed up for a median of 7.1 years. An undirected, correlation network was used to visualize the relationship between clinical features in PAH. This network was enriched for right heart parameters and included N-terminal pro-hormone B-type natriuretic peptide (NT-proBNP), comprehensive echocardiographic parameters, and hemodynamics, as well as 6-min walk distance (6MWD), vital signs, laboratory data, and diffusing capacity for carbon monoxide (Dlco). Connectivity was assessed by using eigenvector and betweenness centrality to reflect global and regional connectivity, respectively. Cox proportional hazards regression was used to model event-free survival for the combined end point of death or lung transplantation. A network of closely intertwined features centered around NT-proBNP with 6MWD emerging as a secondary hub were identified. Less connected nodes included Dlco, systolic BP, albumin, and sodium. Over the follow-up period, death or transplantation occurred in 92 patients (39.8%). A strong prognostic model was achieved with a Harrell’s C-index of 0.81 (0.77-0.85) when combining central right heart features (NT-proBNP and right ventricular end-systolic remodeling index) with 6MWD and less connected nodes (Dlco, systolic BP, albumin, sodium, sex, connective tissue disease etiology, and prostanoid therapy). When added to the baseline risk model, serial change in NT-proBNP significantly improved outcome prediction at 5 years (increase in C-statistic of 0.071 ± 0.024; P = .003). NT-proBNP emerged as a central hub in the intertwined PAH network. Connectivity analysis provides explainability for feature selection and combination in outcome models.
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影响因子：
1
作者：
Brandes, U
通讯作者：
Brandes, U
影响因子：
4.4
作者：
BONACICH, P
通讯作者：
BONACICH, P
影响因子：
24.3
作者：
Kanwar, Manreet K.;Gomberg-Maitland, Mardi;Benza, Raymond L.
通讯作者：
Benza, Raymond L.
DOI：
10.1016/j.echo.2009.01.021
发表时间：
2009-05-01
影响因子：
6.5
作者：
Haddad, Francois;Zamanian, Roham;Rosenthal, David
通讯作者：
Rosenthal, David
影响因子：
9.6
作者：
Benza, Raymond L.;Gomberg-Maitland, Mardi;Frantz, Robert P.
通讯作者：
Frantz, Robert P.