基于心脏磁共振右心室-肺动脉耦联参数在评估CTD-PH危险分层中的研究
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南京医科大学第一附属医院

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国家自然科学基金项目(面上项目,重点项目,重大项目)


The study of CMR based right Ventricular-Pulmonary Arterial Coupling in the Assessment of CTD-PH Risk Stratification
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81601464, 61871117

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    摘要:

    目的:探讨基于心脏磁共振(CMR)右心室-肺动脉耦联(VAC)参数在评估结缔组织疾病相关肺动脉高压(CTD-PH)危险分层中的应用价值。方法:回顾性分析2018年6月至2022年4月期间62例CTD-PH患者临床及CMR资料,根据危险分层将其分为低危及中低危组(n=39例)和中高危及高危组(n=23例),并对患者的左右心室容积、功能参数、左心室心肌组织学参数及VAC进行分析,寻找用于预测CTD- PH危险分层的最佳模型。结果:右心室容积功能参数和右心室插入部的组织学参数在两组PH患者的差异有统计学意义(P<0.05)。右室容积参数中右室最大容积指数(RVEDVI)和VAC具有独立预测效能,联合RVEDVI和VAC具有最高的预测准确性(AUC=0.839,95%CI: 0.735-0.944, P<0.001)。结论:右心室相关的容积、功能参数和右心室插入部的组织学参数可用于评估CTD-PH危险分层,联合RVEDVI和VAC可提高评估危险分层的准确性。

    Abstract:

    OBJECTIVE: To investigate the value of cardiac magnetic resonance (CMR) based right ventricle-pulmonary artery coupling (VAC) parameters in assessing risk stratification of connective tissue disease-related pulmonary hypertension (CTD-PH). METHODS: The clinical and CMR data of 62 patients with CTD-PH between June 2018 and April 2022 were retrospectively analyzed, and they were divided into low-risk low to moderate-risk group (n=39 patients) and moderate-high risk high-risk group (n=23 patients) according to risk stratification, and the patients' right and left ventricle-related volumetric,functional parameters, left ventricular tissue characterization parameters and VAC were statistically analyzed. The optimal model was sought to predict CTD- PH risk stratification. RESULTS: The differences in right ventricle-related volumes, functional parameters, and histological parameters of the right ventricular insertion were statistically significant in the two groups of patients with PH (P<0.05). The RVEDVI and VAC independent predictors, and the combination of RVEDVI and VAC had the best predictive accuracy (AUC=0.839, 95% CI: 0.735-0.944, P<0.001). CONCLUSIONS: Right ventricle-related volumes, functional parameters and tissue characterization parameters of the right ventricular insertion can be used to assess CTD-PH risk stratification; the combination of RVEDVI and VAC improves the accuracy of assessing risk stratification.

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  • 收稿日期:2022-09-27
  • 最后修改日期:2023-02-27
  • 录用日期:2023-08-09
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