Biner Simon, Topilsky Yan, Banai Shmuel, Steinvil Arie, Arbel Yaron, Siegel Robert James, Beigel Roy, Keren Gad, Finkelstein Ariel
Department of Cardiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Division of Cardiology, Cedars-Sinai Medical Center, Los Angeles, California.
Echocardiography. 2015 Oct;32(10):1492-7. doi: 10.1111/echo.12893. Epub 2015 Jan 21.
Transcatheter aortic valve replacement (TAVR) has become a treatment option for patients with severe aortic stenosis (AS) and high surgical risk. Assessment of symptoms in these patients is challenging because of advanced age, comorbidities, and limited physical activity. Noninvasive quantification of pulmonary capillary wedge pressure (PCWP) in candidates for TAVR may be helpful for risk stratification. The objective of the study was to create a model for estimation of PCWP by echo Doppler in patients with severe AS.
Data from 80 patients with severe AS referred for TAVR were used to develop an echo Doppler model for predicting PCWP. Its performance was evaluated in the test cohort of 33 patients who had invasive and noninvasive evaluation. No single echo Doppler parameter estimated PCWP accurately. In the retrospective analysis, the multilinear regression provided an accurate estimate of PCWP (r(2) = 0.74). The model included, in order of importance (all P < 0.05), the ratio of early transmitral velocity (E) to annular velocity (E'), the left ventricular ejection fraction, and the velocity time integral of tricuspid regurgitation signal. In the prospective cohort of patients with severe AS, the model demonstrated good predictive ability of PCWP (r = 0.77, P < 0.01).
In patients with severe AS, noninvasive estimation of PCWP is possible by integration of two-dimensional, spectral, and tissue Doppler variables.
经导管主动脉瓣置换术（TAVR）已成为严重主动脉瓣狭窄（AS）且手术风险高的患者的一种治疗选择。由于这些患者年龄较大、合并多种疾病且体力活动受限，对其症状进行评估具有挑战性。对TAVR候选患者进行肺毛细血管楔压（PCWP）的无创量化可能有助于风险分层。本研究的目的是建立一个通过超声多普勒估计严重AS患者PCWP的模型。
来自80例因TAVR而转诊的严重AS患者的数据用于建立预测PCWP的超声多普勒模型。在33例进行了有创和无创评估的患者组成的测试队列中对其性能进行了评估。没有单一的超声多普勒参数能准确估计PCWP。在回顾性分析中，多元线性回归对PCWP提供了准确的估计（r² = 0.74）。该模型按重要性顺序（所有P < 0.05）包括早期二尖瓣流速（E）与瓣环流速（E'）之比、左心室射血分数以及三尖瓣反流信号的速度时间积分。在严重AS患者的前瞻性队列中，该模型显示出对PCWP具有良好的预测能力（r = 0.77，P < 0.01）。
在严重AS患者中，通过整合二维、频谱和组织多普勒变量可以对PCWP进行无创估计。
