Baker Heart and Diabetes Institute, Melbourne, Australia; Department of Medicine, University of Melbourne, Melbourne, Australia; Western Health, Melbourne, Australia.
Baker Heart and Diabetes Institute, Melbourne, Australia; Monash University Alfred Health, Melbourne, Australia.
JACC Cardiovasc Imaging. 2021 May;14(5):915-927. doi: 10.1016/j.jcmg.2020.12.029. Epub 2021 Mar 17.
This study determined whether flow state classified by stroke volume index (SVi) or transvalvular flow rate (FR) improved risk stratification of all-cause mortality, hospitalization due to heart failure, and aortic valvular interventions for patients with severe aortic stenosis (AS).
SVi is a widely accepted classification for flow state in severe low-flow, low-gradient (LFLG) AS. Recent studies suggest that FR more closely approximates true AS severity and provides more useful prognostication than SVi.
Patients with severe AS over a 7-year period were subclassified by echocardiographic parameters. LFLG-AS was defined as severe AS (aortic valve area index [AVAi]: <0.6 cm/m), with a mean transvalvular pressure gradient of <40 mm Hg in the setting of low flow state: SVi of <35 ml/m and/or FR of <200 ml/s and subclassified into preserved (≥50%; paradoxical) or reduced (<50%; classical) left ventricular ejection fraction (LVEF).
Among 621 consecutive patients with severe AS, the proportions of patients classified as LFLG-AS were different between SVi and FR (p < 0.001). Classification using SVi, FR, and LVEF was a strong predictor of the composite endpoint at the 2-year follow-up. The addition of SVi to the echocardiographic and clinical model provided significant improvement in reclassification (net reclassification improvement: 0.089; 95% confidence interval [CI]: 0.045 to 0.133; p = 0.04), whereas addition of FR did not (net reclassification improvement: 0.061; 95% CI: 0.016 to 0.106; p = 0.17). C-statistics indicated improved risk discrimination when AVAi, LVEF, and SVi or FR were added as predictive variables to the clinical model (p = 0.006).
Low SVi or FR was associated with adverse cardiovascular events and showed improvement in discrimination, but only SVi, not FR, significantly improved risk reclassification compared to other conventional clinical and echocardiographic predictors. This suggests that FR is not superior to SVi in distinguishing true severe from pseudosevere forms of AS and identification of patients with LFLG-AS who have worse outcomes.
本研究旨在确定以每搏量指数（SVi）或跨瓣流量（FR）分类的血流状态是否能改善重度主动脉瓣狭窄（AS）患者的全因死亡率、因心力衰竭住院和主动脉瓣介入治疗的风险分层。
SVi 是一种广泛接受的重度低流量、低梯度（LFLG）AS 血流状态分类方法。最近的研究表明，FR 更接近真实的 AS 严重程度，并提供比 SVi 更有用的预后信息。
对 7 年间的重度 AS 患者进行超声心动图参数分类。LFLG-AS 定义为重度 AS（主动脉瓣口面积指数[AVAi]：<0.6cm/m），伴有低血流状态下平均跨瓣压差<40mmHg：SVi<35ml/m 和/或 FR<200ml/s，并根据左心室射血分数（LVEF）分为保留（≥50%；反常）或降低（<50%；经典）。
在 621 例连续重度 AS 患者中，SVi 和 FR 分类的 LFLG-AS 患者比例不同（p<0.001）。使用 SVi、FR 和 LVEF 进行分类是 2 年随访时复合终点的强预测因子。SVi 加入超声心动图和临床模型后，再分类显著改善（净再分类改善：0.089；95%置信区间[CI]：0.045 至 0.133；p=0.04），而 FR 无显著改善（净再分类改善：0.061；95%CI：0.016 至 0.106；p=0.17）。C 统计量表明，当将 AVAi、LVEF 和 SVi 或 FR 添加为临床模型的预测变量时，风险区分度提高（p=0.006）。
低 SVi 或 FR 与不良心血管事件相关，且能提高区分度，但仅 SVi，而非 FR，与其他传统临床和超声心动图预测因素相比，能显著改善风险再分类。这表明，FR 并不能在区分真性重度和假性重度 AS 以及识别 LFLG-AS 患者中具有更差结局的患者方面优于 SVi。
