Department of Clinical Physiology, Sahlgrenska University Hospital, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Institute of Medicine, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
Department of Clinical Physiology, Sahlgrenska University Hospital, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Department of Cardiology, Sahlgrenska University Hospital, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Department of Radiology, Sahlgrenska University Hospital, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Institute of Medicine, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
J Am Soc Echocardiogr. 2018 Sep;31(9):1002-1012.e2. doi: 10.1016/j.echo.2018.04.002. Epub 2018 May 31.
The recently published integrative algorithms for echocardiographic grading of native aortic regurgitation (AR) and mitral regurgitation (MR) by the American Society of Echocardiography are consensus based and have not been evaluated. Thus, the aims of the present study were to investigate the feasibility of individual parameters and to evaluate the ability of the algorithms to discriminate severe from moderate regurgitation.
This prospective study comprised 93 patients with chronic AR (n = 45) and MR (n = 48). All patients underwent echocardiography and cardiovascular magnetic resonance within 4 hours. The algorithms were evaluated using two different definitions for severe regurgitation: (1) a cardiovascular magnetic resonance standard indicating future need for valve surgery and (2) a clinical standard using patients who underwent valve surgery with proven postoperative left ventricular reverse remodeling and improved functional class (AR/MR, n = 26/26).
The feasibility of the criteria in the first step of the algorithm was higher (AR/MR, 95%/91%) compared with the second step using quantitative Doppler parameters (74%/57%). For the AR algorithm, sensitivity was 95% and specificity 44%, whereas for the MR algorithm, sensitivity was 73% and specificity 92%. Among patients with benefit of surgery, the algorithms correctly identified 77%, misclassified 8%, and were inconclusive in 15% of the patients with AR; the corresponding figures were 73%, 15%, and 12% in the patients with MR.
Using cardiovascular magnetic resonance as reference, the recommended algorithms for grading of regurgitation have the ability to rule out severe AR and rule in severe MR. The quantitative Doppler methods are hampered by feasibility issues, and our findings suggest that the decision regarding surgical intervention in symptomatic patients with discordant or inconclusive echocardiographic grading should be based on a consolidated assessment of clinical and multimodality findings.
美国超声心动图学会最近发布的用于评估原发性主动脉瓣反流（AR）和二尖瓣反流（MR）的综合分级算法是基于共识的，尚未进行评估。因此，本研究旨在探讨各参数的可行性，并评估这些算法区分重度和中度反流的能力。
这项前瞻性研究纳入了 93 例慢性 AR（n=45）和 MR（n=48）患者。所有患者均在 4 小时内行超声心动图和心血管磁共振检查。该算法使用两种不同的重度反流定义进行评估：（1）心血管磁共振标准，表明未来需要瓣膜手术；（2）临床标准，即使用已行瓣膜手术且术后左心室逆重构和心功能分级改善的患者（AR/MR，n=26/26）。
算法第一步的标准可行性更高（AR/MR，95%/91%），而第二步使用定量多普勒参数的可行性更低（74%/57%）。对于 AR 算法，敏感性为 95%，特异性为 44%，而对于 MR 算法，敏感性为 73%，特异性为 92%。在受益于手术的患者中，该算法正确识别了 77%的患者，错误分类了 8%的患者，在 15%的 AR 患者中结果不确定；MR 患者中的对应数据分别为 73%、15%和 12%。
使用心血管磁共振作为参考，推荐的反流分级算法能够排除重度 AR 并确定重度 MR。定量多普勒方法受到可行性问题的限制，我们的研究结果表明，对于症状性患者，如果超声心动图分级存在不一致或不确定的情况，决定是否进行手术干预应基于对临床和多模态发现的综合评估。
