Background

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.

Methods

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).

Results

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.

Conclusions

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.

中文翻译：

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使用当前的美国超声心动图协会对慢性主动脉和二尖瓣关闭不全严重程度进行积分算法的评估：区分严重程度与中度关闭不全

背景

美国超声心动图协会最近发布的用于对自然主动脉瓣关闭不全（AR）和二尖瓣关闭不全（MR）进行超声心动图分级的集成算法是基于共识的，尚未进行评估。因此，本研究的目的是研究各个参数的可行性，并评估算法区分中度反流与重度反流的能力。

方法

这项前瞻性研究包括93例患有慢性AR（n  = 45）和MR（n  = 48）的患者。所有患者均在4小时内接受了超声心动图检查和心血管磁共振检查。使用两种不同的严重反流定义对算法进行了评估：（1）心血管磁共振标准，表明将来需要进行瓣膜手术；（2）进行瓣膜手术的患者，其术后左室反向重塑得到证实，功能等级得到了改善，这是一项临床标准（AR / MR，n ＝ 26/26）。

结果

与使用定量多普勒参数的第二步（74％/ 57％）相比，算法第一步中的标准可行性更高（AR / MR，95％/ 91％）。对于AR算法，灵敏度为95％，特异性为44％，而对于MR算法，灵敏度为73％，特异性为92％。在受益于手术的患者中，该算法正确识别出77％的患者，错误分类的8％，并且在15％的AR患者中没有定论；MR患者的相应数字分别为73％，15％和12％。

结论

以心血管磁共振为参考，推荐的反流分级算法具有排除严重AR和排除严重MR的能力。定量多普勒方法受到可行性问题的困扰，我们的研究结果表明，对有不协调或不确定性超声心动图分级的有症状患者进行手术干预的决定应基于对临床和多模态研究结果的综合评估。