BACKGROUND Mitral regurgitation (MR) is a frequent consequence of mitral valve prolapse (MVP). However, the echocardiographic grading of MR is challenging, and the recommended grading parameters have several limitations. The authors developed a novel echocardiographic parameter to grade MR, the average pixel intensity (API) method, on the basis of pixel intensity analysis of the continuous-wave Doppler signal. METHODS Transthoracic echocardiography was performed prospectively in consecutive patients with MVP (N = 149). MR was quantitatively assessed using the API method, vena contracta width, effective regurgitant orifice area, and regurgitant volume. The primary clinical events were cardiovascular mortality, mitral valve surgery, percutaneous mitral intervention, and heart failure hospitalization. RESULTS The API method was feasible in 90% of all patients with MVP, which was significantly higher than vena contracta width, effective regurgitant orifice area, and regurgitant volume. During a median follow-up period of 17 months, 44 patients (32%) had major adverse cardiac events, and the majority of events occurred in the holosystolic MVP subgroup. The degree of MR severity by the API method was highly significant for the prediction of events. An API cutoff of 111 arbitrary units was defined as "severe" MR due to MVP, with overall superior sensitivity and specificity compared with cutoffs for established MR grading parameters. In patients who did not have major adverse cardiac events during the follow-up period (n = 92), no significant changes in measures of MR severity were found on follow-up echocardiography. CONCLUSIONS The API method is predictive of clinical events and outcomes in MR due to MVP. Therefore, the API method may be considered for grading the severity of MR due to MVP in clinical practice.

中文翻译：

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二尖瓣脱垂的平均像素强度方法和二尖瓣关闭不全的结果。

背景技术二尖瓣关闭不全（MR）是二尖瓣脱垂（MVP）的常见后果。但是，MR的超声心动图分级具有挑战性，推荐的分级参数有几个局限性。作者在连续波多普勒信号的像素强度分析的基础上，开发了一种新的超声心动图参数来对MR（平均像素强度（API）方法）进行分级。方法对连续性MVP（N = 149）患者进行经胸超声心动图检查。使用API​​方法，收缩腔宽度，有效反流孔面积和反流体积对MR进行了定量评估。主要的临床事件是心血管疾病死亡率，二尖瓣手术，经皮二尖瓣介入治疗和心力衰竭住院。结果API方法在所有MVP患者中都是可行的，其中90％明显高于腔静脉收缩宽度，有效反流孔面积和反流体积。在17个月的中位随访期中，有44例患者（占32％）发生了严重的不良心脏事件，大部分事件发生在全收缩期MVP亚组中。API方法的MR严重程度对于事件的预测非常重要。由于MVP，将111个任意单位的API临界值定义为“严重” MR，与已建立的MR分级参数的临界值相比，其总体灵敏度和特异性更高。在随访期间未发生重大不良心脏事件的患者（n = 92），在随访超声心动图上未发现MR严重程度的测量有明显变化。结论API方法可预测由于MVP引起的MR的临床事件和结局。因此，在临床实践中，可以考虑使用API​​方法对由于MVP引起的MR的严重程度进行分级。