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一种简单算法在评估舒张功能障碍及预测冠状动脉旁路移植术后转归中的应用。

Utility of a simple algorithm to grade diastolic dysfunction and predict outcome after coronary artery bypass graft surgery.

机构信息

Department of Anesthesiology, Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina 27710, USA.

出版信息

Ann Thorac Surg. 2011 Jun;91(6):1844-50. doi: 10.1016/j.athoracsur.2011.02.008. Epub 2011 Apr 14.

Abstract

BACKGROUND

Inclusion of a measure of left ventricular diastolic dysfunction (LVDD) may improve risk prediction after cardiac surgery. Current LVDD grading guidelines rely on echocardiographic variables that are not always available or aligned to allow grading. We hypothesized that a simplified algorithm involving fewer variables would enable more patients to be assigned a LVDD grade compared with a comprehensive algorithm, and also be valid in identifying patients at risk of long-term major adverse cardiac events (MACE).

METHODS

Intraoperative transesophageal echocardiography data were gathered on 905 patients undergoing coronary artery bypass graft surgery, including flow and tissue Doppler-based measurements. Two algorithms were constructed to categorize LVDD: a comprehensive four-variable algorithm, A, was compared with a simplified version, B, with only two variables-transmitral early flow velocity and early mitral annular tissue velocity-for ease of grading and association with MACE.

RESULTS

Using algorithm A, only 563 patients (62%) could be graded, whereas 895 patients (99%) received a grade with algorithm B. Over the median follow-up period of 1,468 days, Cox modeling showed that LVDD was significantly associated with MACE when graded with algorithm B (p=0.013), but not algorithm A (p=0.79). Patients with the highest incidence of MACE could not be graded with algorithm A.

CONCLUSIONS

We found that an LVDD algorithm with fewer variables enabled grading of a significantly greater number of coronary artery bypass graft patients, and was valid, as evidenced by worsening grades being associated with MACE. This simplified algorithm could be extended to similar populations as a valid method of characterizing LVDD.

摘要

背景

纳入左心室舒张功能障碍(LVDD)的评估可能会改善心脏手术后的风险预测。目前的 LVDD 分级指南依赖于超声心动图变量,但这些变量并不总是可用或一致,无法进行分级。我们假设,与综合算法相比,一种涉及较少变量的简化算法可以使更多的患者能够进行 LVDD 分级,并且也可以有效地识别出有发生长期主要不良心脏事件(MACE)风险的患者。

方法

收集了 905 例行冠状动脉旁路移植术的患者的术中经食管超声心动图数据,包括基于血流和组织多普勒的测量值。构建了两种算法来对 LVDD 进行分类:一种是综合的四变量算法 A,另一种是简化的两变量算法 B,仅包括二尖瓣早期血流速度和二尖瓣环早期组织速度,以便于分级和与 MACE 的相关性。

结果

使用算法 A,只有 563 例患者(62%)可以进行分级,而使用算法 B 可以对 895 例患者(99%)进行分级。在中位随访 1468 天期间,Cox 模型显示,使用算法 B 进行分级时,LVDD 与 MACE 显著相关(p=0.013),而使用算法 A 时不相关(p=0.79)。最高发生率的 MACE 患者无法用算法 A 进行分级。

结论

我们发现,一种具有较少变量的 LVDD 算法可以对更多的冠状动脉旁路移植患者进行分级,并且是有效的,因为等级恶化与 MACE 相关。这种简化的算法可以扩展到类似的人群中,作为一种有效的 LVDD 特征描述方法。

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