Department of Anaesthesia & Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China.
Anesth Analg. 2010 Nov;111(5):1180-92. doi: 10.1213/ANE.0b013e3181f08a5b. Epub 2010 Aug 24.
Numerous cardiac output (CO) monitors have been produced that provide continuous rather than intermittent readings. Bland and Altman has become the standard method for validating their performance against older standards. However, the Bland and Altman method only assesses precision and does not assess how well a device detects serial changes in CO (trending ability). Currently, there is no consensus on how trending ability, or trend analysis, should be performed. Therefore, we performed a literature review to identify articles published between 1997 and 2009 that compared methods of continuous CO measurement. Identified articles were grouped according to measurement technique and statistical methodology. Articles that analyzed trending ability were reviewed with the aim of finding an acceptable statistical method. Two hundred two articles were identified. The most popular methods were pulse contour (69 articles), Doppler (54), bioimpedance (38), and transpulmonary or continuous thermodilution (27). Forty-one articles addressed trending, and of these only 23 provided an in-depth analysis. Several common statistical themes were identified: time plots, regression analysis, Bland and Altman using change in CO (ΔCO), and the 4-quadrant plot, which used direction of change of ΔCO to determine the concordance. This plot was further refined by exclusion of data when values were small. Receiver operating characteristic curves were used to define the exclusion zone. In animal studies, a reliable reference standard such as an aortic flowprobe was frequently used, and regression or time plots could be used to show trending. Clinical studies were more problematic because data collection points were fewer (8-10 per subject). The consensus was to use the 4-quadrant plot with exclusion zones and apply concordance analysis. A concordance rate of >92% when using a 15% zone indicated good trending. A new method of presenting trend data (ΔCO) on a polar plot is proposed. Agreement was shown by the angle with the horizontal axis and ΔCO by the distance from the center. Trending can be assessed by the vertical limits of the data, similar to the Bland and Altman method.
许多心输出量(CO)监测仪已经生产出来,可以提供连续的而不是间歇的读数。 Bland 和 Altman 已经成为验证其性能的标准方法,以替代旧标准。然而, Bland 和 Altman 方法仅评估精度,而不评估设备检测 CO 连续变化的能力(趋势能力)。目前,对于如何进行趋势能力或趋势分析,尚无共识。因此,我们进行了文献回顾,以确定 1997 年至 2009 年间发表的比较连续 CO 测量方法的文章。根据测量技术和统计方法,将确定的文章进行分组。对分析趋势能力的文章进行了回顾,目的是找到一种可接受的统计方法。确定了 202 篇文章。最流行的方法是脉冲轮廓(69 篇)、多普勒(54 篇)、生物阻抗(38 篇)和经肺或连续热稀释(27 篇)。41 篇文章涉及趋势分析,其中只有 23 篇进行了深入分析。确定了几个常见的统计主题:时间图、回归分析、使用 CO 变化(ΔCO)的 Bland 和 Altman、4 象限图,该图使用 ΔCO 变化的方向来确定一致性。通过排除值较小时的数据,进一步细化了该图。使用接收者操作特征曲线来定义排除区。在动物研究中,经常使用可靠的参考标准,如主动脉流量探头,并且可以使用回归或时间图来显示趋势。临床研究更具挑战性,因为每个受试者的数据采集点较少(8-10 个)。共识是使用带排除区的 4 象限图,并应用一致性分析。当使用 15%的区域时,一致性率>92%表示良好的趋势。提出了一种新的趋势数据(ΔCO)在极坐标图上的表示方法。通过与横轴的夹角和距中心点的距离表示ΔCO。可以通过数据的垂直范围来评估趋势,类似于 Bland 和 Altman 方法。