麻醉深度监测：BIS之外还可以用的指标是？

本文由“小麻哥的日常"授权转载

摘要译文（供参考）

心率动力学的分形特性：

全身麻醉双相变化和脊麻时降低的新生物标志物

经过处理的脑电图（electroencephalogram，EEG）被认为是测量麻醉深度（depth of anesthesia，DOA）的有用工具。

然而，由于它无法检测负责大多数生命体征的脑干和脊髓的活动，因此需要一种新的生物标志物来测量麻醉下中枢神经系统的多维活动。

去趋势波动分析（Detrended fluctuation analysis，DFA）是一种检测非平稳心率（heart rate，HR）行为标度特性的新技术。

本研究研究了在静脉注射异丙酚、吸入地氟醚和脊髓麻醉下心率变异性（heart rate variability，HRV）的分形特性（一种非线性分析）的变化。

我们将DFA方法与传统的光谱分析进行了比较，以评估其在不同麻醉水平下作为替代生物标志物的潜力。

80名接受择期手术的患者被随机分配不同的麻醉。

HRV通过频谱分析和DFA短期（4-11拍）标度指数（DFAα1）测量。

在异丙酚或地氟醚麻醉期间，观察到DFAα1增加，随后在较高浓度下下降。

脊髓麻醉降低了DFAα1和低频/高频比值（LF/HF比值）。

HRV的DFAα1是区分从基线到麻醉状态变化的敏感和特异的方法。

DFAα1提供了一种潜在的实时生物标志物，以测量HRV作为DOA的多个维度之一。

关键词：

麻醉深度；去趋势波动分析；全身麻醉；短期标度指数（DFAα1）；脊麻。

图1脊麻R-R间期频谱分析示例。

（a） 在没有任何术前准备的情况下，在手术当天，患者在术前基线数据收集前至少5分钟以仰卧姿势躺在安静的房间里。

（b） 脊髓麻醉后30分钟通过R-R间期频谱分析进行功率转换。

（c） 60秒的滑动窗口显示了脊髓麻醉后低频和高频的转换功率。

图2 DFA的计算。

（a） 原始R–R间隔和综合时间序列。

（b） 整个时间序列分为几个部分；然后通过减去最佳线性拟合F（n）对每个段进行去趋势化。

（c） 作为分段大小n的函数的去趋势时间序列的均方根。

（d）如果时间序列是自相似的，则关系表明存在幂律（分形）缩放。缩放指数α可以通过F（n）对n的对数对对数图上的线性拟合来估计。α值表示时间序列的相关特性。全局缩放指数a值在n的范围内计算，在n＝4和n＝165空间之间。在n=4和n=11之间计算短期α1。

图3 P组（异丙酚）在基线和全麻后的LF/HF比值；D组（地氟醚）。

方框图将中值、第10、第25、第75和第90百分位数显示为带有误差条的垂直方框，并将位于第10和第90个百分位数之外的所有数据点绘制为黑色圆圈点。基线和连续测量期之间配对t检验的显著性水平如下：*p<0.05。

图4 P组（异丙酚）在基线和全麻后的DFAα1比值；D：D组（地氟醚）。

方框图将中值、第10、第25、第75和第90百分位数显示为带有误差条的垂直方框，并将第10和第90个百分位数以外的所有数据点绘制为黑色圆圈点。基线和连续测量期之间配对t检验的显著性水平如下：*p<0.05；***p<0.001。

图5基线和脊髓麻醉后的LF/HF比值。

（A） ：LM组；（B） ：LMf组；方框图将中值、第10、第25、第75和第90百分位数显示为带有误差条的垂直方框，并将第10和第90个百分位数以外的所有数据点绘制为黑色圆圈点。基线和连续测量期之间配对t检验的显著性水平如下：**p<0.01；***p<0.001。

图6基线和脊髓麻醉后的DFAα1。

（A） ：LM组；（B） ：LMf组；方框图将中值、第10、第25、第75和第90百分位数显示为带有误差条的垂直方框，并将第10和第90个百分位数以外的所有数据点绘制为黑色圆圈点。基线和连续测量期之间配对t检验的显著性水平如下：***p<0.001。

图7基线和椎管后（A）和全身麻醉（B，C）时DFAα1和LF/HF比值的受试者操作曲线分析显示HRV的分形分析提供了比传统光谱测量更敏感和更具体的信息。

原文摘要

Fractal Properties of Heart Rate Dynamics: 

A New Biomarker for Anesthesia-Biphasic Changes in General Anesthesia and Decrease in Spinal Anesthesia

Processed electroencephalogram (EEG) has been considered a useful tool for measuring the depth of anesthesia (DOA). However, because of its inability to detect the activities of the brain stem and spinal cord responsible for most of the vital signs, a new biomarker for measuring the multidimensional activities of the central nervous system under anesthesia is required. Detrended fluctuation analysis (DFA) is a new technique for detecting the scaling properties of nonstationary heart rate (HR) behavior. This study investigated the changes in fractal properties of heart rate variability (HRV), a nonlinear analysis, under intravenous propofol, inhalational desflurane, and spinal anesthesia. We compared the DFA method with traditional spectral analysis to evaluate its potential as an alternative biomarker under different levels of anesthesia. Eighty patients receiving elective procedures were randomly allocated different anesthesia. HRV was measured with spectral analysis and DFA short-term (4-11 beats) scaling exponent (DFAα1). An increase in DFAα1 followed by a decrease at higher concentrations during propofol or desflurane anesthesia is observed. Spinal anesthesia decreased the DFAα1 and low-/high-frequency ratio (LF/HF ratio). 

DFAα1 of HRV is a sensitive and specific method for distinguishing changes from baseline to anesthesia state. The DFAα1 provides a potential real-time biomarker to measure HRV as one of the multiple dimensions of the DOA.

Keywords: depth of anesthesia (DOA); detrended fluctuation analysis (DFA); general anesthesia; short-term scaling exponent (DFAα1); spinal anesthesia.

Figure 1 An example of spinal anesthesia R-R interval spectral analysis. (a) Without any premedication, on the day of surgery, the patient lay in a supine position in a quiet room at least 5 min prior to preanesthetic baseline data collection. (b) Shifting of power by R-R interval spectral analysis 30 min after spinal anesthesia. (c) The sliding window of 60 s shows the shifting power of LF and HF after spinal anesthesia.

Figure 2 Calculation of DFA. (a) Original R–R interval and integrated time series. (b) The total time series was divided into segments; each segment was then detrended by subtracting the best linear fit F(n). (c) Root mean square of the detrended time series as a function of the segment size n. (d) If the time series is self-similar, a relationship indicates the presence of power law (fractal) scaling. The scaling exponent α can be estimated by a linear fit on the log-to-log plot of F(n) versus n. The α value represents the correlation properties of the time series. The global scaling exponent a value was calculated within the range of n, between n = 4 and n = 165 space. Short-term α1 was calculated between n = 4 and n = 11.

Figure 3 LF/HF ratio at baseline and post-general anesthesia for Group P (propofol); Group D (desflurane). Box plots show the median, 10th, 25th, 75th, and 90th percentiles as vertical boxes with error bars and plot all data points that lie outside the 10th and 90th percentiles as black circle dots. The significance levels with paired t-tests between baseline and successive measurement periods are as follows: * p < 0.05.

Figure 4 DFAα1 ratio at baseline and post-general anesthesia for Group P (propofol); D: Group D (desflurane). Box plots showing the median, 10th, 25th, 75th, and 90th percentiles as vertical boxes with error bars and plot all data points outside the 10th and 90th percentiles as black circle dots. The significance levels with paired t-tests between baseline and successive measurement periods are as follows: * p < 0.05; *** p < 0.001.

Figure 5 LF/HF ratio at baseline and post-spinal anesthesia. (A): Group LM; (B): Group LMf; Box plots showing the median, 10th, 25th, 75th, and 90th percentiles as vertical boxes with error bars and plot all data points outside the 10th and 90th percentiles as black circle dots. The significance levels with paired t-tests between baseline and successive measurement periods are as follows: ** p < 0.01; *** p < 0.001.

Figure 6 DFAα1 at baseline and post-spinal anesthesia. (A): Group LM; (B): Group LMf; Box plots showing the median, 10th, 25th, 75th, and 90th percentiles as vertical boxes with error bars and plot all data points outside the 10th and 90th percentiles as black circle dots. The significance levels with paired t-tests between baseline and successive measurement periods are as follows: *** p < 0.001.

Figure 7 Receiver-operating curves analyses of DFAα1 and LF/HF ratio at baseline and postspinal (A) and general anesthesia (B,C) showing fractal analysis of HRV provided a more sensitive and specific information than traditional spectral measurement.

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