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实验性和预测性双血氧饱和度变异性

Experimental and predicted dual oximetry variability.

作者信息

Wong D H, Weir P, Mahutte C K, Onishi R, Daves S, Foran W, Ferraro L, Barker S J

机构信息

Department of Anesthesiology, University of California, Irvine.

出版信息

J Clin Monit. 1993 Sep;9(4):268-74. doi: 10.1007/BF02886697.

Abstract

OBJECTIVE

We wished to determine whether the individual bias (mean difference) and precision (standard deviation of the difference) values of 2 variables, arterial oxygen saturation (SaO2) and mixed venous oxygen saturation (SvO2), could be used to predict the bias and precision values of the combined dual oximetry variable (SaO2-SvO2).

METHODS

We simultaneously measured SaO2 by pulse oximetry and arterial blood gas co-oximetry and SvO2 by fiberoptic reflectance oximetry pulmonary artery catheter and venous blood gas co-oximetry in 238 data sets from 55 patients. Three different methods were used to predict the standard deviation of the difference of (SaO2-SvO2) [s delta(SaO2-SvO2)]: simple sum, root mean square (RMS) error, and RMS error with correction term. We derived the equation for the RMS error with correction term because initial results showed that the simple sum and RMS error methods did not predict s delta(SaO2-SvO2) well. The correction term accounts for the non-independence of simultaneous SaO2 and SvO2 measurements.

RESULTS

The observed overall bias of the SaO2, SvO2, and (SaO2-SvO2) measurement methods were 0.17, -1.76, and 1.94, respectively. The observed overall s delta(SaO2-SvO2) of the (SaO2-SvO2) measurement method was 5.12. The simple sum method overestimated the actual s delta(SaO2-SvO2) by 38%, the RMS error method differed from the actual s delta(SaO2-SvO2) by 3%, and the RMS error with correction term method matched the actual s delta(SaO2-SvO2).

CONCLUSION

The bias of a (SaO2-SvO2) measurement method is simply the bias of the SaO2 measurement method less the bias of the SvO2 measurement method. s delta(SaO2-SvO2) is best predicted by the derived equation, RMS error with correction term. The same principles and equations also apply to other situations in which 2 variables with the same dimensions are combined into 1 variable, such as (PaCO2-EtCO2) gradients and perfusion-pressure gradients. Although the difference between the s delta(SaO2-SvO2) predicted by the RMS error equation and the derived RMS error equation with correction term was small, the difference may be significant for other combined variables.

摘要

目的

我们希望确定两个变量,即动脉血氧饱和度(SaO2)和混合静脉血氧饱和度(SvO2)的个体偏差(平均差值)和精密度(差值的标准差)值是否可用于预测联合双血氧测定变量(SaO2 - SvO2)的偏差和精密度值。

方法

我们在来自55例患者的238个数据集中,通过脉搏血氧测定法和动脉血气共血氧测定法同时测量SaO2,并通过光纤反射血氧测定法肺动脉导管和静脉血气共血氧测定法测量SvO2。使用三种不同方法预测(SaO2 - SvO2)差值的标准差[sδ(SaO2 - SvO2)]:简单求和、均方根(RMS)误差和带校正项的RMS误差。我们推导了带校正项的RMS误差方程,因为初步结果表明简单求和法和RMS误差法不能很好地预测sδ(SaO2 - SvO2)。校正项考虑了同时测量SaO2和SvO2时的非独立性。

结果

SaO2、SvO2和(SaO2 - SvO2)测量方法观察到的总体偏差分别为0.17、 - 1.76和1.94。(SaO2 - SvO2)测量方法观察到的总体sδ(SaO2 - SvO2)为5.12。简单求和法高估实际sδ(SaO2 - SvO2)达38%,RMS误差法与实际sδ(SaO2 - SvO2)相差3%,带校正项的RMS误差法与实际sδ(SaO2 - SvO2)相符。

结论

(SaO2 - SvO2)测量方法的偏差简单来说就是SaO2测量方法的偏差减去SvO2测量方法的偏差。sδ(SaO2 - SvO2)最好通过推导的带校正项的RMS误差方程来预测。相同的原理和方程也适用于其他将两个具有相同维度的变量组合成一个变量的情况,如(动脉血二氧化碳分压 - 呼气末二氧化碳分压)梯度和灌注压梯度。尽管RMS误差方程预测的sδ(SaO2 - SvO2)与推导的带校正项的RMS误差方程之间的差异很小,但对于其他联合变量,这种差异可能很显著。

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