PubMed · 2723708
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M K Sykes. 1989. Pulse oximetry: a "which" hunt?. https://doi.org/10.1007/bf01617876
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OBJECTIVE: The objectives of our study were (1) to compare mixed venous saturations calculated by a blood gas machine with those measured directly by a co-oximeter; and (2) to compare the sensitivities and specificities of VO2s derived from these values. METHODS: Charts were retrospectively reviewed of all MICU patients [n = 16] between December 1, 1991 and January 31, 1992, who required pulmonary artery catheters for their usual care and who had hemoglobin saturations of mixed venous blood concurrently measured by both a co-oximeter (Co-Ox Model 482, Instrumentation Lab, Lexington, MA) and a blood gas analyzer (Nova Biomedical StatLab5, Waltham, MA) which uses a variant of the Severinghaus equation to calculate SVO2 from PVO2). Data used at the time of each SVO2 measurement to calculate oxygen consumption (VO2) further was collected. RESULTS: Available for analysis were 118 mixed venous blood samples. Although the SVO2 values had a correlation coefficient of 0.807 (95% confidence interval [CI] 0.736 to 0.861, Fisher's z-transform), when VO2s were calculated, the blood gas analyzer calculated saturations had a sensitivity of only 58.3% and a specificity of 89%, when compared with those calculated using the saturations measured by the co-oximeter. Attempts to mathematically improve upon the Severinghaus equation and upon an additional four regression equations used by other blood gas analyzers resulted in universally worse sensitivity. CONCLUSION: If SVO2s calculated by a blood gas machine--rather than those co-oximetrically measured--are used to calculate VO2s, 42% of patients with low O2s will be misclassified as normal and 11% of normals will be misclassified as low. This total error appears to be the result of measurement error by the PO2 electrode of the blood gas analyzer and shifts of the oxyhemoglobin dissociation curve, which are not accounted for in the equation that is used to calculate saturation from measured PO2. We were not able to improve mathematically the sensitivity of any of the available regression equations used by blood gas analyzers to calculate SVO2 from PVO2. Therefore, it remains necessary to use co-oximetrically measured saturations when calculating VO2.
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.
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