Vol. 94, Issue 2, 561-566, February 2003
Porcine-specific hemoglobin saturation measurements
Richard
Serianni1,
Jed
Barash1,
Timothy
Bentley2,
Pushpa
Sharma1,
John L.
Fontana1,
Darin
Via1,
Jochen
Duhm3,
Rolf
Bunger4, and
Paul D.
Mongan1
Departments of 1 Anesthesiology and
4 Anatomy, Physiology and Genetics, Uniformed
Services University of the Health Sciences, Bethesda, Maryland 20814;
2 Walter Reed Army Institute of Research,
Washington, District of Columbia 20307; and
3 Department of Physiology, University of Munich,
Munich, Germany 80539
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ABSTRACT |
The
determination of O2 consumption by using arteriovenous
O2 content differences is dependent on accurate
oxyhemoglobin saturation measurements. Because swine are a common
experimental species, we describe the validation of CO-oximeter for
porcine-specific oxyhemoglobin saturation. After developing a nonlinear
mathematical model of the porcine oxyhemoglobin saturation curve, we
made 366 porcine oxyhemoglobin saturation determinations with a
calibrated blood-gas analyzer and a porcine-specific CO-oximeter. There
was a high degree of correlation with minimal variability
(r2 = 0.99, SE of the estimate = 5.2%) between the mathematical model and the porcine-specific
CO-oximeter measurements. Bland-Altman comparison showed that the
CO-oximeter measurements were biased slightly lower (
0.4 vol%), and
the limits of agreement (±2 SD) were 0.7 and 1.5 vol%. This is in
contrast to a 10-20 vol% error if human-specific methods were
used. The results show excellent agreement between the nonlinear model
and CO-oximeter for porcine-specific oxyhemoglobin saturation
measurements. In contrast, comparison of the porcine-specific
oxyhemoglobin saturations with saturations obtained by using human
methods highlights the necessity of species-specific measurement methodology.
CO-oximetry; oxyhemoglobin; mathematical modeling
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INTRODUCTION |
EXPERIMENTAL WORK IN
HEMODILUTION, systemic hypoxia, hemorrhage, and
ischemia-reperfusion routinely produces low levels of oxygenation and extremely low hemoglobin saturations. To obtain accurate data on global and regional O2 delivery and
consumption during these conditions, the ability to measure or
calculate species-specific oxyhemoglobin (HbO2) saturation
is required. Because of the known differences between human hemoglobin
and that of other animal species used for scientific study, companies
have developed COoximeter coefficient sets specific for some
laboratory animals. As with other mammals, porcine hemoglobin has a
significant sequence difference from human hemoglobin (5-7,
19). These sequence differences alter the functional properties
of hemoglobin and change the electrostatic interactions that modulate
the O2 affinity (24). Subsequently, there is a
difference in the HbO2 saturation characteristics of porcine and human blood as demonstrated by the decreased O2
affinity of porcine hemoglobin and the resulting increased 50%
saturation with molecular oxygen (P50) (2, 4,
11, 15, 16, 22, 25). As with dogs and rats, this hemoglobin
sequence difference results in differences in absorbance coefficients
for the hemoglobin species at the specific CO-oximeter wavelengths.
Thus relying on a human or other animal coefficient sets for the
determination of HbO2 saturation will result in data that
are not accurate. Although species-specific CO-oximeters are available
for humans, dogs, and rats, the validation of an accurate
porcine-specific CO-oximeter for laboratory use is currently lacking.
To resolve this deficiency, we compiled laboratory hemoglobin
saturation data that had previously only been used in classic Hill
plots to graphically estimate the P50 of porcine hemoglobin
(10, 15). These data were used to generate a descriptive
mathematical model of the complete porcine HbO2
dissociation curve. In addition, using fresh porcine blood samples,
Instrumentation Laboratories (IL) independently generated a
porcine-specific coefficient set for direct measurement of
HbO2 saturation using the IL 682 CO-oximeter. Subsequently,
using fresh porcine blood obtained from instrumented anesthetized
swine, we determined the HbO2 saturation determined by
using the porcine-specific CO-oximeter and the HbO2
saturation calculated by using the porcine mathematical model. The
agreement of these independent methods of porcine HbO2
saturation was compared with the HbO2 saturation determined
by using a human-specific HbO2 saturation methods. These
studies highlight the potential for significant systematic error when
incorrect measurement methodologies are applied to different species.
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MATERIALS AND METHODS |
Mathematical modeling of the porcine and human HbO2
dissociation curve.
Porcine HbO2 saturation data generated by polarographic
methods were combined with those generated by spectrophotometric
methods for the generation of a mathematical models describing the full porcine HbO2 saturation curve. We compiled a database with
a total of 213 porcine HbO2 saturation data points from 19 separate experimental series: 141 data points came from young adult
porcine blood with normal 2,3-diphosphoglycerate levels in which
hemoglobin saturation was measured by spectrophotometric methods
(15), and 71 of the HbO2 saturation data
points were generated polarographically (4). Although the
HbO2 saturation data were measured differently, the experimental methods in terms of incubation and equilibration with
O2, PCO2, pH, and temperature
(37°C) were identical. Thus the data were combined to mathematically
model the complete O2 dissociation curve. Furthermore,
there were 34 HbO2 values from 11 experimental series
determined spectrophotometrically and 18 values determined
polarographically from eight experimental series at the critical
hypoxic range (PO2 = 0-25 Torr). Each
of the 19 experimental series was assigned one zero-saturation value at an assumed PO2 = 0. The database also
contained 6 values for PO2 
98 Torr
(4).
Because O2 saturation of hemoglobin as a function of
PO2 is sigmoidal and can be described as a
nonlinear rectangular hyperbola with cooperativity, we used a general
nonlinear rectangular hyperbola mathematical model with an
exponentiated variable to account for the sigmoidal nature of the
Hb-O2 saturation (S) relationship (8). This
model yielded an equation in the following general form
![(%saturation/100) = {(S·P<SUB>O<SUB>2</SUB></SUB><SUP><IT>n</IT></SUP>)/[(S·P<SUB>O<SUB>2</SUB></SUB><SUP><IT>n</IT></SUP>) + &bgr;]}](/content/vol94/issue2/fulltext/561/img001.gif)
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(1)
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Because our goal was only to develop a highly descriptive model
of the porcine HbO2 saturation curve and not to validate the previous work that described the P50 and the molecular
binding sites for O2, we chose to use the simpler form in
Eq. 1, instead of the classic Hill equation in which 
would be exponentiated (n) and would
define the P50. Using the maximum likelihood routines of
Gauss 3.5 and Gaussx 3.7 (Aptech Systems, Kent, WA), we fitted the sigmoidal nonlinear rectangular hyperbola equation to the porcine
data as previously described (14). At the extremes, the
limits of saturation were assumed 0 and 100%. Furthermore, because pH
and temperature can influence HbO2 binding, correction factors were added to the model (12, 21, 23, 24, 26). The
correction for pH (
pH) was based on the Bohr effect where [(logPO2)/pH] = 0.3 and
0.48 for swine and humans, respectively, and pH = (7.4 measured pH) (3, 23). Thus a "pH factor" of
(0.3 · pH or
0.48 · pH) was added to the models to
correct the measured PO2. Temperature
correction in the model was accomplished according to Severinghaus
(23) by using pH = 0.031 (37°C measured
temperature) for human data and Willford and Hill (26) by
using pH = 0.022 (37°C measured temperature) for the
swine data. This temperature correction of pH is subsequently
translated into a change in PO2 by use of the
Bohr effect.
The mathematical model of the human HbO2
dissociation curve was derived from 135 single or mean observations
relating PO2 and hemoglobin saturation in human
blood at 37°C and pH 7.4 (2, 4, 9, 16, 18, 23).
IL 682 CO-oximeter coefficient determination for porcine blood.
Heparinized whole blood was obtained from Yorkshire swine (30-35
kg) and shipped overnight on ice to IL, where it was prepared for the
determination of the porcine coefficient set for the IL 682 CO-oximeter. The animal coefficient set is an inverse 4 × 4 matrix of the relative absorption coefficients for the porcine blood at
the IL 682 measuring wavelengths (535, 585, 594, and 626 nm). In brief,
IL personnel used standard validated laboratory procedures (on file at
IL) to produce and measure porcine blood samples that consisted of
100% HbO2, 100% deoxyhemoglobin, 100% methemoglobin, and
100% carboxyhemoglobin. From these samples, IL determined the
coefficient set for swine, which was subsequently programmed into the
IL 682 CO-oximeter.
Construction of in vitro porcine HbO2 dissociation
curve.
Gas tanks of 100% N2, O2, and CO2
were connected to a Cameron Instruments (CIC) gas-mixing flowmeter that
delivered the water-saturated gases in desired proportions to a CIC
dual equilibrator (Cameron Instruments, Brownsville, TX). Six Yorkshire
swine were used on separate days for these experiments. In preparation,
they were anesthetized with halothane, intubated, and ventilated to
maintain the arterial PCO2 at 40 Torr. After
percutaneous placement of a 20-gauge femoral arterial cannula,
3-ml fresh heparinized blood samples were obtained and immediately
added to each of the spinning chambers of the equilibrator. The
equilibration conditions in the CIC dual equilibrator were targeted at
37.0°C, pH 7.40 (balanced by the addition of NaHCO3 or
HCl), and a PCO2 of 40.0 Torr. The blood
samples were equilibrated over a range of gas flows for N2
and O2 in a stepwise manner to produce
PO2 ranging from 0 to 500 Torr. At each step,
the blood samples were equilibrated for 3-5 min before 1 ml was
withdrawn and analyzed on an IL 682 CO-oximeter programmed with porcine
coefficients and a calibrated IL 1610 blood-gas analyzer. As the
equilibrated samples were consumed from each chamber over 20-30
min, the blood in the equilibrating chamber was replenished with fresh
heparinized blood from the anesthetized swine. After the final
measurements at no O2 flow, complete deoxygenation was
ensured by the addition of 20 mg sodium dithionite. Fresh human blood
samples were used in similar methods to measure HbO2
saturation on an IL 682 programmed with human coefficients at
PO2 levels ranging from 20 to 120 Torr. These measurements were used as a validation data set for the human mathematical modeling.
Statistical analysis.
Data are presented as means ± SD. The linear regression analysis
was used to determine the correlation between the IL 682 porcine
hemoglobin saturation and the mathematical model-predicted porcine
saturations. Agreement between saturation measurements made by the IL
682 CO-oximeter and the porcine HbO2 saturations predicted
by the mathematical model were evaluated by use of Bland-Altman analysis (1, 17). In this analysis, the mean of the two
measurements is plotted against the difference in the measurements. The
limits of agreement of the two techniques is reported as the mean
difference ± 2 standard deviations of the mean difference.
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RESULTS |
Mathematical modeling Hg dissociation curves using data sets.
At pH 7.4, 37°C, the following basic porcine HbO2
dissociation equation was obtained from the porcine data points
(n = 213)
The obtained fit was excellent (r2 = 0.98, SE of the estimate = 7.1%), and there was no significant
autocorrelation detected by use of the Durbin Watson statistic. This
mathematical model with the correction factors provides a highly
descriptive estimate of porcine hemoglobin saturation over the entire
physiological range of PO2 values as well as
those experimental extreme values that occur during hypoxemia,
hemorrhage, and/or resuscitation. From the porcine model, the predicted
P50 was 32.9 Torr. This is consistent with the reported
adult porcine P50 of 3234 Torr (4, 11, 13, 15, 24,
25). In addition, the predicted 99% (P99) and 7.5%
saturation with molecular oxygen (P7.5) (the extremes) were, respectively, 150.8 and 14.4 Torr at 37°C and pH 7.4.
The descriptive modeling of the adult human O2
dissociation curve on the 135 published measurements performed at
37°C and pH 7.4 yielded the following equation
Comparison of the human mathematical model with the validation set
of human Hb saturations (n = 95 saturation
determinations) measured on the IL 682 CO-oximeter programmed with
human coefficients revealed a high linear correlation between both
measurement methods with minimal variability
(r2 = 0.98). The P50 predicted
by the human model for the adult human was 26.1 Torr. This
P50 value was within the range of the values for humans
(2, 12, 23). However, it is appreciably lower than the
P50 of the adult pig obtained from Eq. 2. At the
extremes, the P99 and P7.5 for the adult human
were, respectively, 146.9 and 9.7 Torr. This modeling predicts that,
compared with the porcine O2 dissociation curve, the human
O2 dissociation curve would rise faster at
PO2 > 10 Torr and thus reach a
half-saturation value at a substantially lower
PO2.
PO2 predicted and measured HbO2
saturation data.
We performed 366 separate porcine HbO2 saturation
determinations on the IL 682 CO-oximeter. The temperature maintained in the dual-chamber equilibrator was 37.1 ± 0.1°C. The
PO2 values measured by the IL 1610 ranged from
of 639 to 0 Torr. The measured pH was 7.41 ± 0.03, and
PCO2 was 39.8 ± 0.08 Torr.
Figure 1 compares measured (IL 682 CO-oximeter) HbO2 saturation with the corresponding
calculated hemoglobin saturations from the measured
PO2 (IL 1610) for both porcine and human
mathematical models. At a PO2 > 100 Torr,
the human and porcine HbO2 dissociation curves are
essentially identical. However, as the PO2
declines below 80 Torr, the IL 682 CO-oximeter-measured and the
mathematical model-predicted porcine HbO2 saturations are
noticeably shifted to the right of the predicted human HbO2
saturations. Thus the porcine HbO2 saturation decrease more
rapidly, resulting in a P50 at ~33 Torr compared with the
predicted human P50 of ~26 Torr.
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Fig. 1.
Relationship of the PO2 of fresh
porcine blood determined on the IL 1610 blood-gas analyzer and the
oxyhemoglobin (HbO2) saturation determined by the IL 682 CO-oximeter programmed with porcine-specific coefficients or by
mathematical calculation using both porcine- and human-specific models.
Graphically, the results of the HbO2 saturation determined
by direct measurement and that derived when using the porcine-specific
model are very similar. In contrast, the HbO2 saturation
determined from the PO2 using the
human-specific algorithm shows a left shift and lower 50% saturation
with molecular oxygen than the porcine-specific HbO2
saturation data.
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Figure 2 shows porcine HbO2
saturation measured with the IL 682 CO-oximeter with the
HbO2 saturation calculated from the measured PO2 using the porcine and human model. When
measured porcine HbO2 saturations are compared with
saturations predicted by the porcine mathematical model, there is an
extremely high degree of correlation between the data with minimal
variability (r2 = 0.99, SE of the
estimate = 5.2%). Comparing measured HbO2 saturations with saturations predicted by the mathematical model of the human HbO2 saturation curve revealed a nonlinear pattern of
correlation throughout the range of hemoglobin saturations in which
measured porcine saturations were consistently lower than those
predicted by the human mathematical model.
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Fig. 2.
Close correlation of the measured and mathematically
predicted porcine HbO2 saturation from porcine blood
samples assayed for this paper is shown. However, this linear
correlation is lost when the HbO2 saturation is determined
by using a technique specific for human hemoglobin. SEest, SE of the
estimate.
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Figure 3 compares hemoglobin saturation
differences with the use of porcine HbO2 saturation data
obtained from the IL 682 CO-oximeter and the differences in that data
with saturations predicted from the PO2 by the
mathematical models in a Bland-Altman-style plot. Figure 3 shows that,
over the range of saturation measurements, IL 682 measurements were
biased slightly lower (mean Hg saturation bias = 0.4%), and the
limits of agreement (±2 SD) were 0.7 and 1.5%. In general, this
shows a good agreement of the two methods for determining the
O2 saturation of porcine hemoglobin. In contrast, the
Bland-Altman comparison of the IL 682-measured porcine HbO2 saturation levels with the HbO2 saturation predicted by the
human mathematical model shows an average overestimation of the percent porcine HbO2 saturation by the human HbO2
saturation model of 9.8 ± 6.6. Between HbO2
saturations of 60 and 30, these differences represent a 20-40%
error in the saturation determination. These differences in the
HbO2 saturation are significant because they occur at the
physiologically relevant mixed venous O2 tensions of
40-25 Torr.
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Fig. 3.
Bland-Altman analysis of the IL 682 CO-oximeter porcine
HbO2 saturation data and the HbO2 saturation
data from the mathematical model specific for porcine HbO2
saturation. The IL 682 data is biased slightly lower (0.4 vol%), and
the difference in measurements between a saturation of 0-100% is
<1.5 vol%. In contrast, if the HbO2 saturation of porcine
blood is determined by human-specific methods, the difference could be
as large as 18 vol%. Because the largest differences occur in the
PO2 range of venous blood and the mathematical
determination of O2 content is highly dependent on the
HbO2 saturation, there exists a large potential for error
in venous O2 content and thus global or regional
O2 consumption when human-specific methods are used to
determine the HbO2 saturation of porcine blood.
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DISCUSSION |
The important new information presented in this paper is the
development of a convenient, but solely descriptive, mathematical model
for nonlinear estimation of porcine HbO2 saturation and the
agreement with a porcine-specific CO-oximeter for laboratory determination of fractional HbO2 saturation. We developed
this as a descriptive nonlinear cooperative rectangular hyperbola that describes the saturation curve accurately at both extremely low and
high PO2 as well as in the physiological
PO2 ranges. Because this is an entirely
pragmatic and descriptive approach, the model does not have
implications for the regulation of O2 binding by hemoglobin. However, for the first time, our model describes the entire
saturation curve accurately, both at extremely low and high
PO2 as well as in the middle. This accurate
description and measurement of porcine HbO2 saturation is
important because swine are frequently used for experimental situations
(hemodilution, systemic hypoxia, ischemia-reperfusion, or
resuscitation) that routinely produce extremely low or high blood
oxygenation levels that result in extremely very low or near 100%
hemoglobin saturations. To estimate with acceptable accuracy the
delivery and consumption of O2 under such conditions, a
complete HbO2 dissociation curve and measurement modality
is required. The importance of accurate species-specific measurement
techniques is demonstrated in the differences in the porcine-specific
HbO2 saturation and saturation determined by use of
human-specific methods.
One other purpose of this study was to validate the IL 682 CO-oximeter
for accurate measurement of porcine HbO2 saturation. The
validation of the IL 682 measurements is based on a Bland-Altman statistical method for evaluating differences in measurements obtained
on the same samples by two different measurement techniques (1,
17). This method evaluates the mean difference between the two
methods over the range of interest (estimated bias) and the variability
of the measurements (standard deviation) around the mean difference.
The mean difference ± 2 SD is defined as the "limits of
agreement." If no significant differences in data outcomes are
produced between the two measurements within the range of interest, the
methods can be used interchangeably. Because the existing methods of
measuring porcine HbO2 saturation are extremely time
consuming, we modeled the entire adult human and porcine
O2-dissociation curves on the basis of data compiled from the literature by using published data from Bartels and Harms (4) and both published and unpublished data from Kim and
Duhm (15). This produced nonlinear cooperative
mathematical models that were not based on the original Hill formula
and are, therefore, purely descriptive. The models were nonlinear
rectangular hyperbolas with positive cooperativity that described the
HbO2 saturation for both adult humans and swine with high
fidelity; they were also well defined at
PO2 = 0 Torr and proved to be accurate at physiological extremes, i.e., both at low (<20 Torr) and high (>100
Torr) PO2 levels. We compared the predicted
model data with directly measured values by using CO-oximetry. This
validation produced essentially identical curves over the entire
PO2 range of clinical and experimental
interest. From Fig. 3 there is a close agreement of HbO2
saturation measured with the IL 682 CO-oximeter and the mathematical
model of porcine HbO2 saturation. In addition, the limits
of agreement (±1.1%, 2 SD) between the two methods would not be
expected to cause any appreciable error in the calculation of
O2 content or O2 consumption. Overall, the
measured HbO2 saturation is slightly lower than the
HbO2 saturation predicted by the mathematical model
(0.4% mean bias). However, this difference and the limited variability shown by the limits of agreement are experimentally and
physiologically insignificant.
The main reason for the close agreement of these two different methods
of porcine HbO2 saturation is related to the accuracy of
the primary measurements. The measurements made by the IL 682 CO-oximeter are derived from the porcine-specific coefficient set
stored in memory. This coefficient set is an inverse 4 × 4 matrix
of the relative absorption coefficients at the measuring wavelengths of
the IL 682 CO-oximeter. The IL 682 CO-oximeter uses this coefficient
set and the absorption of the sample at the CO-oximeter wavelengths to
calculate a fractional HbO2 saturation by dividing the
HbO2 saturation by the sum (100%) of the oxy-, deoxy-,
carboxy-, and methemoglobin saturation. The coefficient set is derived
from porcine blood by using standard techniques by IL personnel (data
on file with IL). In brief, the absorption coefficients for oxy-,
deoxy-, carboxy-, and methemoglobin for porcine blood at the set
wavelengths are determined by measuring a sample containing only one
hemoglobin species. The absolute accuracy of the absorption
coefficients for the individual hemoglobin is related to the
assumptions made by IL in the protocols that generate the data for the
calculation of the coefficients for the IL 682 CO-oximeter. Those
protocols use fresh animal blood to generate "pure" hemoglobin
species to determine the absorbance characteristics. However,
pure deoxyhemoglobin is still potentially contaminated by the unknown
small amount of carboxyhemoglobin in the fresh blood sample. The
accuracy of the pure carboxyhemoglobin absorbance at the four
wavelengths is limited by the amount of methemoglobin in the original
sample. Finally, the accuracy of the absorbance characteristics of
100% HbO2 is limited by the small amounts of carboxy- and
methemoglobin in the fresh sample. Before calculation of the
coefficient set, the IL protocols correct the saturation measurements
for the residual levels of carboxy- and methemoglobin. However, the
polarographic and spectrophotometric experiential data used for
modeling accounted only for oxy- and deoxyhemoglobin and do not measure
or modify for contamination by carboxy- and methemoglobin. Although the
small amount of these contaminants inherent in the fresh porcine blood
has a small effect on the overall calculations, it does limit the
absolute accuracy of the CO-oximeter and the original measurements by
Kim and Duhm (15) and Bartels and Harms (4).
Another potential small source of error in the measurement of the
HbO2 saturation in the porcine blood is the use of HCl to
correct the pH to 7.4. Because Cl competes for binding sites with
2,3-bisphosphoglycerate and CO2, it can decrease
HbO2 affinity (20, 21). However, in this
experiment the swine were anesthetized, ventilated, and maintained
normothermic between arterial blood sampling. In addition, because the
pH of the fresh arterial blood from the swine ranged between 7.39 and 7.42, pH correction was infrequent. Thus, although not fully
documented, the impact of changes in the Cl content on the IL 682 measured HbO2 saturation was probably minimal.
The second purpose of this study was to estimate the error incurred, if
human O2 dissociation curves are used in porcine
experiments. There are substantial differences between the human and
the porcine saturation data in the PO2 for
venous blood samples. The magnitude of this difference is illustrated
in the calculation of O2 content for regional or global
O2 consumption. Because the HbO2 saturation is
a major factor in the determination of O2 content
[(1.34 · Hb · HbO2
saturation) + (0.003 · PO2)], the
differences in the HbO2 saturation and thus the
O2 content determined by using the human methodology for
porcine HbO2 saturation can be quite large. On the other
hand, the differences in calculated arterial O2 contact are
small (0.5%) because the porcine HbO2 saturation is
overestimated by the human methodology difference <0.5 vol% at
PO2 levels >100 Torr. However, if the
PO2 of the venous blood is 40 or 30 Torr, i.e.,
in the physiological range, the HbO2 saturation derived from human methods is overestimated by 11.0 and 15.9 vol%,
respectively. This leads to an overestimation of the venous
O2 content in the porcine blood with normal Hb levels (10 g/dl) by 1.5 and 2.1 ml/dl, respectively. In these examples, the
systematic error leads to an underestimation in the arterial-venous
O2 content difference by 30.3 and 27.5%, respectively.
This error is further compounded by the multiplication of the arterial
and venous O2 content difference by the flow rate in the
calculation of either regional or global O2 consumption. In
addition, if the HbO2 saturation measurements are used to
calculate the cardiac output by the Fick method, erroneously high
HbO2 saturation measurements determined for porcine blood by using human-specific methods will result in a 45 and 43%
overestimation in the cardiac output at venous
PO2 levels of 40 or 30 Torr, respectively.
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ACKNOWLEDGEMENTS |
This work was supported in part by the Office of Naval Research,
The Office of Research and Development, Medical Research Service,
Department of Veterans Affairs, and the Walter Reed Army Institute of Research.
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FOOTNOTES |
The opinions or assertions contained herein are the private views of
the authors and are not to be construed as reflecting the views of the
Department of the Army, the Department of Defense, or the Department of
Veterans Affairs.
Address for reprint requests and other correspondence:
P. D. Mongan, Dept. of Anesthesiology, Uniformed Services
Univ. of the Health Sciences, 4301 Jones Bridge Rd., Bethesda, MD 20814 (pmongan{at}usuhs.mil).
The costs of publication of this
article were defrayed in part by the
payment of page charges. The article
must therefore be hereby marked
"advertisement"
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
First published October 18, 2002;10.1152/japplphysiol.00710.2002
Received 31 July 2002; accepted in final form 8 October
2002.
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J APPL PHYSIOL 94(2):561-566
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ABSTRACT
INTRODUCTION
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![(%/100) = (0.13534·P<SUB>O<SUB>2</SUB></SUB>)<SUP>2.62</SUP>/[(0.13534·P<SUB>O<SUB>2</SUB></SUB>)<SUP>2.62</SUP> + 27.4] (<IT>3</IT>)](/content/vol94/issue2/fulltext/561/img003.gif)
