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1 Departments of Anesthesiology
and Medicine, Severe anemia is
associated with remarkable stability of pulmonary gas exchange (S. Deem, M. K. Alberts, M. J. Bishop, A. Bidani, and E. R. Swenson.
J. Appl. Physiol. 83: 240-246,
1997), although the factors that contribute to this stability have not been studied in detail. In the present study, 10 Flemish Giant rabbits
were anesthetized, paralyzed, and mechanically ventilated at a fixed
minute ventilation. Serial hemodilution was performed in five rabbits
by simultaneous withdrawal of blood and infusion of an equal volume of
6% hetastarch; five rabbits were followed over a comparable time.
Ventilation-perfusion
(
anemia; oxygen; carbon dioxide; rabbits
SEVERE ANEMIA is associated with remarkable stability
of pulmonary gas exchange and transport, despite a fall in the carrying capacity of blood for O2 and
CO2. Several factors contribute to this stability, including an increased cardiac output
( Previous studies in this area have suggested that the gas-exchange
efficiency of the normal lung may be improved with acute hemodilution,
as evidenced by higher arterial PO2
(PaO2) and lower alveolar-arterial
PO2 difference
[(A-a)PO2] (although this finding is by no means consistently observed;
see Table 1). In the presence of venous admixture,
anemia has been postulated to result in either an increase (50) or a
decrease (57) in PaO2, depending on the
effect on mixed venous PO2 (
ABSTRACT
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ABSTRACT
INTRODUCTION
METHODS
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DISCUSSION
REFERENCES
A/
)
relationships were studied by using the multiple inert-gas-elimination
technique, and pulmonary blood flow distribution was assessed by using
fluorescent microspheres. Expired nitric oxide (NO) was measured by
chemiluminescence. Hemodilution resulted in a linear fall in hematocrit
over time, from 30 ± 1.6 to 11 ± 1%. Anemia was associated
with an increase in arterial PO2 in
comparison with controls (P < 0.01 between groups). The improvement in
O2 exchange was associated with
reduced
A/
heterogeneity, a reduction in the fractal dimension of pulmonary blood
flow (P = 0.04), and a relative
increase in the spatial correlation of pulmonary blood flow
(P = 0.04). Expired NO increased with
anemia, whereas it remained stable in control animals
(P < 0.0001 between groups). Anemia
results in improved gas exchange in the normal lung as a
result of an improvement in overall
A/
matching. In turn, this may be a result of favorable changes in
pulmonary blood flow distribution, as assessed by the fractal dimension
and spatial correlation of blood flow and as a result of increased NO availability.
INTRODUCTION
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
) and increased
O2 extraction, the latter
contributing also to greater CO2
transport by the Haldane effect (11).
). Because anemia results in
a fall in blood viscosity, a secondary increase in ,
and changes in microcirculatory blood flow, acute hemodilution may also
result in reduced heterogeneity of pulmonary blood flow and an improvement in ventilation-perfusion
(A/)
distributions (40, 66). Because gas exchange,
A/
heterogeneity, and pulmonary blood flow distribution have not been
systematically studied, we explored these factors in a rabbit model of
acute normovolemic hemodilution.
Table 1.
Studies reporting PaO2 with acute
variations in Hct
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Ten adult Flemish Giant rabbits, weighing ~5 kg each, were randomized
to either control (n = 5) or
hemodilution (n = 5) groups. After placement of an ear vein catheter, animals were anesthetized with
intravenous ketamine and xylazine. A tracheotomy was performed, and the
animals were mechanically ventilated (Siemens Servo 900B, Siemens
Elema, Solna, Sweden) in the supine position using room air, a tidal
volume of ~12 ml/kg, and a frequency of ~20 breaths/min. Pancuronium (0.2 mg/kg) was administered to allow control of minute ventilation
(E), and
infusions of ketamine and xylazine and pancuronium for maintenance
of anesthesia and paralysis were begun. A carotid arterial line, a
jugular venous line, and a femoral venous line were surgically placed.
The jugular venous line was advanced into the right ventricle for
monitoring of right ventricular pressure and sampling of mixed venous
blood gases. Heparin (200 units/kg) was admininstered intravenously to
prevent thrombosis of the intravascular lines. A peripheral intravenous
infusion of inert gases (see below) for determination of
A/
relationships, using the multiple inert-gas-elimination technique
(MIGET), was begun (34, 62). Arterial blood pressure,
right ventricular pressure, heart rate, and airway pressures were
acquired by using a Spacelabs 511 monitor (Hillsboro, OR) and recorded
by using an analog-to-digital converter, data-acquisition software
(Strawberry Tree, Sunnyvale, CA), and a personal computer
(Apple Macintosh, Cupertino, CA).
E was
adjusted to achieve an arterial PCO2 of 30-35 Torr and fixed for the remainder of the experiment.
Twenty to thirty minutes after initiation of the inert-gas infusion, baseline measurements and samples were taken. These included arterial and mixed venous blood gases; hematocrit (Hct); arterial lactate; mixed expired PO2, PCO2, and nitric oxide (NO); and the hemodynamic data and airway pressures mentioned above. Fluorescent microspheres were injected intravenously immediately after withdrawal of MIGET samples for later determination of pulmonary blood flow distribution.
After baseline measurements were taken, animals in the hemodilution group underwent three serial isovolemic hemodilutions, with repeat measurements and microsphere administration ~30 min after completion of each hemodilution (1-h intervals). Hemodilution was performed by simultaneous withdrawal of blood and infusion of 6% hydroxyethyl starch at equal volumes, with exchanges ranging between 50 and 80 ml. Control animals were observed over time, with serial measurements and microsphere injections at 1-h intervals. At the conclusion of the experiment, animals were killed with a combination of an overdose of ketamine and exsanguination.
Mixed venous and arterial blood gases and mixed expired
CO2 and
O2 were measured by using an IL
1620 blood-gas machine (Instrumentation Laboratory, Lexington, MA).
Venous and arterial O2 contents
were measured by using an IL 482 CO-oximeter (Instrumentation
Laboratory). Mixed expired NO was measured continuously by using
chemiluminescence (Sievers Instruments, Boulder, CO), with gas sampling
from a 50-ml mixing chamber at a rate of 120 ml/min. Hct was measured
by centrifugation of duplicate samples. Expired
E was
measured at the conclusion of the experiments by using a sidestream
spirometer (Datex Medical Instruments, Tewksbury, MA).
Blood samples for analysis of serum lactate were spun in a
microcentrifuge at 12,000 rpm for 20 s. One milliliter of plasma was
drawn off and frozen at 
4°C for later analysis. Lactate
levels were assayed by using a YSI 1500 Sport lactate analyzer (Yellow Springs Intruments, Yellow Springs, OH).
Calculations.
O2 consumption
(O2) and
CO2 production
(CO2) were
calculated from the volumes and concentrations of inspired and expired
gases (by using appropriate temperature and humidity corrections) and
normalized for body weight. Similarly, NO output was calculated from
the corrected expired
E and the
concentration of NO in the expired gas. The respiratory quotient was
calculated as the ratio of
CO2/O2.
was calculated with the Fick equation using O2 and blood
O2 contents. The fraction of
physiological dead space
(VDS/VT Bohr)
was calculated by using the Enghoff modification of the Bohr equation
and reported as a percentage. O2
extraction ratio was calculated as the ratio of arteriovenous
O2 content to arterial
O2 content and reported as a
fraction. Alveolar PO2, used to
calculate the
(A-a)PO2,
was calculated by using the alveolar gas equation.
Inert-gas analysis. Six inert gases (ethane, halothane, sulfurhexafluoride, cyclopropane, diethyl ether, and acetone) were dissolved in 5% dextrose solution and infused continuously at 0.7 ml/min. Duplicate arterial and venous blood samples (1 ml) and mixed expired gas samples were obtained at each measurement point; blood and gas samples were drawn simultaneously over ~30 s, with a total time for duplicate samples of ~2 min. Expired gas samples were stored at 40°C before analysis to avoid water condensation and loss of soluble gases. Concentrations of inert gases were measured on a gas chromatograph (Varian 3300, Walnut Creek, CA) equipped with a flame-ionization detector and electron-capture detector. The gas-extraction method of Wagner and associates (62, 63) was used to determine inert-gas tensions in the blood samples.
Fluorescent microsphere analysis. Fluorescent microspheres of four different colors were kept under ultrasonic agitation (Branson 1200, Branson Cleaning Equipment, Shelton, CT) until they were drawn up into a syringe immediately before injection. Each injection contained ~3.3 million microspheres of one color in 1 ml, which was calculated to give sufficient resolution based on earlier published work (1, 4, 22).
After euthanasia at the conclusion of the experiment, a median sternotomy was performed, the pulmonary artery cannulated, and the left ventricle opened. The lungs were flushed with 37°C saline containing 2% dextran for 5 min at 150 ml/min. The lungs were then dissected out of the chest, the heart and extraneous tissue were removed, and the lungs were suspended and reinflated at 20 cmH2O for 2 days to dry. The dried lungs were encased in blocks of foam sealant and sliced perpendicular to the cranial-caudal axis every 5 mm. The lung slices were placed in a Plexiglas jig with a grid of 6-mm holes placed 1 cm on-center. A core of lung tissue was removed from each hole that fell over lung, and the piece was given x, y, and z coordinates. The core pieces (~200 per lung) were weighed, coded for any airway or residual blood content, and placed in numbered vials. The vials were filled with 1 ml of 2-ethoxyethyl acetate to dissolve the microspheres over 24 h, and the solvent was transfered to cuvettes and read for fluorescence (Perkin-Elmer LS50B, Perkin-Elmer, Norwalk, CT) by using emission and excitation wavelengths determined with standards containing all four colors. The fluorescence was converted to weight-normalized relative blood flow by dividing the result by the weight of the individual piece and the average fluorescence of the specific color for all pieces.
Data analysis. All data are presented as means ± SE at baseline and at the three subsequent measurement time points (T1-3). Physiological data were analyzed by using Student's t-test to detect differences between groups at baseline and by repeated-measures multivariate ANOVA to detect differences between groups over time, by using the software package StatView (Abacus Concepts, Berkely, CA). A P value <0.05 was accepted as statistically significant.
MIGET analysis was performed on five control and four anemic rabbits.
Inert-gas exchange was assessed by changes in the ventilation and
perfusion distributions predicted by the 50-compartment model of Wagner
et al. (62, 63). Inert-gas shunt
(QS/QT)
and inert-gas dead space
(VDS/VT miget),
and log SDs of the perfusion and ventilation distributions were
calculated from the 50-compartment model. Global A/
heterogeneity was also assessed by the dispersion index (Disp R*-E*),
derived from the retention (R) and excretion (E) data and corrected for
dead space (34). Data were averaged from the duplicate samples and are
presented as means ± SE for each group. If the sums of squares for
an individual data set were >5.0, these data were omitted from the
final analysis. This resulted in elimination of only one data set.
Differences between groups at baseline were tested by using Student's
t-test, and differences over time or
with hemodilution were tested by using repeated-measures ANOVA.
Disp R*-E* was significantly different between groups at baseline (see RESULTS). To statistically control for this difference, the baseline value was subtracted from values at T3 for both groups (T3-B). A multiple-regression model was then created, which utilized baseline Disp R*-E*Group (a dicotomous indicator variable) and the interaction product of Group and baseline Disp R*-E* (Group_BDisp) as independent variables and T3-B as the dependent variable. The significance of the difference between groups in the change in Disp R*-E* was determined by examining the coefficient and P value for the interaction term Group_BDisp.
Fluorescent microsphere analysis was performed on all rabbits.
Heterogeneity of pulmonary blood flow was characterized by calculating
the coefficient of variation (CV) of weight-normalized relative blood
flow (CVQ) at each measurement
point for each individual rabbit. Microsphere data were also analyzed
by using simple linear regression models for flow in relation to linear
spatial dimensions X (transverse,
right to left), Y (coronal, ventral to
dorsal), Z (saggital, cranial to
caudal), and Dh
{distance from the hilum, expressed as
[(x xh)2 + (y yh)2 + (z zh)2]0.5,
where xh,
yh, and
zh are the
coordinates of the hilum of each lung (left or right)} to
characterize the distribution of pulmonary blood flow across the lung
(1, 35). In a modification of previously described methods, we analyzed
blood flow in the transverse, i.e.,
X-axis, in relation to the orientation
of the individual lungs. Thus, rather than characterizing flow in terms
of right to left across both lungs, we characterized flow from lateral to medial for each lung and pooled these data. To detect changes in
regional blood flow between groups over time, the individual regression
slopes for the above spatial dimensions were compared by using
repeated-measures ANOVA. Baseline differences were determined by using
an unpaired Student's t-test. Data
for spatial dimensions are presented as means ± SE for each group.
Pulmonary blood flow distribution was tested for fractal structure by
examining the CV of blood flow to individual pieces, using a range of
piece sizes (25). By combining neighboring pieces into a conglomerate
piece of a given size (based on multiples of the initial piece size),
the CV of blood flow could be calculated as if the lung had been
divided into larger pieces. Conglomerate piece sizes of 2, 3, 4, 6, 8, 12, 16, 24, 32, 48, and 64 were constructed as follows: a central piece
was chosen at random from all available pieces and then neighboring
pieces were chosen until the desired conglomerate size was reached.
Individual pieces assigned to a conglomerate were then flagged as
unavailable. The process was repeated, choosing another central piece
at random from the remaining available pieces. If a conglomerate could
not be constructed because of unavailability of neighboring pieces, the
central piece was abandoned and another chosen. This was repeated until
the lung was divided into as many conglomerate pieces as possible. Conglomerates were restricted to lie entirely within the left or right
lung but were not restricted to be entirely within lobes. For
conglomerate pieces, the CV will vary randomly, depending on which
individual lung pieces were assigned to which conglomerates. Therefore,
we repeated the algorithm for dividing the lung into larger
conglomerate pieces. For conglomerates of size
n, we repeated the process
times (rounding up to the next
integer value for noninteger square roots). Thus, for conglomerates of
size 64, we repeated the algorithm eight times, obtaining eight
CVs. We used the mean of the logarithm of the eight CVs for regression
modeling [to obtain fractal dimension (D)], used the SD of the
logarithm of the eight CVs for plotting error bars, and used the total
number of conglomerate pieces for all eight repetitions as the
regression weight at piece size 64. Log(CV) was plotted against
log(piece size), and a regression line was obtained by using weighted
regression analysis. The fractal dimension
D was calculated as (1 slope),
where slope was obtained from the regression line fitted to the log(CV)
vs. log(piece-size) data. A test for linear trend in
D over time was done by using weighted-regression ANOVA.
Further characterization of temporal flow patterns and their spatial location within the lung was carried out by using cluster analysis (24). The residual temporal flow for individual lung pieces was calculated as the relative flow to each piece at a given time, minus the mean of the four weight-normalized relative flows for that piece (times 0, 1, 2, and 3). Cluster dendrograms, time-series plots, and three-dimensional rotating plots of the spatial location of individual lung pieces were examined to identify distinct flow pattern groups. Distinct flow pattern clusters were chosen by using the automatic algorithm, as discussed in the APPENDIX of Glenny et al. (24). Weight-normalized relative flow values from all possible neighboring piece pairs within the lung were obtained, and a correlation coefficient was calculated by using the Pearson product-moment correlation. For each rabbit, scatter plots of microsphere counts for each piece at time i vs. time j were examined, and correlation was determined. A randomization test was then performed to compare the anemic rabbit and control rabbit correlations.
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Baseline physiological variables were similar between groups, although
venous PCO2 was significantly
different, possibly as a result of a slightly lower
CO2 and higher
in anemic animals (Table
2). The difference in arterial
PCO2 between groups was of borderline
statistical significance (P = 0.05). Serial hemodilution resulted in a linear fall in Hct from 30 ± 1.6 to 11 ± 1% (Table 2). Hct did not change significantly in the
control group (P < 0.0001 for
difference between groups over time). Mean arterial pressure and right
ventricular pressure did not differ between groups or change with time
or hemodilution, despite an ~50% increase in
with hemodilution
(P < 0.05 between groups over time).
Arterial pH fell insignificantly in both groups, whereas arterial
lactate increased slightly (Table 2).
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Neither arterial nor venous PCO2
changed with hemodilution (Table 2); however,
PaO2 (Fig.
1) and
(A-a)PO2 (Table 2) improved with hemodilution in comparison with the control group. This improvement occurred despite a fall in the
with hemodilution (Fig. 1).
VD/VT Bohr,
CO2, and
O2 did not change
significantly over time or with hemodilution (Table 2). As expected
from the above observations, respiratorty quotient did not
change with hemodilution or time (Table 2).
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Expired NO did not differ significantly between groups at baseline, but
it progressively increased in the anemic group while remaining stable
in the control group (P < 0.0001 between groups over time) (Fig. 2).
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A/
distributions (MIGET).
Inert-gas measurements are shown in Table
3.
QS/QT
was very low in both groups, and, although it was higher in anemic than in control animals throughout the experiment, the differences were not
statistically significant.
QS/QT
remained stable and low over time and/or hemodilution. Disp R*-E* was
significantly higher in anemic animals at baseline
(P < 0.05). Disp R*-E* fell with
each hemodilution while increasing slightly in control animals over
time. The difference in groups over time was highly significant (P < 0.01) and remained significant
after it was controlled for differences in groups at baseline
(P < 0.05) (see
METHODS).
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), did not differ significantly between groups at baseline but
increased with hemodilution while falling slightly in the control group
(P = 0.04 between groups over time) (Fig. 6).
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In agreement with previous work from our laboratory (11), the present
study shows that CO2 elimination
and CO2 remain remarkably
stable in anesthetized rabbits despite severe hemodilution. Of
interest, however, is the finding that arterial blood
O2 tension increases with severe
anemia, particularly in comparison with control animals followed over
time. This mild improvement in PaO2 and
(A-a)PO2
occurs in association with improvements in global indexes of
A/
heterogeneity (Disp R*-E*), a reduction in the fractal dimension of
blood flow D, increased spatial
correlation of blood flow , and an increase in expired NO.
Anemia and PaO2:
theoretical considerations. There are several potential
reasons that anemia may affect arterial oxygenation. These include the
influences of changes in ,
effective blood O2 solubility, , blood viscosity, capillary transit time, and
A/ heterogeneity.
Local changes which affect alveolar-arterial equilibration of
O2 can be described by the
"equilibration coefficient"
D/(Q · 
), whereby a high
D/(Q · ) value is associated with a high degree of
equilibration (55). D represents the diffusive conductance of the
alveolar membrane and is unlikely to be affected by anemia. Q
represents pulmonary capillary blood flow, which increases during anemia, with the potential effect of reducing alveolar-arterial gas
equilibration. However, the modest changes with
anemia (50% with severe hemodilution) and the ameliorating effect of capillary recruitment are likely to prevent significant transit time
shortening (56). represents the capacitance of the gas in blood and
is equal to the slope of the blood binding curve. The slope of the
oxyhemoglobin dissociation curve is reduced in anemia (5, 52),
predicting a higher degree of gas equilibration. Thus, at the
alveolar-capillary level, anemia likely results in either no change or
in slightly improved gas equilibration, compared with the nonanemic state.
More globally, in the presence of venous admixture, this effect is
moderated by the greater saturation range Hb undergoes during anemia
and the "flattening" of the oxyhemoglobin dissociation curve at
high PO2 ranges. Indeed, in the
presence of venous admixture, the flattened oxyhemoglobin curve and
reduced may result in an
increased (A-a)PO2
and a reduced PaO2 (52). In the presence
of a fixed intrapulmonary shunt, if
(and mixed venous
O2 saturation) were
to remain constant during anemia, PaO2
would actually increase as anemia progressed, as illustrated by the
extreme example of calculating PaO2 by
using the shunt equation in the presence and absence of Hb (50).
Other global factors that might be expected
to improve gas exchange in anemia include reduced
A/
heterogeneity due to increased , reduced blood
viscosity, and changes in red cell-dependent vasoactive mediators.
These effects are discussed in more detail below.
Anemia and
PaO2:
studies. Over 45 years ago, Ryan and Hickam (57) found
that a group of anemic patients without obvious lung disease had lower
PaO2 and higher (A-a)PO2
than a group of nonanemic controls. They attributed the relative
hypoxemia seen with anemia to the effect of venous admixture and a
likely reduction in the . However, this study was confounded by the presence of both acute and
chronic anemia and the inability to control for potential cardiovascular and/or pulmonary disease in the study group.
Experimentally, the relationship between anemia and PaO2 is not well defined. A multitude of studies have examined the cardiopulmonary effects of hemodilution or blood transfusion in the absence of known lung disease. A thorough survey of the studies that reported blood-gas data reveals 11 that suggest an inverse relationship between PaO2 and Hct, five that suggest a direct relationship between PaO2 and Hct, and 11 that suggest either no or an inconsistent effect of Hct on PaO2 (see Table 1 for Ref. listing). However, only three of these studies (30, 48, 51) included concurrent controls for the effects of time and/or anesthesia, and none engaged in a systematic analysis of the effects of Hct on PaO2.
The effect of anemia on arterial oxygenation in the presence of lung pathology is also ill defined. In rabbits with left lung atelectasis, isovolemic hemodilution resulted in a relative increase in intrapulmonary shunt and a lower PaO2 than in a control group followed over time (13). Earlier, Bishop and Cheney (3) found no change in shunt after isovolemic hemodilution in dogs with oleic acid-induced lung injury; however, that study also suffered from the lack of a control group. Studies of critically ill humans suggest a deleterious effect of higher Hct on pulmonary O2 exchange, but the potential cardiovascular and inflammatory effects of autologous banked blood transfusion, in addition to the reduced 2,3-diphosphoglycerate in banked blood, make these findings difficult to interpret (20, 38, 58).
The present study shows that isolated and compensated acute anemia is
associated with an increase in PaO2, in
comparison to nonanemic controls. We emphasize the comparison with a
control group, because prolonged time under anesthesia may be
associated with the development of atelectasis and a decrement in
pulmonary gas exchange, thus masking any potential benefits from
anemia. This may be the reason that a previous study (lacking a control group) performed in our laboratory was unable to show an improvement in
PaO2 with hemodilution (11). Another
unique facet of the present study is that
E was fixed
throughout. This may differ from the clinical situation where severe
anemia may result in hyperventilation and respiratory alkalosis, which,
in turn, may have variable and independent effects on
A/
heterogeneity and O2 exchange.
In the present study, the improvement in
PaO2 was seen despite a fall in
with anemia (Fig. 1), the
result of which should be to magnify the effect of venous admixture, as
suggested by Ryan and Hickam (57). In the following sections, we
discuss potential mechanisms by which anemia resulted in improved
O2 exchange in our study.
A/
and pulmonary blood flow distributions and anemia.
The improvement in PaO2 that we observed
was associated with an improvement in overall
A/
matching. The potential mechanisms by which
A/
matching improves with anemia include an increase in pulmonary blood
flow (), a reduction in blood viscosity, and an
interaction between red blood cells and the vasoactive mediator NO.
These factors may lead to a change in pulmonary blood flow distribution
and, theoretically, a change also in ventilation distribution.
A/
distribution and anemia. Because varies with changes in Hct, these flow changes themselves could alter
A/
relationships. In a series of studies from the same laboratory,
however, both moderate decreases (50%) and moderate-to-large increases
(50-300%) in pulmonary blood flow from normal resulted in
increased
A/ heterogeneity in isolated dog lung lobes (16, 17, 53). These changes in
flow were larger than the ~20-50% increase in
in our hemodiluted rabbits. The difference in
results from our study may also be accounted for by the development of
increased arterial pressure with increased perfusion of
the isolated lobar preparation. We found no increase in right
ventricular pressure as an index of arterial pressure in our animals,
and it may be that anemia induces unique effects on
A/
because of its independent effects on blood flow and pressure, through
a reduction in blood viscosity and increased NO availability. Finally,
much larger exercise-induced increases in in humans
are associated with worsening
A/ heterogeneity, but concomittant increases in
E make
comparison with our study difficult (21, 32, 61).
Studies of skeletal muscle suggest that anemia results in more even
distribution of flow (44) and in more even distribution of Hct (43,
45). The latter effect may be a particulary important factor in
improving
A/
matching (40). Increased may reduce pulmonary blood
flow heterogeneity by converting low-flow areas to high-flow areas, as
suggested by Caruthers and Harris (7). However, other investigators
were unable to document significant changes in pulmonary blood flow
distribution in exercising horses (1) and dogs (54) and during
hypovolemic hemorrhage in dogs (46). In a study of acute isovolemic
hemodilution in dogs, Kleen et al. (41) found no change in the global
relative dispersion of pulmonary blood flow in association with a fall
in Hct from 36 to 20%. They did note an increase in dispersion in more
ventral (nondependent) lung zones in these supine animals, an effect
that was reversed with hyperoxia. They did not find a change in either global or isogravitational dispersion with more severe hemodilution (Hct 8%), but this maneuver was accompanied by the simultaneous presence of hyperoxia (inspired O2
fraction 1.0), which may have produced confounding effects on blood
flow distribution.
In the present study, hemodilution resulted in an ~65% fall in Hct
and a 50% increase in from baseline. Despite these
changes, we found no significant changes in most measures of pulmonary blood flow distribution. A slight trend toward reduced overall heterogeneity of blood flow (Fig. 3) was noted. The power of our study
to detect significant changes in these parameters may have been limited
by the small number of rabbits studied or changes in perfusion
heterogeneity on a smaller scale than can be resolved with the present study.
Further analysis revealed that pulmonary blood flow in the rabbit is
consistent with a fractal model, in similarity to other species (7,
25). Fractal structure implies that an object (in this case, the
pulmonary circulation) has a characteristic form that remains constant
over a magnitude of scales (26). The mean fractal dimension
D for the rabbit (1.21 ± 0.05)
compares with that derived for anesthetized dogs (1.09 ± 0.02)
(25), awake dogs (1.13 ± 0.01) (54), and isolated perfused sheep
lungs (1.14 ± 0.09) (7).
Interestingly, we found that D fell
significantly with hemodilution while remaining relatively stable in
control animals (Fig. 5). A fall in D
suggests a trend toward more uniform dispersion of blood flow
(D = 1.0), away from random dispersion
of flow (D = 1.5). This observation is
unique in that other investigators have been unable to document
significant changes in lung D over time or with changes in flow or position (7, 25, 54). Our data are
consistent with those of Cousineau et al. (9), who found that fractal
dimension D decreased in canine hearts
after hemodilution (Hct 37-18%).
The fractal nature of pulmonary blood flow suggests that structural
characteristics of the lung are predominant in determining blood flow
distribution. However, our observation that anemia results in changes
in D suggests that local and/or
metabolic factors, such as reduced viscosity or increased NO, may
result in active redistribution of blood flow in the lung. The finding
that spatial correlation increases with anemia (Fig. 6) is
consistent with the observed changes in
D. The implications of these
observations in terms of gas-exchange efficiency are unclear.
NO and anemia. Expired NO increased at
each level of hemodilution while remaining stable in control animals
(Fig. 2). In a previous study (12), we made a similar observation in an
isolated rabbit lung model and concluded that the increased NO
associated with lower Hct was responsible for inhibition of hypoxic
pulmonary vasoconstriction. Although the source of expired NO (airway
vs. endothelial) is controversial (14), whatever its origin, expired NO
levels correlate with relative responsiveness of the pulmonary vascular
tree (12). Increased expired NO seen with anemia could potentially
result for two reasons: 1) increased
flow-mediated endothelial production of NO (due to increased
) and 2) decreased scavanging of NO by red blood cell-Hb. In either case,
the presence of increased NO at the vascular level would likely lead to
vasodilation, decreased hypoxic pulmonary vasoconstriction, and a
potential redistribution of pulmonary blood flow. It may be by this
mechanism that the fractal dimension D
was observed to decrease with anemia. Increased expired NO may also
alter the airway tone, leading to a redistribution of ventilation.
Further work is necessary to clarify these issues.
Conclusions. We have shown that acute
normovolemic hemodilution in healthy rabbits results in an improvement
in PaO2 in comparison with nonanemic
controls. This improvement in oxygenation appears to be mediated by
reduced
A/
heterogeneity, which may, in turn, be related to increased uniformity
of pulmonary blood flow, particularly as assessed by the fractal
dimension D. The potential mechanisms
by which anemia results in improvements in
A/
matching include an increase in pulmonary perfusion, a reduction in
blood viscosity, and/or an increase in concentration of the vaso-
and bronchodilator substance NO.
| |
ACKNOWLEDGEMENTS |
|---|
The authors thank Dr. Robb W. Glenny for reviewing the manuscript.
| |
FOOTNOTES |
|---|
This work was supported by grants from the American Heart Association, Washington Affiliate, and by National Heart, Lung, and Blood Institute Grants HL-03796-01 and HL-45571.
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. §1734 solely to indicate this fact.
Address for reprint requests and other correspondence: S. Deem, Dept. of Anesthesiology, Box 359724, Harborview Medical Center, 325 Ninth Ave., Seattle, WA 98104-2499 (E-mail: sdeem{at}u.washington.edu).
Received 5 June 1998; accepted in final form 5 March 1999.
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REFERENCES |
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TOP
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