(Circulation. 1999;99:626-632.)
© 1999 American Heart Association, Inc.
Clinical Investigation and Reports |
From the Department of Internal Medicine, Division of Cardiology, Saint Louis University Health Sciences Center, St Louis, Mo (T.L.W., T.J.D., R.G.B., E.A.C., M.J.K.); the Cardiovascular Division, University of Minnesota, Minneapolis (L.W.M.); and the Black Hills Cardiovascular Research Group, Rapid City, SD (J.H.D.).
| Abstract |
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Methods and ResultsOne hundred six posttransplant patients
undergoing cardiac catheterization had measurement of
CFR in at least 3 major epicardial vessels. Patients were divided into
those with minimal angiographic abnormalities (n=37) and those with no
angiographic abnormalities (n=69). The ranges, coefficients of
variation, and univariate and multivariate
regression analyses of CFR were computed to determine the major
clinical factors influencing the degree of variability. The abnormal
angiographic group was older (54±11 versus 47±13 years;
P<0.003), had older hearts (35±11 versus 27±10 years;
P<0.005), and were further posttransplant (1626±1022
versus 931±984 days; P<0.0009). There was no
difference in global CFR between groups (normal, 3.4±0.8 versus
abnormal, 3.4±0.7; P=NS). The coefficient of variation
of CFR was higher for the abnormal group (16.3±8.6% versus
11.0±5.5%; P<0.0006). Univariate and
multivariate predictors of increased variability in CFR
included angiographic abnormalities, patient age, and body mass index.
Both angiographic abnormalities and an elevated CV of CFR were
predictive of a combined end point of death, congestive heart failure,
or subsequent development of
50% coronary
stenosis.
ConclusionsThese data demonstrate that increased variability of CFR is associated with discernible allograft coronary arteriopathy and is predictive of outcome in patients after heart transplantation.
Key Words: blood flow transplantation arteries
| Introduction |
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Allograft vasculopathy is difficult to detect clinically because patients are often asymptomatic secondary to denervation, and the results of noninvasive testing have been disappointing.4
The peculiar features of allograft vasculopathy include its circumferential involvement of the epicardial vessels and extension into the intramyocardial vessels.4 6 Standard coronary angiography is limited because a normal angiogram does not exclude extensive myointimal proliferation, and angiography can provide little information on intramyocardial resistance vessels.7 8 9 10
To assess allograft resistance vessel function, various techniques, including intracoronary Doppler and PET, have been used to measure both resting and hyperemic blood flow.11 12 13 14 15 Coronary flow reserve (CFR), defined as the ratio of hyperemic to resting blood flow, has been used as an index of resistance vessel integrity.
Previous studies have yielded conflicting results regarding the question of whether epicardial and microvascular disease occur concordantly.11 16 17 18 19 These studies have been limited by either presentation of mean flow data or evaluation of a single vascular distribution. Given that epicardial angiographic abnormalities can appear at different rates in different vascular beds, we hypothesized that abnormalities in resistance vessel function would also have a nonuniform time course across various perfusion fields. We further hypothesized that asymmetry of resistance vessel function would manifest as differences in CFR measured in different vascular beds. If the development of epicardial and resistance vessel arteriopathy occurs simultaneously, then variability of CFR should be most evident in patients with angiographic abnormalities. This heterogeneity of microvascular dysfunction may indicate early endothelial dysfunction before the appearance of flow-limiting epicardial stenoses. The purpose of this study was to measure intrapatient flow reserve variability in a posttransplant population and assess its relationship to early manifestations of epicardial disease and other clinical variables.
| Methods |
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All vasoactive medications were withheld for 12 to 24 hours before the study. No patients had been receiving a long-acting ß-blocker. Patients routinely received 2 mg of diazepam and 25 mg of diphenhydramine before catheterization.
Cardiac Catheterization Protocol
Right ventricular endomyocardial
biopsy and right and left heart catheterization with
hemodynamic measurements were performed from the
femoral approach. Right coronary angiography was performed in
standard fashion after 150 to 200 µg of intracoronary
nitroglycerin.
Coronary Flow Velocity Measurements
After completion of the right coronary arteriograms,
heparin 5000 U IV was administered, and an 0.018-in Doppler-tipped
guidewire (FloWire, Cardiometrics, Inc)20 21 was advanced
past the most distal acute marginal branch of the right
coronary artery and positioned proximal to the origin of the
posterior descending artery. Flow velocity measurements were obtained
at baseline and at peak hyperemia after bolus injection of
adenosine 12 to 18 mg IC.21 Bolus injection of
adenosine was used because it produces peak increases in
coronary flow velocity without changes in epicardial vessel
diameter, so that flow velocity changes are accurate surrogates of
total flow changes.22 The CFR was calculated as the
quotient of hyperemic to baseline average peak velocity
(APV).
Left coronary angiography was then performed after administration of nitroglycerin 150 to 200 µg IC. After completion of angiography, the Doppler guidewire was placed in the proximal left anterior descending coronary artery. Baseline and peak hyperemic flow velocities were measured. The protocol was then repeated with the guidewire in the proximal circumflex artery. In patients with left dominant circulation, either the first obtuse marginal, median ramus, or first diagonal artery was also studied, depending on which artery was largest.
Endomyocardial Biopsy Analysis
Five specimens of right ventricular
endomyocardium were obtained at each study. The specimens
were examined by light microscopy and graded according to standard
criteria.23 The biopsy results were assigned a numerical
score (0=0, 1A=1, 1B=1.5, 2=2, 3A=3, 3B=3.5, 4=4).
Left Ventricular Function Analysis
Each patient underwent either gated equilibrium radionuclide
scanning or 2-dimensional echocardiographic assessment
of left ventricular function within 24 hours of
catheterization. For those patients undergoing
echocardiography, 2-dimensional and M-mode
evaluations of wall motion and wall thickness were performed according
to the standards of the American Society of
Echocardiography.24
Radionuclide studies using technetium-labeled red blood cells were obtained in a standard fashion visualizing the heart in 3 projections. After a cine endless-loop display was created, wall motion was assessed with anterior, septal, inferior, apical, and lateral segments classified as normal, hyperkinetic, akinetic, or dyskinetic. All evaluations were performed by observers unaware of catheterization flow results.
Angiographic Data Analysis
Each coronary angiogram was evaluated by 2 independent
observers blinded to the results of the flow data and clinical history.
Angiographic evidence of disease was defined as type A (luminal
irregularities or narrowings in a primary or secondary coronary
vessel) or type B (distal tapering, loss of distal branches, or blunt
occlusion identified on serial studies) as described by Gao et
al.25
Quantitative angiographic evaluation was performed on-line with the Philips DCI-ACA system, with the contrast-filled catheter serving as a reference standard. The dimensions of the nondiseased proximal artery segments and absolute luminal diameter of the coronary artery 5 mm distal to the tip of the Doppler-tipped guidewire were measured.
An off-line evaluation of any stenosed vessel with a type A lesion was performed with a quantitative caliper system (ImageCon Systems, Inc). The normal adjacent segment was used as the reference for measurement of the extent of stenosis. If the vessel had multiple lesions, all lesions were measured by electronic calipers.
Patients were divided into 2 groups: normal, with no angiographic abnormalities, and abnormal, with type A and/or B lesions. No patient had a stenosis >50% diameter narrowing.
Coronary Flow Velocity Data Analysis
Flow velocity data were printed on an integrated video page
printer that provided computer-calculated variables of
intracoronary flow velocity. The APV was used in the
calculation of CFR. Flow data were reviewed by 2 physicians (T.L.W.,
T.J.D.) blinded to the angiographic findings to verify satisfactory
computerized tracking of the velocity signal. If the automatic tracking
of the velocity profile was inadequate, both baseline and
hyperemic flow velocity signals were planimetered off-line with
a commercially available digitizing tablet interfaced with a
microcomputer as previously validated.21
Hemodynamic Data
Blood pressure and heart rate were continually monitored and
recorded for each baseline and hyperemic flow velocity
signal measurement. For every patient, the double product was
calculated as heart ratexsystolic pressure.
Analysis of Flow Heterogeneity
Heterogeneity of CFR in an individual patient
was evaluated as follows: A global CFR was calculated as the average
value from the studied vessels. The following measures of intrapatient
variability of CFR were then derived: (1) range: maximum CFR-minimum
CFR; normalized range: range/global CFRx100; and (2) coefficient of
variation (CV): SD of CFR/mean CFRx100 for each patient (Table 1
demonstrates a sample
calculation).
|
An analysis of hemodynamic variability was performed to determine whether the variability in CFR could be due to changes in hemodynamic parameters. Calculations identical to those described above for CFR were made for heart ratexpressure product, mean blood pressure, and heart rate.
Statistical Analysis
Statistical analysis between groups was made with
Student's unpaired t test as indicated. For groups with
nonnormal distributions, a Mann-Whitney U test was
performed. For comparisons of >2 groups, 1-way ANOVA was used. For
groups with nonnormal distributions, the nonparametric
version of a 1-way ANOVA, the Kruskal-Wallace test, was used. For
standard 1-way ANOVA, post hoc testing was done with Tukey's highly
significant difference test. Survival data were analyzed
with a Cox proportional hazards regression model.
Multivariable analysis was performed with a logistic
regression model. For correlations between groups, the
nonparametric correlation coefficient Spearman's
was
used for nonnormal distributions and a Pearson's correlation
coefficient was used for normal distributions. Unless otherwise stated,
all values are presented as mean±SD. Statistical difference
was accepted at a value of P<0.05. The statistical
calculations were made with a commercially available statistical
package (JMP 3.15, SAS Institute).
| Results |
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Hemodynamic and Angiographic Data
Baseline hemodynamics are shown in Table 3
. Both groups had normal ejection
fractions, with the angiographically normal group having a slightly
higher value than the abnormal group (63±7% versus 60±7%;
P=0.03). There were no significant differences in baseline
hemodynamics between groups. In the abnormal group, the
mean diameter stenosis was 23.7±11% (range, 14% to
49%).
|
Coronary Flow Velocity Data
For the entire patient group, the APV at baseline was lower for
the right coronary artery (15.1±5.3 cm/s) than the circumflex
or left anterior descending coronary arteries (Table 4
). The left anterior descending had the
highest and the right coronary artery had the lowest absolute
peak hyperemic APV. Despite differences in absolute flow
velocities, there was no difference in CFR among vessels. There were
also no differences for hemodynamic values at the time
of individual coronary artery flow reserve measurements (Table 5
).
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Coronary Flow Variability
There were no differences in baseline or hyperemic APVs or
global CFR between the normal and abnormal angiographic groups (Table 6
). The range (normal, 0.75±0.46 versus
abnormal, 1.1±0.55; P=0.0008) and the normalized range of
CFR (normal, 21.8±10.9% versus abnormal, 32.2±16.3%;
P=0.0006) were lower in the normal group. The coefficient of
variation of CFR (CV CFR) was also lower in the normal group
(11.0±5.5% versus 16.3±8.6%; P=0.0006). The population
mean for CV CFR was 12.8±7.2%. There was no difference in CV CFR for
patients with type B versus type A angiographic disease (18.5±14%
versus 16±7%, P=NS). The CV CFR was not different whether
3 vessels (12.9±0.8%) or 4 vessels (12.5±1.0%, P=NS)
were studied.
|
To evaluate the effect of variability in absolute velocity, the CVs for resting and peak hyperemic APV were calculated. The CV for resting APV was higher in the angiographically abnormal group (26.2±12.0%) than the normal group (18.0±8.2%; P=0.0006). The CV for hyperemic APV was almost identically higher for the abnormal group (26.7±14.0%) than the normal group (18.2±10.4%; P=0.0019).
To determine whether the differences in CV CFR between the
angiographically normal and abnormal patient groups were due to
hemodynamic factors, the same statistical
analysis was performed on hemodynamics measured
at the time of the coronary flow velocity measurements. There
were no differences in any measures of hemodynamic
variability between the normal and abnormal groups (Table 7
).
|
Left ventricular mass and mass index had inverse relationships with CFR (r=-0.23, P=0.04 and r=-0.29, P=0.017, respectively). Despite this finding, there was no relationship between either left ventricular mass or left ventricular mass index and CV CFR (r=0.008, P=NS and r=0.09, P=NS, respectively).
To assess the effects of time posttransplant, the correlation between CV CFR and both the age of the heart and the time after transplantation was examined. There was no correlation between age of the heart (r=0.14, P=0.1412) or time posttransplantation (r=0.18, P=0.065) and CV CFR.
A logistic regression model to find predictors of increased flow
variability was performed at 2 levels (Table 8
). First, patients above the 75th
percentile were defined as abnormal for CV CFR. By this standard (CV
CFR >16.2%), 4 factors (angiographic abnormality, age, blood
pressure, body mass index, and ischemic cause of heart failure)
had a direct relationship and 2 factors (CV of mean blood pressure and
arterial oxygen saturation) had an inverse relationship. In
a multiple logistic regression model, the factors that remained
significant were angiographic abnormality, arterial oxygen
saturation, CV of mean blood pressure, and body mass index.
|
A second logistic regression was performed using the population mean of
CV CFR±SD as the measure of abnormal variability (ie, CV CFR >20%,
approximating the 90th percentile in this nonnormally distributed
population). By univariate logistic regression,
angiographic abnormality, body mass index, total
cholesterol/HDL ratio, and hemoglobin had a direct
relationship and arterial oxygen saturation had an inverse
relationship. In a multiple logistic regression analysis, only
angiographic abnormality (P=0.043) and arterial
oxygen saturation (P=0.041) were significant (Table 9
).
|
Rejection and CFR
Previous studies have suggested that cellular rejection results in
a diminished CFR.26 In this study, the CFRs of the 39
patients with grade 0 biopsies were not significantly different from
CFRs of rejecting patients (3.5±0.6 versus 3.3±0.8;
P=0.06). Similarly, intrapatient flow reserve variability by
biopsy grade showed no significant relationship. The CV CFR in patients
with grade 0 biopsies was 14±8.4%, versus 12.1±6.3%
(P=0.36) in patients with
1A grade biopsy. There was no
relationship between average biopsy score at 1 month, 6 months, 12
months, or the life of the graft and CV CFR. There was also no
relationship between number of treated rejections at any time point and
CV CFR.
Clinical Events
The patients were followed up for an average of 26±7.3 months. To
evaluate the effects of variability of flow on clinical events, a
composite end point was devised of cardiac death (sudden death,
myocardial infarction, or left ventricular failure),
development of congestive heart failure unrelated to rejection, or
development of a >50% diameter stenosis in a primary
epicardial vessel. A univariate Cox proportional hazards
model found that angiographic abnormalities (risk ratio, 2.0; 95% CI,
1.24 to 3.4; P=0.0040), CV CFR (risk ratio per decile
percent, 2.4; 95% CI, 1.4 to 4.0; P=0.0036), CV of resting
flow (risk ratio per decile percent, 2.2; 95% CI, 1.4 to 3.4;
P=0.0011), and variability of hyperemic flow
velocity (risk ratio per decile percent, 1.6; CI, 1.04 to 2.3;
P=0.0314) were all significant in determining event rates. A
multivariate Cox proportional hazards model found that
only CV CFR (risk ratio, 2.1; CI, 1.01 to 4.1; P=0.0489) was
significant. Angiographic abnormality (P=0.55) and
variability of hyperemic flow were not significant. There was a
trend toward significance for variability of resting flow
(P=0.06).
| Discussion |
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The initial hypothesis that epicardial angiographic disease would be associated with different microvascular perfusion field responses was supported by these findings. CFR is not uniform across the left ventricular myocardium, and this variation increases in patients with angiographic evidence of disease. Variability in CFR is not due to hemodynamic parameters, because the magnitude and direction of hemodynamic variability cannot explain the variability seen in the CFRs within an individual patient.
Regional variability for resting and hyperemic APV is to be expected, given the relative differences in perfusion field size supplied by the different interrogated epicardial vessels. The increase over baseline variability found in the angiographically abnormal group suggests that endothelial dysfunction may play a role in this group. Basal blood flow autoregulation is strongly influenced by local release of endothelium-derived mediators such as endothelium-derived relaxing factor,27 which interacts with myogenic and passive properties of vascular walls to coordinate blood flow distribution.28 Prior work has demonstrated significant spatial heterogeneity of basal and hyperemic blood flow in a canine model. CVs of 24.3% in basal flow and 30.4% in peak hyperemic flow were found between milligram-sized sections of the left ventricular free wall.29 The present study demonstrated variability when regional perfusion fields were examined, rather than small sections of a single perfusion field. The enhanced degree of blood flow variability found in patients with mild-to-moderate angiographic abnormalities may explain, at least in part, the enhanced variability found in the CFR of these 2 groups.
The finding of this increased variability suggests that early endothelial dysfunction may predate the appearance of hemodynamically significant angiographic abnormalities and disrupt the usual endothelium-derived local control of vascular tone and flow.
Sources of Variability of CFR
A variety of causes may lead to enhanced variability of CFR. One
possible explanation is the influence of reinnervation on the
transplant coronary circulation.30 In animal
models, the distribution of adrenergic receptors, in particular
2-receptors, across the microcirculation is
heterogeneous31 and may explain enhanced
vasoreactivity in response to adenosine.32 33
Because reinnervation is heterogeneous, the minimal
achievable coronary vascular resistance in
innervated versus denervated beds may be different.
Reinnervation differences could potentially modify regional left
ventricular metabolism and subsequently
regional blood flow. Denervated myocardium is not
metabolically equivalent to innervated
myocardium.34 35 36 37 Data on patients studied
early posttransplant, who are therefore completely denervated, may
offer indirect evidence in support of this hypothesis. The CV CFR in
patients studied at
1 year posttransplant was 13.7±7.5%, versus
9.4±4.2% (P=0.01) in patients studied within 42 days.
There was no relationship, however, between days posttransplant and CV
CFR (r=0.18, P=0.065).
Cellular rejection has also been shown to affect CFR.12 Higher grades of rejection may represent a more widespread process, presumably leading to a more uniform effect on CFR.38 We found no evidence, however, that differences in flow reserve were related to the grade of rejection.
Previous studies using PET suggest an elevated variability in flow reserve in patients with abnormal cholesterol.39 Correlation analysis of CV CFR showed a significant relationship between total cholesterol/HDL ratio and flow variability (r=0.28, P=0.0051). In the multiple logistic regression analysis, however, no lipid variable was a significant independent predictor of CFR variability.
PET studies have also shown that resistance vessel function in vascular beds remote from the affected epicardial artery in patients with single-vessel disease is abnormal relative to control patients with no arterial disease.40 41 A similar finding in transplant patients is not unexpected. A functional abnormality in the resistance bed and an absolute decline in microvascular cross-sectional area are 2 possible explanations. Given that absolute CFRs were not different between the normal and abnormal groups, it is difficult to implicate any significant loss of recruitable microvascular cross-sectional area. The findings suggest that the development of epicardial and small-vessel disease may be asymmetrical processes resulting in enhanced intervessel CFR variability. It is likely that the involvement of the intramyocardial vessels may be as heterogeneous as that found in the epicardial vessels.
Lower arterial saturation was associated with increased CV CFR. This finding is probably closely linked to the question of innervation. Denervated arteriolar smooth muscle has primarily anaerobic metabolism,42 whereas innervated arteriolar smooth muscle is primarily aerobic.43 The complex interplay between innervation and resistance vessel smooth muscle metabolism could be affected by changes in arterial oxygen saturation.
Increased body mass index was also predictive of increased CFR variability. Studies have demonstrated a correlation between elevated body mass index and development of a diffuse variant of transplant coronary arteriopathy.44 On the basis of the present data, a more pronounced arteriopathy should be associated with increased variability. Obesity has also been associated with insulin resistance, which has been correlated with both macrovascular and microvascular abnormalities. The microvascular abnormalities are thought to be related to increased sympathetic outflow; thus, heterogeneous reinnervation may again be implicated in increased variability.45 46
The proportional hazards analysis suggests that increased variability is associated with an increased frequency of an adverse outcome. Variability of CFR appears to have important clinical implications in a posttransplant patient population. The detection of increased variability, however, requires a more thorough evaluation of coronary blood flow than has been attempted in previous studies. The long-term resolution of the importance and source of enhanced variability will require characterization by postmortem examinations.
Limitations
CFR determinations in all 3 vessels could not be performed
simultaneously. Although changes in heart rate and blood
pressure may affect CFR measurements in patients, the mean blood
pressure and heart rate recorded during these studies did not
change significantly.47 There was no relationship between
heart rate or mean arterial pressure and CV CFR.
Absolute CFR values with the Doppler guidewire are lower than those reported in other studies using an intracoronary Doppler catheter.11 Previous studies have measured the Doppler shift with a zero-cross methodology that appears to overestimate flow compared with the fast Fourier transform spectral analysis used by the Doppler guidewire.20 21 48 The Doppler guidewire has been validated in both in vitro and in vivo models.20 CFRs measured in PET studies in transplant patients correlate more closely with measurements made with the Doppler guidewire than those made with the intracoronary Doppler catheter.
Conclusions
The findings in this study suggest that in a posttransplant
population, evaluation of resistance vessel function in a single
coronary artery by Doppler technology will fail to identify
variability among vascular regions. A complete evaluation of resistance
vessel function should include the calculation of the variability of
both baseline coronary flow and coronary vasodilatory
reserve. Those patients with modest angiographic abnormalities who do
not have diminished CFR may have subtle microvascular abnormalities not
readily appreciated by other methods. Although the precise clinical
association of increased variability of baseline flow and CFR with
outcome has not yet been established, increased coronary
vasodilatory reserve variability correlates with a significantly
increased risk of cardiovascular events and most likely
heralds the presence of allograft arteriopathy at the microvascular
level.
| Footnotes |
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Received March 24, 1998; revision received October 22, 1998; accepted November 3, 1998.
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