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Circulation. 1995;92:1141-1147

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(Circulation. 1995;92:1141-1147.)
© 1995 American Heart Association, Inc.


Articles

Association of Coronary Disease With Segment-Specific Intimal-Medial Thickening of the Extracranial Carotid Artery

John R. Crouse, III, MD; Timothy E. Craven, MSPH; Amy P. Hagaman, MA; M. Gene Bond, PhD

From the Departments of Medicine and Public Health Sciences and the Division of Vascular Ultrasound Research, Bowman Gray School of Medicine of Wake Forest University, Winston Salem, NC.


*    Abstract
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*Abstract
down arrowIntroduction
down arrowMethods
down arrowResults
down arrowDiscussion
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Background Several investigators have evaluated relations between risk factors and intimal-medial thickness (IMT) of the extracranial carotid arteries and between IMT and clinical cardiovascular disease. Different indexes of IMT have been used as referents. We compared the strength of association of various IMT measurements with coronary artery disease as measured at coronary angiography.

Methods and Results We quantified the mean of the IMT for 12 sites of the extracranial carotid arteries (common carotid, bifurcation, internal carotid, near and far walls, and left and right sides [mean aggregate]) as well as for various combinations of sites (eg, segment-specific means, far walls only, maximum of any site) in 270 patients with or free of coronary artery disease. Models including age and all the indexes of IMT identified the mean aggregate as the only variable independently associated with the status of coronary atherosclerosis for the group as a whole. Next most strongly correlated was the mean common plus bifurcation. When classification algorithms were tested for ability to correctly classify case patients and control subjects, the mean bifurcation, mean common plus bifurcation, and mean aggregate were most strongly related to case-control status; however, the predictive power of the mean common was also strong.

Conclusions These data support use of the mean aggregate extracranial carotid IMT for correlation with the status of coronary atherosclerosis; however, the data also support use of the mean common plus bifurcation, since there is little increase in predictive power of the mean aggregate over this index. Use of the common carotid alone is also justifiable and may be preferable for certain analyses.


Key Words: coronary disease • carotid arteries


*    Introduction
up arrowTop
up arrowAbstract
*Introduction
down arrowMethods
down arrowResults
down arrowDiscussion
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A number of studies have quantified the association of intimal-medial thickness (IMT) of the extracranial carotid arteries and the status of coronary atherosclerosis.1 2 3 4 5 6 7 More recently, an association has been observed between atherosclerosis of the common carotid artery and incident coronary heart disease (CHD).8 In addition, studies have shown that factors that reduce risk of coronary artery disease (CAD) can influence progression rates of extracranial carotid atherosclerosis as measured by B-mode9 10 11 or Doppler12 ultrasound, and extracranial carotid atherosclerosis has been shown to progress faster in individuals with adverse levels of CAD risk factors13 14 15 and in individuals who themselves have coronary artery disease.16 IMT of the extracranial carotid arteries has often been quantified as the mean of IMT from 12 sites at three segments (left and right side, near and far wall of the common carotid, bifurcation, and internal carotid artery) or, alternatively, as the mean of IMT at 4 sites for each segment.17 Few data suggest a stronger association of CAD with disease at one or the other of these segments or, alternatively, with the mean aggregate. To investigate segment-specific associations with CAD in more detail, we quantified IMT of the extracranial carotid arteries in 270 individuals who were recruited as part of a study of risk factors for individuals undergoing coronary angiography, and we related IMT at the individual segments and sites to the status of coronary atherosclerosis.


*    Methods
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up arrowAbstract
up arrowIntroduction
*Methods
down arrowResults
down arrowDiscussion
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Population
The population recruited for this study is an extension of populations described previously, drawn from individuals undergoing cardiac catheterization at Bowman Gray School of Medicine.2 The study includes individuals who have undergone cardiac catheterization to define the status of coronary atherosclerosis. Inclusion criteria include age >=45 years and catheterization that identifies "case patients" (>=50% stenosis of one or more vessels) and "control subjects" (no lumen irregularities). Equal numbers of case patients, control subjects, men, and women were recruited according to a stratified random sampling strategy. Patients with coronary stenosis of <50% were excluded ("nonobstructive" CAD). Exclusion criteria include clinical instability (patients with myocardial infarction within the past 6 weeks, cardiogenic shock, or other evidence of clinical instability), previous coronary artery bypass surgery or angioplasty, use of certain medications or presence of certain clinical conditions that would alter plasma lipids (use of hypolipidemic drugs or thyroid medication, use of cortisone, liver disease, alcohol abuse, creatinine >=2.5, or heparin use), or certain unusual conditions, for example, individuals with carcinoma. In addition, patients with prevalent symptomatic cerebrovascular disease are excluded (stroke, transient ischemic attack, endarterectomy). Participants all provided informed consent.

For this study, individuals underwent initial risk factor profile testing approximately 6 to 8 weeks after their catheterization at a Preventive Cardiology Outpatient Clinic.

Clinical Evaluation
At the time of their clinic visit, participants were interviewed by the study coordinator using a standardized questionnaire. She obtained information regarding their heart and vascular disease history, vascular disease risk factor status, menstrual status, medications, and prior diagnostic evaluations. Participants also underwent measurement of height, weight, blood pressure, waist and hip girth, and cardiovascular disease risk factors. The presence of hypertension was defined by a history of the disease or a systolic blood pressure >150 mm Hg or a diastolic blood pressure >90 mm Hg. The presence of diabetes was defined by history of the disease or by a fasting glucose level of >140 mg/dL. Smoking status was recorded as the number of pack-years smoked.

Lipoprotein Analysis
Plasma total cholesterol and triglyceride and lipoprotein cholesterol were quantified in the Centers for Disease Control and Prevention–standardized Lipid Laboratory of the Bowman Gray School of Medicine according to the Lipid Research Clinics Program procedures.18 Cholesterol and triglyceride determinations were done on the Technicon RA-500 by enzymatic methods. For the determination of plasma HDL cholesterol concentrations, the heparin-manganese precipitation procedure as described in the Lipid Research Clinics manual was used. For total and HDL cholesterol determinations, the RA-500 enzymatic method was used with the Technicon reagent substituted by the Boehringer-Mannheim (BMD) high-performance cholesterol reagent.19 HDL plus LDL cholesterols were recovered after ultracentrifugation (in the 1.006 infranatant), and LDL was quantified as the difference between the 1.006 infranatant cholesterol and the cholesterol in the infranatant after precipitation of LDL.

Ultrasound
The ultrasound methodology for this trial was similar to one previously described.20 A Biosound 2000 II s.a. high-resolution ultrasound unit equipped with an 8-MHz transducer was used. Images were transcribed on SVHS 1/2-in videotape. An RMI 414B tissue-mimicking phantom was used to monitor and ensure instrument performance. Sonography and reading were done by trained and certified sonographers and ultrasound readers with regular quality control. Patients are examined in the supine position, and each carotid wall and segment is interrogated independently from continuous angles to identify the thickest intima-media site. Each scan of the common carotid artery begins just above the clavicle, and the transducer is moved cephalad through the bifurcation and along the internal carotid artery. Three segments are identified on each side: the distal 1.0 cm of the common carotid proximal to the bifurcation, the bifurcation itself, and the proximal 1.0 cm of the internal carotid artery. At each of the three segments for both near and far wall in the left and right carotid arteries, the sonographer identifies two interfaces: on the near wall, the first interface (interface 2) is the adventitial-medial boundary and the second (interface 3) is the intima-lumen boundary; on the far wall, the first interface (interface 4) is the lumen-intima and the second (interface 5) is medial-adventitial. Thus, 2-3 and 4-5 define IMTs on the near and far walls, respectively. When these interfaces have been demonstrated, the sonographer reduces gain and time-gain control settings as low as possible to decrease artifacts and then records the video images that include the maximum 2-3 and 4-5 IMTs at each of the 12 segments. Readers examine the videotapes and identify frames that demonstrate the maximum 2-3 and 4-5 IMTs within each segment. Frames are captured electronically and displayed on high-resolution monitors, and wall maximum thicknesses are calculated at each site.

Statistical Evaluation
For this study, case patients and control subjects were compared on the basis of several B-mode ultrasound characteristics of the extracranial carotid arteries. The segment-specific mean of the maximum of 4 sites for each of three segments (near and far wall, left and right side) was calculated (mean common, mean bifurcation, mean internal), as well as the mean of the aggregate of all 12 sites (4 sites at each of three segments, mean aggregate) and the mean of the far wall at each of 6 sites. In addition, the segment-specific maximum (maximum of the four wall thicknesses at each of the three segments) was identified (max common, max bifurcation, max internal) and the maximum of all 12 sites (max aggregate).

Statistical Methods
Descriptive statistics were computed for variables of interest. Statistics computed included means, SDs, and percentiles of continuous variables (eg, age, lipid levels, IMT measurements) and frequencies and relative frequencies of categorical factors (eg, diabetes status, hypertension history) by case-control status and by sex. Variables were examined to verify that assumptions of statistical techniques were met. Univariable comparisons of mean lipid levels and IMT measurements between case and control groups were made with unpaired t tests. Univariable comparisons of case-control differences in categorical factors were performed with {chi}2 tests. Associations between IMT measurements were examined with Pearson correlation coefficients both overall and by sex.21

The logistic discriminant function was used to examine the differential abilities of each of the nine IMT measurements to effectively predict case-control status after age differences between case patients and control subjects were controlled for. This was done by use of separate logistic regression models, one for each IMT variable, each of which included age as a covariable. Comparisons between models were performed by examining medians and interquartile ranges of the resubstitution predicted probabilities of correct classification (ie, the probability of being a case for case patients and one minus the probability of being a case for control subjects22 ). Forward stepwise logistic regression was used to examine which IMT measurement or combination of measurements was best at predicting case or control status. Each IMT measurement was included as a candidate for selection after age was forced into the model. When variable selection was performed, the most significant (smallest P value) IMT with a value of P<.05 was selected first, then the next most significant factor with a value of P<.05 was entered after the factor(s) already selected was controlled for. Stepping continued until all factors with (type III) values of P<.05 were entered, and any factors that stepped into the model that became nonsignificant at a later step were removed.23


*    Results
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up arrowAbstract
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*Results
down arrowDiscussion
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Of 280 individuals recruited for this study, data were available for IMT of all three segments (common carotid, bifurcation, and internal carotid) in 270 participants. The internal carotid artery could not be interrogated at all in 10 participants. Therefore, the analysis of associations of carotid arterial measurements with the status of coronary atherosclerosis was confined to the 270 individuals for whom information regarding IMT at one or more sites for each of the three arterial segments was available. Clinical characteristics of the 280 participants originally enrolled are provided in Table 1Down. Individuals with CAD were older than those free of CAD and in general had higher total and LDL cholesterol, lower HDL cholesterol, more pack-years of smoking, and a greater prevalence of diabetes and hypertension. Because of the strong and consistent association of age with both the status of coronary atherosclerosis and IMT (data not shown), all analyses have been adjusted for age.


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Table 1. Risk Factors in Patients With CAD and in CAD-Free Control Subjects

In this as in several other studies,20 24 25 there was a differential rate of "missing data" for scanning the common carotid, bifurcation, and internal carotid arteries. More than 99% of sites could be evaluated in the common carotid artery and 94% in the bifurcation, but only 78% could be evaluated in the internal carotid. The worst two sites in this regard were the near wall of the left and right internal carotid arteries, where 27% and 30% of the attempted interrogations were unsuccessful.

Mean and maximum age-adjusted IMTs for (1) the aggregate of all three segments, (2) the three segments individually, (3) the common plus bifurcation, and (4) the bifurcation plus internal in 270 participants with and without coronary artery disease are presented in Table 2Down. This table also shows data for the mean aggregate for the far wall only. There are significant differences between case patients and control subjects for the group as a whole and for men and women separately for every index of IMT. In general, the case-control differences in the mean bifurcation, the mean bifurcation plus common, and the mean aggregate were greater than differences in other indexes of IMT for the group as a whole (T=5.84, 5.85, and 5.93, respectively). For men, case-control differences in the mean bifurcation, the mean common plus bifurcation, the mean internal, and the mean aggregate were greatest (T=3.70, 3.85, 3.97, and 4.19, respectively), whereas in women, the case-control differences in the mean bifurcation, the mean common plus bifurcation, the max bifurcation, and the max aggregate were greatest (T=4.47, 4.31, 4.58, and 5.03, respectively). In the group as a whole and for men and women separately, the case-control differences in the mean bifurcation, the mean common plus bifurcation, and the mean aggregate were consistently large, whereas the differences in the common carotid were relatively small compared with other indexes of IMT. Of interest, while there were large differences in mean internal associated with the status of coronary atherosclerosis in men, these differences were considerably less in women. Similarly, the max aggregate, which showed the largest difference associated with the status of coronary atherosclerosis in women, showed the smallest difference in men. Evaluation of data from the far wall only did not result in greater case-control differences than the mean aggregate (T for the mean aggregate far wall only for the group as a whole and for men and women separately was T=5.34, 3.43, 4.05, respectively; for the mean aggregate, T=5.93, 4.19, 4.08, respectively). SEMs were consistently lowest for the common carotid, followed by the common carotid plus bifurcation and the mean aggregate. SEMs were consistently considerably higher for the maximum indexes.


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Table 2. Mean Segment-Specific IMT in Patients With CAD and in CAD-Free Control Subjects

As shown in Table 3Down, segment-specific indexes and aggregate indexes were highly correlated with one another (correlation coefficients range from r=.395 to r=.945). In general, the mean of the bifurcation, internal, and common carotid were correlated with one another in the group as a whole and in men and women separately (correlation coefficients range from r=.466 to r=.707), with the bifurcation and the internal carotid showing the strongest association with one another (r=.653, r=.707, and r=.588 for the group as a whole and for men and women separately), as has previously been noted.26 Correlations of the segment-specific maxima with one another were weaker than for the means (range of correlations, from r=.395 to r=.612) but also were strongest for the association of the bifurcation with the internal carotid artery (r=.578, r=.612, and r=.530 for the group as a whole and for men and women separately). The segment-specific and aggregate maxima were highly correlated with the mean segment-specific and mean aggregate indexes of IMT (range of correlation coefficients, from r=.87 to r=.94), and the mean aggregate index correlated with the mean segment-specific indexes, whereas the maximum aggregate index correlated with the maximum segment-specific indexes (correlations were stronger with the bifurcation and internal than with the common carotid artery).


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Table 3. Correlation Coefficient for Interassociation Among IMT Segments

Next, we carried out logistic regression to estimate the independent association of age and the nine measures of carotid IMT with the status of coronary atherosclerosis (Table 4Down). In this analysis, the mean aggregate was the only variable selected for the group as a whole. The maximum aggregate was selected for women, and both the maximum and mean aggregates were selected for men. Other IMT thickness measures did not remain significant in multivariable analysis because of intercorrelations among sites as described above. We repeated this analysis incorporating only the five mean indexes (three mean segment-specific indexes, the mean common plus bifurcation, and the mean aggregate). In this analysis, the mean aggregate was the only variable selected for the group as a whole and for men, whereas the mean bifurcation was selected for women. In models including only the mean internal, mean bifurcation, mean common, and mean common plus bifurcation, the mean common plus bifurcation was selected for the group as a whole, the mean internal was selected for men, and the mean bifurcation was selected for women.


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Table 4. Results of Forward Stepwise Multivariate Selection Procedures for Logistic Regression Models to Predict the Status of Coronary Atherosclerosis as a Function of Age and Measures of Carotid IMT Overall and by Sex

Finally, we tested individual classification algorithms for their ability to correctly classify case patients and control subjects (Table 5Down). In this analysis, including age and IMT in the model, the mean bifurcation, the mean common plus bifurcation, and the mean aggregate consistently showed greater power to discriminate case patients from control subjects for the group as a whole and for men and women separately compared with other IMT indexes. The analyses described above (Table 4Up) identify the mean aggregate (for all patients and for men) and the mean bifurcation (for women) as the best discriminators of CAD case patients from control subjects after exclusion of the (relatively unstable) maximum indexes. Table 5Down provides an estimate of the additional power associated with the mean aggregate (for the group as a whole and for men) and of the bifurcation (for women) over the mean common plus bifurcation, and therefore, of the increase in predictive power associated with quantification of the mean internal. For the group as a whole, the median probability of correct classification is .649 for the mean aggregate and .639 for the mean common plus bifurcation. For men, the corresponding probabilities are .646 and .620. For women, the internal is one of the weakest predictors, and the median probabilities for the mean bifurcation versus the mean common plus bifurcation are .656 versus .655. Thus, information from the internal carotid adds very little to the predictive power of the mean common plus bifurcation in any group. Furthermore, increase in predictive power associated with the mean aggregate compared with the mean common carotid was not dramatic (eg, median probability of correct classification for the mean aggregate for all patients was P=.649 and for the mean common, P=.607).


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Table 5. Logistic Models to Predict CAD Status as a Function of Age and Each of the 11 Segment-Specific and Aggregate IMT Measures


*    Discussion
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up arrowAbstract
up arrowIntroduction
up arrowMethods
up arrowResults
*Discussion
down arrowReferences
 
Many investigators have evaluated associations of risk factors17 and of change in risk factor levels9 10 11 12 27 with extracranial carotid IMT. Others have evaluated associations of extracranial carotid IMT with presence or absence2 and extent28 of CAD at angiography as well as with CHD.1 3 4 5 6 7 Stenosis of the carotid arteries measured by Doppler29 30 31 or by B-mode8 ultrasound has also been shown to correlate with CHD incidence. An early evaluation of measurement reliability suggested that an aggregate measure of extracranial carotid IMT extent that incorporates information from the near and far walls of each of three extracranial carotid segments (common, bifurcation, internal carotid) on the left and right sides had greater stability than measurements at individual sites and that incorporation of information from several sites with potentially variable response to risk factors and variable susceptibility to atherosclerosis was advantageous32 ; subsequently, many epidemiological studies have used the mean aggregate IMT as an index of disease of the extracranial carotid arteries1 2 6 19 25 26 28 (reviewed in Reference 17). Most clinical trials that have used B-mode ultrasound to evaluate outcome have also focused on the mean aggregate IMT (12 sites) of the extracranial carotid arteries.10 11 27 However, several observers have had difficulty in scanning the internal carotid artery, for various technical reasons, including its tortuosity, proximity to the mandible, etc,33 34 or have used computerized methods that may be best suited for quantification of the IMT of the far wall of the common carotid artery.9 Partly for these reasons, these investigators and others have focused attention on the common carotid artery for epidemiological studies4 7 35 36 37 and clinical trials,9 and recently, investigators have reported good reliability for measurements confined to the common carotid arteries for computerized9 as well as visual38 readings. Use of information from the common carotid only has been criticized because the common carotid is not predisposed to develop stenotic disease. Use of information from the near walls of arteries has also been criticized because of the lesser validity of ultrasound measurements in relation to pathology from these sites compared with far walls.39 40

Another approach to quantification of carotid arterial disease (as in the Cardiovascular Health Study) has been to measure the far wall IMT of the common carotid and internal carotid (really internal carotid plus bifurcation) separately and, in addition, to obtain Doppler ultrasound quantification of percent stenosis of the internal carotid.3 41 These data can be used either separately or in the aggregate to characterize individuals according to "wall thickening" or "plaque."

A final alternative to use of the mean of various measurements at segments or in the aggregate is to use the single maximum IMT observed over all sites. The approach that quantifies mean IMT has the advantage of stability and of capturing extent of disease, whereas the approach that quantifies the maximum focuses on severity of disease and probably better identifies arterial plaques. Both approaches are likely to be informative in cross-sectional studies; for longitudinal studies, the greater stability associated with mean measurements is likely to improve analytic power.

The present study identifies strong associations of coronary artery status with mean (near plus far wall) IMT at each of three carotid segments as well as with the mean aggregate IMT. Associations of IMT with CAD were no stronger when information from only the far wall was used, and measurement variability of data from the far wall exceeded that of the near plus far wall. Individual segment-specific and aggregate maxima were strongly correlated with CAD. However, variability of the index represented by the maximum of all sites was greater than for any other index.

In multivariate analysis of the entire roster of potential predictors for the group as a whole, the mean aggregate appeared most informative. In sex-specific analysis for women, the maximum aggregate was most informative, and for men, the mean and maximum aggregates were both predictive, further supporting the importance of the maximum index in cross-sectional analysis. When the individual maximum measurements were not included in the predictive equations, the mean aggregate was most predictive in the group as a whole and in men, whereas the mean of the bifurcation was strongest in women. Including only the segment-specific means in the predictive equation, the mean common plus bifurcation had the strongest predictive power for the status of coronary atherosclerosis in the group as a whole, whereas the mean bifurcation was strongest in women and the mean internal in men. However, from the classification algorithms, the differences in predictive power associated with various indexes of carotid arterial disease were trivial in comparison with the strength of association of each with CAD.

Thus, for cross-sectional studies including men and women, the mean aggregate and/or the individual maximum is the best index of extracranial carotid disease because of their strength of association with CAD. For studies of disease progression or clinical trials, the mean aggregate is probably preferable because of its smaller measurement variability. For those investigators who would prefer not to include the internal carotid in analysis because of difficulty in visualization and lesser stability of measurements of this segment, an ideal B-mode protocol for cohort studies or clinical trials would most likely include the mean of the near and far walls of both the common carotid artery and the bifurcation. Both segments are easily accessible, and inclusion of data from the bifurcation would probably expand the informativeness above that of either segment alone. In our analysis, adding information from the internal carotid to that from the common and bifurcation provided very little additional power to categorize the status of coronary atherosclerosis.

On the other hand, much of the literature that associates extracranial carotid disease with incident CHD focuses on stenosis of the internal carotid artery (eg, see Reference 29); one other study in which segment-specific analyses were compared with one another for ability to predict prevalent CHD found stenosis of the internal carotid artery to be most highly predictive.3 Salonen and Salonen8 observed the highest correlation with incident CHD to be plaque or stenosis of the common carotid/bifurcation. Thus, for prediction of incident CHD, an index of stenosis by Doppler or one derived from the maximum IMT observed at all sites may be as strong as or stronger than the mean aggregate index.

Finally, these data also support use of the common carotid artery alone, particularly for studies of associations of risk factors with carotid arterial disease, cohort studies, or clinical trials, in that it, too, is associated with the status of coronary atherosclerosis. It is excellent in regard to measurement stability, and since it is much easier to interrogate than other segments, it may be ideal for certain (eg, computerized) measurements.


*    Acknowledgments
 
This research was supported by grant RO-1 HL-35333 from the NHLBI.


*    Footnotes
 
Reprint requests to Dr John R. Crouse III, Department of Medicine, Bowman Gray School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157.

Received November 22, 1994; revision received February 27, 1995; accepted February 27, 1995.


*    References
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowMethods
up arrowResults
up arrowDiscussion
*References
 
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