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European Heart Journal Advance Access originally published online on December 1, 2004
European Heart Journal 2005 26(4):363-368; doi:10.1093/eurheartj/ehi017
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© The European Society of Cardiology 2004. All rights reserved. For Permissions, please e-mail: journals.permissions{at}oupjournals.org

Assessment of flow-mediated vasodilatation (FMD) of the brachial artery: effects of technical aspects of the FMD measurement on the FMD response

Michiel L. Bots1,*, Jan Westerink2, Ton J. Rabelink3 and Eelco J.P. de Koning3

1Julius Center for Health Sciences and Primary Care, HP Str. 6.131 University Medical Center, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
2Department of Internal and Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
3Department of Medicine, Division of Nephrology, Leiden University Medical Center, Leiden, The Netherlands

Received 1 June 2004; revised 7 September 2004; accepted 9 September 2004; online publish-ahead-of-print 1 December 2004.

* Corresponding author. Tel: +31 30 250 9352; fax: +31 30 2505485. E-mail address: m.l.bots{at}jc.azu.nl


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 References
 
Aims The ability to assess endothelial function non-invasively with B-mode ultrasound has lead to its widespread application in a variety of studies. However, the absolute values obtained using this approach vary considerably across studies. We studied whether technical aspects of the methodology can explain the wide variety in absolute values across studies.

Methods and results A literature search was performed to identify published reports on flow-mediated vasodilatation (FMD) of the brachial artery published between 1992 and 2001. Information on type of equipment (wall track/B-mode), location of the measurement (antecubital fossa/upper arm), occlusion site (lower/upper arm), occlusion duration (min), and occlusion pressure was extracted. Patient characteristics were also extracted. For the healthy populations, mean FMD varied from 0.20 to 19.2%; for the coronary heart disease (CHD) patients FMD varied from –1.3 to 14%; for subjects with diabetes mellitus FMD varied from 0.75 to 12%. Compared with occlusion at the upper arm, lower arm occlusion was related to decreased FMD (mean difference in FMD –2.47%; 95% CI 0.55–4.39). An occlusion duration of ≥4.5 min was related to an increased FMD compared with an occlusion time of ≤4 min (mean difference 1.30%; 95% CI 0.35–2.46). These findings were adjusted for other technical aspects of the methodology and for differences in risk factors between populations.

Conclusion Mean FMD differs widely between studies. There is a great overlap between populations (healthy, CHD, diabetics). Our findings suggest that the technical aspects of the measurements, the location, and the duration of the occlusion may explain some of these differences, whereas type of equipment, location of the measurement, and occlusion pressure do not.

Key Words: Trials • Endothelial function • Prevention • Subclinical atherosclerosis • Cardiovascular risk


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 References
 
Over the last decades the focus of interest in cardiovascular epidemiology has broadened from studies on causes and consequences of elevated cardiovascular risk factors to include research on causes and consequences of (subclinical) atherosclerosis and related arterial wall abnormalities. In particular, large population-based and hospital-based studies have used techniques that enable non-invasive assessment of vascular wall characteristics to detect early vascular disease. Examples of measurements of subclinical atherosclerosis are assessment of coronary artery calcification, arterial stiffness, brachial endothelial function, and carotid intima–media thickness. Several reasons can be put forward for an increased interest in these indicators of vascular disease and potential ‘surrogate’ markers of cardiovascular risk. One is that established cardiovascular risk factors are insufficient in accurately identifying those individuals that will suffer from atherosclerotic disease in the future. Measures of subclinical vascular disease may enhance the precision of these predictions and thus enable improved tailor-made medical care. In addition, the availability of non-invasive measurements of subclinical vascular disease enables studies to be conducted among children, adolescents, and young adults that may greatly enhance our insight into the causes, development, and pathophysiological mechanisms of cardiovascular disease. Finally, assessing the presence of subclinical vascular disease may increase the efficiency and feasibility of randomized controlled trials on the efficacy of a certain treatment as fewer subjects are needed when the focus is on reduction of incidence of cardiovascular disease.

To non-invasively assess endothelial function, brachial arteries are scanned, with high resolution ultrasound imaging, under baseline conditions (at rest) and during hyperaemia induced by inflation and deflation of a sphygmomanometer cuff mostly around the forearm distal to the site scanned with ultrasound. The induced shear stress caused by the increased blood flow following transient ischaemia induces nitric oxide (NO) release, which in turn causes local arterial vasodilatation. Endothelial function, defined as flow mediated dilatation (FMD), is estimated as the percentage increase in vessel diameter from baseline conditions to maximum vessel diameter during hyperaemia. Impaired endothelial function of the brachial artery assessed in this manner has been reported in asymptomatic children and adults with elevated cardiovascular risk factors such as smoking,1–3 hypercholesterolaemia,4–7 hypertension,8–11 diabetes mellitus,12–16 and hyperhomocysteinaemia.17–19 Although the results of these studies are likely to be internally valid, comparison of the FMD values across studies is troublesome. The absolute mean FMD values vary considerably across populations, ranging from –1.9 to 19.2%. Whether these differences are due to differences in study populations (and thus risk factor profiles) or are a consequence of various aspects of measurement methodology is unclear. The latter is of importance when providing reference values of FMD. Therefore, we set out to evaluate whether technical or operative factors may explain the variability in absolute FMD values observed across studies by performing a literature search to identify published reports on flow-mediated vasodilatation of the brachial artery published between 1992 and 2001. The technical or operative aspects of the FMD measurement that were evaluated were equipment (wall track/B-mode), location of the measurement (antecubital fossa/upper arm), occlusion site (lower/upper arm), occlusion duration (min), and occlusion pressure.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 References
 
Identification of studies
We performed a literature search using PubMed (www.ncbi.nlm.nih.gov). ‘Flow mediated vasodilatation’ was used as the search term. The search was limited to ‘English language’, ‘human study’, and publication date between 1 January 1992 and 31 December 2001. The search was performed on 5 July 2002 and yielded 250 hits.1–250 All these papers were reviewed to assess whether they reported FMD of the brachial artery by non-invasive techniques. From each paper, a number of issues were extracted by one of the authors (J.W.); these data were: percentage men, mean age, mean total cholesterol, mean LDL cholesterol, mean HDL cholesterol, mean body mass index, mean systolic blood pressure, mean diastolic blood pressure, mean heart rate, percentage hypertensives, percentage hypercholesterolaemic subjects, percentage current smokers, percentage diabetics, and percentage patients with coronary heart disease (CHD). In case of uncertainty, the issues were discussed with one of the other authors (M.L.B., E.J.P.dK.) until consensus was reached.

Since our aim was to study determinants of differences in mean FMD across populations, one paper could contribute more than one study population. For example, when a paper described three groups of patients (i.e. healthy controls, diabetics, patients with CHD), the paper would yield three records in our database. For each study population, the same data were collected as listed above. In addition, information was collected on the mean study population FMD value and its standard deviation. With respect to technical or operative aspects of the measurement, data were extracted on type of equipment (wall track/B-mode), Iocation of the measurement (antecubital fossa/upper arm), occlusion site (lower/upper arm), location of the probe (antecubital fossa/upper arm), occlusion site (above/below the probe), occlusion duration (min), and occlusion pressure (certain value above systolic pressure in mmHg). The papers in which an occlusion pressure of 50 or 100 mmHg above systolic was used were categorized in the group with occlusion blood pressure between 200 and 250 mmHg. This decision was based on the observation that mean systolic blood pressure of the studied population plus either 50 or 100 mmHg always resulted in an average occlusion blood pressure below 250 mmHg.

Statistical analyses
The methodology of our analyses can be summarized as meta-regression, generally as described in papers on meta-analysis.251,252 The main differences in our approach compared with those described in the meta-analysis papers are two-fold. First, our outcome (dependent) variable was not a measure of association (e.g. an odds ratio), but rather the mean reported FMD value. Secondly, we have not aimed to estimate a common, ‘true’ mean FMD value over all studies. We have instead assumed the existence of heterogeneity, and explored some of the possible sources of variability between studies. For this reason, we have chosen a ‘fixed effects’, rather than a ‘random effects’, model in our analyses.

The distribution of FMD across studies is graphically presented in strata of healthy subjects, subjects with all CHD, and in subjects with diabetes mellitus. General characteristics of the study populations are presented as means with standard deviations or percentages. To determine the relation of methodological factors to the FMD estimate, linear regression models were performed. In these models, the studies were weighted for the inverse of the variance [=1/(se*se)] of the FMD measurement. With multi-variable regression models, the relationships were adjusted for differences in sex, age, presence of CHD, and diabetes.

Statistical significance was assumed when the two-sided P-value was <0.05. We did not adjust our models for multiple testing by using, for example, a Bonferroni correction. We do not feel that multiple testing is a major issue here but it may have affected our findings. Our main findings are given in Table 3, where we in principle ran only six models for the crude analyses and one model for column 2 and one model for column 3, amounting to 18 comparisons. Based on independent comparisons, one of the nine significant findings may be attributed to chance. However, we concentrate our paper on results of the two factors that were consistent findings.


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  		Table 3 Relationship of characteristics of the methodology used to the measured FMD
 

   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 References
 
Of the 250 papers from the literature search, 20 were excluded because of non-clarity in the presentation of the results. Due to clear overlap of study groups, two papers were excluded to prevent the possibility that one study group would have a greater weight in the analysis. A further nine studies were excluded because of missing data (standard deviations/errors) of the FMD estimate, which were needed for weighted linear regression. This left 219 papers, yielding 412 study groups comprising 16 680 subjects. General characteristics of the study populations are given in Table 1. Note that these values are means of the means provided of each study population. Table 1 also shows that the availability of information that could be extracted from the article varied considerably. Figure 1 shows the distribution of mean FMD values across healthy populations (A), CHD population (B) and populations with diabetes mellitus (C). From this figure it is clear that there is a wide distribution of mean FMD values in populations and a considerable overlap between populations. For the healthy populations, the mean FMD varied from 0.20 to 19.2%. For the CHD patients, mean FMD ranged from –1.3 to 14%. For subjects with diabetes mellitus mean FMD ranged from 0.75 to 12%. The FMD and the standard deviation of the FMD distribution is presented by number of patients in the study group (Figure 2).


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  		Table 1 General characteristics of the study populations
 


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  		Figure 1 Distribution of mean FMD values among healthy populations (A), CHD populations (B) and populations with diabetes mellitus (C).

 


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  		Figure 2 The relation of mean FMD (top) and standard deviation of the FMD distribution by number of subjects in the study group (n=405 study groups: 7 with patient numbers >175 were excluded for graphical reasons).

 
Information on fasting status was meagrely described. Out of the 412 papers, data on duration of fasting could be retrieved from 141 studies. Of those, 93% of the studies had a fasting time of 8 h or more, whereas 97.2% had a fasting time of 4 h or more. Given that the general consensus is that baseline FMD should be measured in a fasting state, these data may indicate that most of the FMD values obtained were measured in a fasting status. Information on the percentage of the population that used drugs was limited.

Overall, the use of lipid lowering drugs was 5.4% and of ACE-inhibitors 7.1%. The use was mainly restricted to the population with CHD or diabetes mellitus and again not described in detail in every paper.

Table 2 provides information on the observed technical or operative aspects of the FMD measurement in the studies. Complete information on all technical aspects could be extracted from 208 populations. The majority of the studies used B-mode ultrasound (87.7%), measured FMD above the antecubital fossa (89.2%) using an ischaemic trigger at the forearm (81.6%) with a duration of 4–5 min (84.4%) and an occlusion pressure above 250 mmHg (40.9%).


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  		Table 2 General characteristics of the methodology used in the studies
 
In Table 3, the relationship of technical aspects of the methodology to the measured FMD level is presented. Since mean FMD values of a population may reflect prevalence of risk factors of that population as well as technical aspects, the main findings were based on adjusted models. In a model where the various technical aspects were all included and in which adjustments were made for age, sex, presence of CHD, and diabetes, the lower arm occlusion compared with upper arm occlusion was related to a significantly decreased FMD (mean difference in FMD –2.47%; 95% CI 0.55–4.39). An occlusion duration of ≥4.5 min was related to a significantly increased FMD compared with an occlusion time of ≤4 min (mean difference 1.30%; 95% CI 0.35–2.46) (Table 3). Type of equipment (wall track/B-mode), location of the measurement (antecubital fossa/upper arm), and occlusion pressure were not statistically significantly related to mean FMD values of the populations.

To further explore the effect of adjustment for other cardiovascular risk factors on the magnitude of the relations of the two most important methodological aspects and on the variance explained, we extended the analyses with multi-variable models using smoking, body mass index, total cholesterol level, systolic blood pressure, use of lipid-lowering drug, and use of ACE-inhibitors (Table 4). From that table it is apparent that adjustments tend to attenuate the association with occlusion time, but not with upper arm occlusion. In addition, Table 4 shows that only a small percentage of the variability in the data is explained by technical aspects, and that, by far, the differences in cardiovascular risk factors between populations explain the variability in FMD across populations.


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  		Table 4 Relation of occlusion time and occlusion site to FMD, adjusted using various models
 

   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
References
 
Our findings confirm that there is a wide variety in measured mean FMD levels between populations, and even within populations that look alike, such as populations comprising subjects with CHD or subjects with diabetes mellitus. In addition, our findings indicate that some of these differences are attributable to technical aspects related to the measurement of the FMD of the brachial artery. The latter are important when comparing studies and when trying to provide reference values for FMD.

Some aspects of our study need to be addressed. First, the information we used in the analyses was retrieved from data reported in the papers. As can be seen from Tables 1 and 2, information was not always available on either the technical aspects or the risk factor information. This has clearly limited the precision of the associations in multi-variable models. In addition, it has been argued that missing information is not at random and may bias results towards a positive finding. We have, however, no means to substantiate this further. Furthermore, missing data in papers suggests providing more baseline information in tables in articles rather then restricting inclusion to that information which is of major importance or significance for the results of the article. Secondly, although our findings point towards differences across studies, they do not question the internal validity of the results of the individual papers. Furthermore, we used only the baseline data of the studies.

In various studies, the effects of methodology on the outcome of FMD have been addressed. In several, relatively small, studies the FMD response with an upper arm occlusion compared with using lower arm occlusion showed a higher FMD value.51,70,100,173,232 Our findings confirm this, but in a larger data set. A longer duration of the ischaemic trigger has been shown to increase the FMD response,91 a finding in agreement with our results. It has been shown that the measurement of FMD at the level of the radial artery leads to a lower absolute FMD value compared with a measurement at the level of the brachial artery.51 We extend that evidence by showing that, independent of other technical aspects, the mean values of the FMD measurements did not differ between assessments in the cubital fossa or above the cubital fossa. We are not aware of studies that have been conducted to evaluate the difference between the standard B-mode assessment and the wall track system. Our results show no difference in mean FMD values. In our analyses, the occlusion pressure (above or below 275 mmHg) did not affect the mean FMD values. Others, however, in a relatively small study, indicated that increased occlusion pressure leads to a higher absolute value of FMD.91 Finally, our results show that only a small part of the variability between populations can be explained by technical aspects related to the FMD measurement technique.

It has been suggested that reference values for FMD are important, in particular when the FMD measurement is going to be used as an indicator of risk. The observed wide range of measured FMD values across populations hampers the utility of FMD reference values. Our results indicate that neither differences in technical aspects, nor risk factor distributions can completely explain these differences. Attempts at setting reference values should at least take cuff location and occlusion time into account as well as cardiovascular risk factor levels. In addition, the results support standardization of the FMD measurements as has been attempted recently.253 A uniform methodology will facilitate the comparison between studies.

In conclusion, mean FMD values differ widely between studies. There is a great overlap between populations (healthy, CHD, diabetics). Our findings suggest that of the technical aspects of the measurements, location of the occlusion and duration of the occlusion may explain some of the differences, whereas type of equipment, location of the measurement, and occlusion pressure do not.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

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