Measurement characteristics of the ankle-brachial index: results from the Action for Health in Diabetes study

Abstract

Many protocols have been used in clinical and research settings for collecting systolic blood pressure (SBP) measurements to calculate the ankle-brachial index (ABI); however, it is not known how useful it is to replicate measurements and which measures best reflect cardiovascular risk. Standardized measurements of ankle and arm SBP from 5140 overweight or obese individuals with type 2 diabetes were used to estimate sources of variation. Measurement characteristics of leg-specific ABI, as calculated using a standard algorithm based on the highest SBP of the dorsalis pedis or posterior tibial arteries, were projected using simulations. Coefficients of variability ranged from 2% to 3% when single SBP measurements were used and ABI was overestimated by 2-3%. Taking two SBP measurements at each site reduced standard errors and bias each by 30-40%. The sensitivity of detecting low ABI ranges exceeded 90% for ABI within 0.05 of the 0.90 clinical cut-point. The average and the minimum of the two (i.e. right and left) leg-specific ABI values had similar U-shaped relationships with Framingham risk scores; however, the average leg ABI had slightly greater precision. Replicating SBP measurements reduces the error and bias of ABI. Averaging leg-specific values may increase power for characterizing cardiovascular disease risk.

Trial registration: ClinicalTrials.gov NCT00017953.

Figure 1

Standard error of leg-specific ABI from the three approaches across the range of ABI. Summary: for higher ABI, its variability due to measurement error is increased. Replicating SBP measurements (Approach 1) reduces variability.

Figure 2

Expected bias of leg-specific ABI: from the three approaches and across the range of underlying ABI. Summary: ABI calculated by the AHA algorithm tends to overestimate its true value. Replicating SBP measurements (Approach 1) reduces bias.

Figure 3

Expected sensitivity and specificity of leg-specific ABI for classifying individuals with respect to underlying ABI at cutpoints of < 0.90 (Panel A) and > 1.30 (Panel B) with (Approach 1) and without (Approach 2) replicate SBP measurements. Summary: when the value of ABI is more than 0.05 units from the clinical cutpoints of 0.90 and 1.30, it reliably distinguishes patients with low and high ABI.

Figure 4

Distribution of Framingham 1-year risk scores across the distribution of average and minimum ABI values. Summary: cardiovascular disease risk scores are elevated for both low and high ABI.

Figure 5

Standard error of minimum and average ABI with (Approach 1) and without (Approach 2) replication of SBP measurements. Summary: averaging ABI values from the right and left legs reduces standard error.