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Ankle Brachial Index Screening In Asymptomatic Older Adults

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Ankle Brachial Index Screening In Asymptomatic Older Adults

Abstract and Introduction

Abstract


Background Screening for peripheral arterial disease (PAD) by measuring ankle brachial index (ABI) in asymptomatic older adults is currently recommended to improve cardiovascular disease risk assessment and establish early treatment, but it is not clear if the strategy is useful in all populations. We examined the prevalence and independent predictors of an abnormal ABI (<0.90), in an asymptomatic sample of 1,017 adults, 60 to 69 years old, enrolled in the ADVANCE study.
Methods Baseline data collected between December 2001 and January 2004 among the healthy older controls enrolled in ADVANCE was examined. Frequency distributions and prevalence estimates of an abnormal ABI were calculated, using both standard and modified definitions of ABI. Stepwise logistic regression was used to examine independent predictors of ABI <0.90. Signal detection analysis using recursive partitioning was employed to explore potential demographic and clinical variables related to ABI <0.90.
Results The prevalence of ABI <0.90 was 2% when using the standard definition and 5% when using a modified definition. ABI prevalence did not differ by gender (P > .05). Compared with subjects who had a normal ABI (0.90–1.39), subjects with an ABI <0.90 were more likely to currently smoke, be physically inactive, have a coronary artery calcium score >10, and an FRS >20% (P ≤ .02). Independent predictors of ABI <0.90 when using the standard definition included currently smoking, physical inactivity, and body mass index >30 (all P values ≤.03), and when using the modified definition included currently smoking, physical inactivity, and hypertension (all P values ≤.04). Currently, smoking was the only significant variable for ABI <0.90 derived through recursive partitioning (P = .02), and indicated that prevalence of ABI <0.90 was 1.5% for nonsmokers, while it was 6.6% for current smokers.
Conclusions ABI screening in generally healthy individuals 60 to 69 years old may result in lower prevalence rates of a positive result than estimates based on studies in clinical populations. The modified definition for calculating ABI captured more asymptomatic adults with suspected peripheral arterial disease. More evaluation of the appropriate role of ABI screening in unselected populations is needed before routine screening is implemented.

Introduction


Evidence that adults with peripheral arterial disease (PAD) in the lower extremities are at higher risk for a cardiovascular disease (CVD) event, such as myocardial infarction or stroke, is clearly established. The American College of Cardiology/American Heart Association 2005 Practice Guidelines for the management of patients with PAD recommend measurement of ankle brachial index (ABI) in asymptomatic adults ≥50 years old with history of smoking or diabetes, among adults with lower extremity circulation problems, and all adults ≥70 years old to improve CVD risk assessment and establish early treatment. The recent Ankle Brachial Index Collaboration meta-analysis suggests that measurement of ABI may improve CVD risk prediction beyond the Framingham risk score. On the other hand, the United States Preventive Services Task Force recommends against routine ABI screening in asymptomatic adults, citing that there is insufficient evidence to warrant routine screening and that the added costs in time and resources may exceed benefits.

Routine screening tests are most useful when they reduce mortality or morbidity. The elements of a good screening test include its ability to detect a subclinical phase of the disease, when early treatment is known to improve patient outcomes, and to be widely accessible, simple to administer, inexpensive, and associated with minimal discomfort and morbidity for the population to be screened. Further, it is paramount that a screening test has established strong sensitivity and specificity for the disease being screened, for example, an ABI for detecting PAD. Reported sensitivity and specificity of ABI <0.90 to detect ≥50% stenosis in the lower extremities using digital subtraction angiography, is 76% and 90%, respectively.

In 2003, the average US cost of performing an ABI was $61 per case. Yet, ABI screening among adults at higher risk for developing PAD also uses resources such as staff training and time, equipment and supplies. Campbell et al conducted a study to improve targeted screening efforts for identifying PAD in high risk persons and reported associated costs ranging from 1 to 3 days of staff time per diagnosis. In addition, these investigators estimated that 15 patients needed to be screened to detect one new patient with PAD.

Reported prevalence of PAD, using ABI <0.90 as the indicator, ranges from 1.2% in a managed care organization's population of 6.67 million adult members ≥18 years old, up to 29% in the PARTNERS study which enrolled only higher-risk adults, that is, 50 to 69 years old with a history of smoking or diabetes mellitus or adults at least 70 years old. It is unknown what the prevalence of PAD (using ABI <0.90) is among healthy adults 60 to 69 years old without documented clinical cardiovascular disease.

Another issue for determining prevalence estimates of PAD using ABI <0.90 as the indicator, are the various methods reported for calculating ABI. The standard method uses the highest ankle pressure for each leg, divided by the highest brachial pressure. Recently, other investigators have suggested that modifying the ABI calculation method by using the lowest ankle pressure for each leg, divided by the highest brachial pressure, would improve sensitivity. This modified method for calculating an ABI leads to higher prevalence estimates, although it may degrade the specificity of the test.

Our aim was to determine the prevalence of an abnormal ABI (<0.90) along with independent predictors, in an asymptomatic sample of 1017 older adults, 60 to 69 years old, enrolled in the ADVANCE study, using both standard and modified methods for calculating ABI.

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