The ankle-brachial index in clinical decision making

Herbert Jelinek, Matthew Austin

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


Background The ankle'brachial index (ABI) is an important tool for assessment of peripheral vascular disease. Diverse methods/equations for determining the ABI have been reported as well as different cut-off values used to indicate the presence of vascular pathology. Objectives (i) Investigate the role of the brachial component to determine the ABI, and (ii) investigate the influence of different lower cut-off values. Method Three methods/equations of utilising the brachial value were used to determine the ABI of 522 individuals. Ankle blood pressure readings were divided by: (i) average of the left and right brachial reading (AVERAGE); (ii) highest of left and right brachial reading (HIGHEST); (iii) higher brachial pressure was used unless the brachial pressures differed by less than 15 mmHg between the right and left side in which case the average was used (PROVISO). For these three methods/equations cut-off points were set at 0.8. 0.9 and 1.0. Data were analysed using one-way analysis of variance for continuous data and '2 analysis for categorical data. Results Comparison between the three methods/equations used to determine the ABI showed a statistically significant difference between the AVERAGE and HIGHEST method/equation (p = 0.005). Further, varying the cut-off values for each of the methods also showed statistically significant differences (p < 0.001). Conclusion Evidence-based data are currently insufficient for development of peripheral vascular diagnostic guidelines. Our research indicated that the method and cut-off value chosen for the ABI can lead to statistically significant differences in the number of people identified with possible peripheral vascular disease.
Original languageEnglish
Pages (from-to)153-157
Number of pages5
Issue number3
Publication statusPublished - 2006


Dive into the research topics of 'The ankle-brachial index in clinical decision making'. Together they form a unique fingerprint.

Cite this