Impact of Ankle Brachial Index Calculations on Peripheral Arterial Disease Prevalence and as a Predictor of Cardiovascular Risk

Antonio J G Pereira Filho; Fredrik Sartipy; Fredrik Lundin; Eric Wahlberg; Birgitta Sigvant

doi:10.1016/j.ejvs.2022.05.001

Impact of Ankle Brachial Index Calculations on Peripheral Arterial Disease Prevalence and as a Predictor of Cardiovascular Risk

Eur J Vasc Endovasc Surg. 2022 Aug-Sep;64(2-3):217-224. doi: 10.1016/j.ejvs.2022.05.001. Epub 2022 May 7.

Authors

Antonio J G Pereira Filho¹, Fredrik Sartipy², Fredrik Lundin³, Eric Wahlberg⁴, Birgitta Sigvant⁵

Affiliations

¹ Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. Electronic address: antonio.garciapereirafilho@regionvarmland.se.
² Section of Vascular Surgery, Department of Clinical Science and Education, Karolinska Institute at Södersjukhuset, Stockholm, Sweden.
³ Centre of Clinical Research, Region Värmland, Karlstad, Sweden.
⁴ Department of Medicine and Health, Linköping University, Linköping, Sweden.
⁵ Department of Surgical Sciences, Uppsala University, Uppsala, Örebro University Hospital, Sweden.

PMID: 35537637
DOI: 10.1016/j.ejvs.2022.05.001

Abstract

Objective: The aim of this study was to estimate the prevalence and predictive accuracy for cardiovascular (CV) morbidity by using different ankle brachial index (ABI) calculation methods in the general population.

Methods: ABI measurements and questionnaire data were collected from 5 080 randomly selected citizens aged 60 - 90 years. A 10 year follow up with data from Swedish national health registries was carried out. ABI was calculated using as numerator the highest (ABI-HI) or the lowest (ABI-LO) ankle BP obtained in each leg. Subjects were defined as references or having peripheral arterial disease (PAD) based on ABI-LO (Group 1) or ABI-HI (Group 2). Prevalence, mortality, CV events and risk were then analysed for these three groups, and their predictive power by using the area under the curve (AUC).

Results: A total of 4 909 inhabitants were included in the cohort (References: 83.8%, Group 1: 6.7% and Group 2: 9.6%). The prevalence of PAD was 16% using ABI-LO, and 9.6% using ABI-HI. The 10 year all cause mortality for references and Groups 1 and 2 was 27.6%, 48.8%, and 67.2%, respectively. The overall age adjusted hazard ratio (95% confidence interval) for the composite outcome of CV mortality and a non-fatal CV event was 1.25 (1.06 - 1.49) for Group 1 and 2.11 (1.85 - 2.39) for Group 2. The prediction accuracy for ABI < 0.9 in predicting CV event measured with AUC was 0.60 for ABI-HI and 0.62 for ABI-LO.

Conclusion: An ABI < 0.9 should be considered a strong risk marker for future CV morbidity. Applying the traditional ABI calculation method of using the highest measured ankle BP, a group of subjects with high CV risk may be overlooked for intervention, and this why the lowest ankle BP should be the preferred for risk stratification. However, as a single predictive tool an ABI < 0.9 cannot adequately discriminate which individual will have a future CV event regardless of calculation method used.

Keywords: Ankle brachial index; Cardiovascular events; Mortality; Risk assessment; Risk marker.

MeSH terms

Aged
Aged, 80 and over
Ankle Brachial Index / methods
Cardiovascular Diseases* / diagnosis
Cardiovascular Diseases* / epidemiology
Heart Disease Risk Factors
Humans
Middle Aged
Peripheral Arterial Disease* / complications
Peripheral Arterial Disease* / diagnosis
Peripheral Arterial Disease* / epidemiology
Predictive Value of Tests
Prevalence
Risk Factors