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International Journal of Vascular Medicine
Volume 2016, Article ID 1390475, 5 pages
Research Article

ABPI against Colour Duplex Scan: A Screening Tool for Detection of Peripheral Arterial Disease in Low Resource Setting Approach to Validation

1Public Health Complex, Ministry of Health, 555/5, 6th Floor, Elvitigala Mawatha, Narahenpita, 10100 Colombo, Sri Lanka
2Department of Community Medicine, Faculty of Medicine, University of Colombo, No. 25, Kynsey Road, 008000 Colombo, Sri Lanka
3Department of Surgery, Faculty of Medicine, University of Colombo, No. 25, Kynsey Road, 00800 Colombo, Sri Lanka

Received 28 November 2015; Accepted 8 February 2016

Academic Editor: Mark Morasch

Copyright © 2016 Janaka Weragoda et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. In Sri Lanka the ABPI has not been used as a screening tool to detect peripheral arterial disease (PAD) in epidemiological studies. This study was conducted to determine the best cutoff value of ABPI to detect PAD in Sri Lankan population. Methods. The ABPI measured by arterial Doppler to detect PAD was validated against colour duplex scan as the criterion using 165 individuals referred to vascular laboratory, National Hospital Sri Lanka. In all selected individuals ABPI was measured and lower limb colour duplex scan was performed. Narrowing of luminal diameter of lower limb arteries 50% or more was considered as haemodynamically significant and having PAD. The discriminative performance of the ABPI was assessed using Receiver Operator Characteristic (ROC) curve and calculating the area under the curve (AUC). The sensitivity and specificity of different threshold levels of ABPI and the best cutoff value of ABPI to detect PAD were determined. Results. ABPI 0.89 was determined as the best cutoff value to identify individuals with PAD. At this level of ABPI high sensitivity (87%), specificity (99.1%), positive predictive value (98.9%), and negative predictive value (88.4%) were observed. Conclusion. ABPI ≤ 0.89 could be used as the best cut off value to detect PAD.