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. 2009 Jul;32(7):1231-6.
doi: 10.2337/dc08-2230. Epub 2009 Apr 14.

Automated ankle-brachial pressure index measurement by clinical staff for peripheral arterial disease diagnosis in nondiabetic and diabetic patients

Cécile Clairotte  1 , Sylvie Retout, Louis Potier, Ronan Roussel, Brigitte Escoubet
Affiliations

Automated ankle-brachial pressure index measurement by clinical staff for peripheral arterial disease diagnosis in nondiabetic and diabetic patients

Cécile Clairotte et al. Diabetes Care. 2009 Jul.

Abstract

Objective: Peripheral arterial disease (PAD) is a prognostic marker in cardiovascular disease. The use of Doppler-measured ankle-brachial pressure index (Dop-ABI) for PAD diagnosis is limited because of time, required training, and costs. We assessed automated oscillometric measurement of the ankle-brachial pressure index (Osc-ABI) by nurses and clinical staff.

Research design and methods: Clinical staff obtained Osc-ABI with an automated oscillometric device in 146 patients (83 with diabetes) at the time of Dop-ABI measurement and ultrasound evaluation.

Results: Measurements were obtained in most legs (Dop-ABI 98%; Osc-ABI 95.5%). Dop- and Osc-ABI were significantly related in diabetic and nondiabetic patients with good agreement over a wide range of values. When Dop-ABI <or=0.90 was used as the gold standard for PAD, receiver operating characteristic curve analysis showed that PAD was accurately diagnosed with Osc-ABI in diabetic patients. When ultrasound was used to define PAD, Dop-ABI had better diagnostic performance than Osc-ABI in the whole population and in diabetic patients (P = 0.026). Both methods gave similar results in nondiabetic patients. The cutoff values for the highest sensitivity and specificity for PAD screening were between 1.0 and 1.1. Estimation of cost with the French medical care system fees showed a potential reduction by three of the screening procedures.

Conclusions: PAD screening could be improved by using Osc-ABI measured by clinical staff with the benefit of greater cost-effectiveness but at the risk of lower diagnostic performance in diabetic patients.

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Figures

Figure 1
Figure 1
Relationship between Dop-ABI and Osc-ABI in nondiabetic (A) (r = 0.60; P < 0.0001) and diabetic (B) (r = 0.49; P < 0.0001) patients. C: Bland-Altman representation of Doppler and oscillometric measurement of ABI in the whole population and the 95% limit of agreement to the mean difference.
Figure 2
Figure 2
ROC Curves for Osc-ABI for diagnosis of PAD, as defined with Dop-ABI <0.90 in the whole population (A), diabetic patients (B), and nondiabetic patients (C). D: Best cutoff determination for maximizing both the sensitivity and the specificity in the whole population, diabetic and nondiabetic patients. ——, sensitivity; – – –, specificity.
Figure 3
Figure 3
ROC curves for Dop-ABI and Osc-ABI for diagnosis of ultrasound-identified arterial stenosis in the whole population (A), diabetic patients (B), and nondiabetic patients (C). Black square, Osc-ABI; gray diamond, Dop-ABI. D: Osc-ABI. E: Dop-ABI best cutoff determination for maximizing both the sensitivity and the specificity in the whole population, diabetic and nondiabetic patients. ——, sensitivity; – – –, specificity.
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Comment in

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