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


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.
Clairotte
Cécile
C
Département de Physiologie-Explorations Fonctionnelles, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, Paris, France.
Retout
Sylvie
S
Potier
Louis
L
Roussel
Ronan
R
Escoubet
Brigitte
B
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D055109:Ankle Brachial Index / Q000379:methods*; D001331:Automation; D015992:Body Mass Index; D002784:Cholesterol / Q000097:blood; D003925:Diabetic Angiopathies / Q000097:blood / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000503:physiopathology; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007866:Leg / Q000098:blood supply; D008297:Male; D008875:Middle Aged; D016491:Peripheral Vascular Diseases / Q000097:blood / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000503:physiopathology; D011446:Prospective Studies; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012684:Sensory Thresholds; D018608:Ultrasonography, Doppler; D055815:Young Adult
D002784:Cholesterol; D006442:Glycated Hemoglobin