BACKGROUND: The reference standard for diagnosing peripheral arterial disease in primary care is the ankle brachial index (ABI). Various methods to measure ankle and brachial blood pressures and to calculate the index are described. AIM: To compare the ABI measurements performed in primary care with those performed in the vascular laboratory. Furthermore, an inventory was made of methods used to determine the ABI in primary care. DESIGN OF STUDY: Cross-sectional study. SETTING: Primary care practice and outpatient clinic. METHOD: Consecutive patients suspected of peripheral arterial disease based on ABI assessment in primary care practices were included. The ABI measurements were repeated in the vascular laboratory. Referring GPs were interviewed about method of measurement and calculation of the index. From each patient the leg with the lower ABI was used for analysis. RESULTS: Ninety-nine patients of 45 primary care practices with a mean ABI of 0.80 (standard deviation [SD] = 0.27) were included. The mean ABI as measured in the vascular laboratory was 0.82 (SD = 0.26). A Bland-Altman plot demonstrated great variability between ABI measurements in primary care practice and the vascular laboratory. Both method of blood pressure measurements and method of calculating the ABI differed greatly between primary care practices. CONCLUSION: This study demonstrates that the ABI is often not correctly determined in primary care practice. This phenomenon seems to be due to inaccurate methods for both blood pressure measurements and calculation of the index. A guideline for determining the ABI with a hand-held Doppler, and a training programme seem necessary.
BACKGROUND: The reference standard for diagnosing peripheral arterial disease in primary care is the ankle brachial index (ABI). Various methods to measure ankle and brachial blood pressures and to calculate the index are described. AIM: To compare the ABI measurements performed in primary care with those performed in the vascular laboratory. Furthermore, an inventory was made of methods used to determine the ABI in primary care. DESIGN OF STUDY: Cross-sectional study. SETTING: Primary care practice and outpatient clinic. METHOD: Consecutive patients suspected of peripheral arterial disease based on ABI assessment in primary care practices were included. The ABI measurements were repeated in the vascular laboratory. Referring GPs were interviewed about method of measurement and calculation of the index. From each patient the leg with the lower ABI was used for analysis. RESULTS: Ninety-nine patients of 45 primary care practices with a mean ABI of 0.80 (standard deviation [SD] = 0.27) were included. The mean ABI as measured in the vascular laboratory was 0.82 (SD = 0.26). A Bland-Altman plot demonstrated great variability between ABI measurements in primary care practice and the vascular laboratory. Both method of blood pressure measurements and method of calculating the ABI differed greatly between primary care practices. CONCLUSION: This study demonstrates that the ABI is often not correctly determined in primary care practice. This phenomenon seems to be due to inaccurate methods for both blood pressure measurements and calculation of the index. A guideline for determining the ABI with a hand-held Doppler, and a training programme seem necessary.
Authors: P Greenland; J Abrams; G P Aurigemma; M G Bond; L T Clark; M H Criqui; J R Crouse; L Friedman; V Fuster; D M Herrington; L H Kuller; P M Ridker; W C Roberts; W Stanford; N Stone; H J Swan; K A Taubert; L Wexler Journal: Circulation Date: 2000-01-04 Impact factor: 29.690
Authors: A T Hirsch; M H Criqui; D Treat-Jacobson; J G Regensteiner; M A Creager; J W Olin; S H Krook; D B Hunninghake; A J Comerota; M E Walsh; M M McDermott; W R Hiatt Journal: JAMA Date: 2001-09-19 Impact factor: 56.272
Authors: Olga A Gimnich; Jonathan Holbrook; Tatiana Belousova; Christina M Short; Addison A Taylor; Vijay Nambi; Joel D Morrisett; Christie M Ballantyne; Jean Bismuth; Dipan J Shah; Gerd Brunner Journal: Am J Cardiol Date: 2020-11-02 Impact factor: 2.778
Authors: Mark R Nelson; Stephen Quinn; Tania M Winzenberg; Faline Howes; Louise Shiel; Christopher M Reid Journal: BMJ Open Date: 2012-10-25 Impact factor: 2.692