| Autor: |
Rodway AD; Surrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.; Brighton and Sussex University Hospitals NHS Trust, Brighton BN2 5BE, UK., Cheal D; Brighton and Sussex University Hospitals NHS Trust, Brighton BN2 5BE, UK., Allan C; Surrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK., Pazos-Casal F; Surrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK., Hanna L; Department of Surgery and Cancer, Imperial College London, London SW7 2BX, UK., Field BCT; Surrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.; Department of Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK., Pankhania A; Surrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK., Aston PJ; Department of Mathematics, University of Surrey, Guildford GU2 7XH, UK., Skene SS; Department of Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK., Maytham GD; Surrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.; St George's University Hospitals NHS Foundation Trust, London SW17 0QT, UK., Heiss C; Surrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.; Department of Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK. |
| Abstrakt: |
Ankle brachial pressure index (ABPI) is the first-line test to diagnose peripheral artery disease (PAD). Its adoption in clinical practice is poor and its validity, particularly in diabetes, is limited. We hypothesised that ABPI can be accurately and precisely estimated based on cuffless Doppler waveforms. Retrospective analysis of standard ABPI and handheld Doppler waveform characteristics (n = 200). Prospective analysis of angle-corrected Doppler acceleration index (AccI, n = 148) and standard ABPI with testing of performance to diagnose PAD as assessed with imaging reference standards in consecutive patients. The highest AccI from handheld Doppler at ankle arteries was significantly logarithmically associated with the highest standard ABPI (E[y] = 0.32 ln [1.71 ∗ x + 1], p < 0.001, R2 = 0.68, n = 100 limbs). Estimated ABPI (eABPI) based on AccI closely resembled ABPI (r = 0.81, p < 0.001, average deviation −0.01 ± 0.13 [SD], n = 100 limbs). AccI from angle-corrected Doppler in patients without overt media sclerosis (ABPI ≤ 1.1) improved ABPI prediction (E[y] = 0.297 ∗ ln[0.039 ∗ x + 1], R2 = 0.92, p = 0.006, average deviation 0.00 ± 0.08, n = 100). In a population (n = 148 limbs) including diabetes (56%), chronic limb-threatening ischaemia (51%) and media sclerosis (32%), receiver operating characteristics analysis of (angle-corrected) eABPI performed significantly better than standard ABPI to diagnose PAD defined by ultrasound (ROC AUC = 0.99 ± 0.01, p < 0.001; sensitivity: 97%, specificity: 96%) at the ≤0.9 cut-off. This was confirmed with CT angiography (ROC AUC = 0.98, p < 0.001, sensitivity: 97%, specificity: 100%) and was independent of the presence of diabetes (p = 0.608). ABPI can be estimated based on ankle Doppler AccI without compression, and eABPI performs better than standard ABPI to diagnose PAD independent of diabetes. eABPI has the potential to be included as a standard component of lower extremity ultrasound. |
