The aim of this pilot study is to investigate the diagnostic accuracy of two automated ABPI devices across the spectrum of PAD (asymptomatic PAD, suspected symptomatic PAD \[IC; including mild moderate and severe IC based on the Rutherford classification (21) and CLTI\] and post-bypass surveillance). A second aim is to assess their useability and tolerability through semi-structured interviews with patients and clinicians. This means the research will be split into two workstreams.
Adults aged 18 and over
At risk of PAD with ≥1 cardiovascular risk factor
No previous diagnosis of PAD
English speaking and able to understand test protocols
Patients who are unable to provide informed consent
Recent (≤4 weeks) lower-limb surgery
Ulcers, casts or bandages that cannot or should not be compressed
Patients who have had a therapeutic intervention (stent or graft) which extends to the ankle
Group 1: Asymptomatic PAD: Patients identified by the GP (PIC sites). Records screened to identify 'at risk' of PAD with \>1 cardiovascular disease risk factor Group 2: Suspected symptomatic PAD: 2a. Patients with suspected IC referred to dedicated nurse-led claudication clinic. Group 2b. Patients with suspected CLTI referred to dedicated urgent vascular (HOT) clinic. Group 3: Patients undergoing surveillance seen in dedicated clinics by vascular scientists
Cohort
Cross-sectional
MESI mTablet
DeviceThe MESI mTablet uses 3CUFFTM technology to detect pulse waveforms to assess ABPI. This involves placing a blood pressure cuff on all 4 limbs at the same time. The two arm cuffs then inflate and simultaneously measure the blood pressure in both brachial arteries. The cuff with the highest systolic pressure than reinflates with both the ankle cuffs simultaneously. The ABPI is then calculated and displayed on the tablet. A ratio of \<0.9 will indicate the presence of PAD.
BlueDop vascular Expert (BlueDopVE)
DeviceThe BlueDop device is a cuffless device which comprises an egg-shaped handheld probe component and an output monitor device. The device measures mean arterial blood pressure through an algorithm. Simply, it calculates the average blood pressure based on the normal rise and fall of pressure during each heartbeat. The device then automatically generates an ankle-brachial pressure index and a corresponding traffic-light classification for each lower-limb artery, based on waveform. This output is interpreted using table 2 below. Essentially an ABPI of 0.8-1.0 with a biphasic or triphasic waveform indicates no disease whereas an ABPI \<0.8 and / or a monophasic/non-specific waveform indicates the presence of PAD.
Diagnostic Accuracy
Diagnostic accuracy assessed via sensitivity, specificity, positive predictor value (PPV) and negative predictor value (NPV).
Validity assessed via correlation
Diagnostic performance assessed via area under the receiver operating characteristic (AUROC) curve and the assessment time difference, assessed via measurement of the time taken to perform each automated ABPI assessment and the manual ABPI assessment.
Diagnostic performance
Assessed via area under the receiver operating characteristic (AUROC) curve.
Time taken to perform each automated ABPI assessment and the manual ABPI assessment.
Time taken to perform each assessment in seconds
Qualitative Workstream - Assessment of usability and tolerability of automated devices.
Semi structured interviews analysed using thematic analysis
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