Abstract

IntroductionLeg ulcers are usually treated with compression therapy unless there is evidence of peripheral arterial disease (PAD). Compression may lead to vascular complications in people with PAD. Timely diagnosis and appropriate treatment are important to ensure the best patient outcomes. PAD is usually assessed using a manual ankle brachial pressure index (ABPI). Automated devices may reduce time to diagnosis and treatment of leg ulcers. This study investigated the diagnostic accuracy, clinical effectiveness, and cost effectiveness of automated ABPI measurement, compared with manual doppler testing, to detect PAD in people with leg ulcers.MethodsWe conducted a systematic review of studies of any design assessing automated devices in any population. Meta-analyses were conducted where possible. A decision tree and Markov model was used to capture lifetime costs, quality-adjusted life-years (QALYs), and cost effectiveness from a UK National Health Service perspective. Sensitivity analyses captured the uncertainty surrounding model assumptions and probabilistic sensitivity analyses described parameter uncertainty. Value of information analysis was conducted to identify future research priorities.ResultsA total of 22 studies provided diagnostic accuracy data for five automated devices, but there were no studies in people with leg ulcers. Meta-analysis of 12 studies demonstrated a pooled sensitivity of 64 percent (95% confidence interval [CI]: 57, 71) and a specificity of 96 percent (95% CI: 92, 98) for detecting PAD. Automated devices were cheaper to complete due to shorter test times, but the increased risk of inappropriate or delayed treatment due to inaccurate test results offset the cost savings and reduced the QALYs for automated devices.ConclusionsGiven the current limited evidence base, automated devices would only be cost effective if they can demonstrate substantial reductions in time to diagnosis in clinical practice. Value of information analysis identified the following research priorities: (i) to determine diagnostic accuracy in a population with leg ulcers; (ii) to determine the impact of test results on ulcer healing times, and (iii) to determine the risk of providing inappropriate treatment based on inaccurate test results.

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