Meta-analysis of duplex surveillance following lower limb endovascular intervention
Introduction: The aim of this systematic review was to identify the evidence in the literature for limb salvage with the introduction of duplex surveillance.
Methods: A systematic review and meta-analysis was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (PRISMA) methodology for all studies which compared a group undergoing clinical surveillance with a group undergoing combined clinical and duplex surveillance after endovascular therapy for peripheral arterial disease. MEDLINE, EMBASE, the Cochrane Database for Systematic Reviews, and ClinicalTrials.gov were searched for relevant studies by 2 reviewers. Studies were quality assessed using the ROBINS-I tool. An individual patient data survival analysis and meta-analysis for 1- and 2-year amputation outcomes using a random-effects model were performed.
Results: Two low-quality nonrandomized studies met the inclusion criteria. There was a statistically and clinically significant reduction in major amputation in patients undergoing combined clinical and duplex surveillance (log-rank p<0.001). The number needed to treat to prevent 1 amputation at 2 years was 5 patients. At 1 year, the odds ratio (OR) for amputation was 0.22, 95% confidence interval (CI)=0.10-0.48, with no statistical heterogeneity. At 2 years, the numbers of patients were low and the effect on amputation was less certain OR=0.25, 95% CI=0.04-1.58.
Conclusions: Preliminary, low-quality data suggests that there may be a clinically significant reduction in major amputation with the introduction of duplex surveillance. It is recommended that a randomized controlled trial is performed to confirm these findings and identify the anatomical subgroups that benefit the most from surveillance.
History
Refereed
- Yes
Publication title
Journal of Endovascular TherapyISSN
1074-6218External DOI
Publisher
SAGE PublicationsFile version
- Published version
Item sub-type
ReviewAffiliated with
- School of Medicine Outputs