Saint-Bonnet Doppler waveform classification system: a scoping review and evidence-based appraisal using AGREE II and AGREE-REX.
Authors
Affiliations (4)
Affiliations (4)
- Section of Vascular Surgery, Department of Surgery and Cancer, Imperial College London, London, United Kingdom.
- Department of Radiology and Medical Imaging, College of Applied Medical Sciences, Majmaah University, Al-Majmaah, Saudi Arabia.
- Institute of Epidemiology and Health Care, University College London (UCL), London, United Kingdom.
- Imperial Vascular Unit, Imperial College Healthcare NHS Trust, London, United Kingdom.
Abstract
Doppler waveform interpretation is central to the diagnosis and surveillance of lower limb peripheral arterial disease (PAD). Despite widespread clinical use of duplex ultrasound (DUS) and hand-held Doppler (HHD), waveform terminology remains highly variable and non-standardised across institutions. The Saint-Bonnet classification, proposed by the French College of Teachers in Vascular Medicine (CEMV), offers a structured eight-category morphological framework mapped to haemodynamic severity. Its evidence base and methodological quality have never been formally appraised. A scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). MEDLINE (Ovid) and Embase (Ovid) were searched from 1946 to November 2025. Studies describing, applying, validating, or evaluating the Saint-Bonnet classification were eligible. Data were extracted using a standardised form. Methodological quality was appraised using AGREE II (six domains) and AGREE-REX (three domains), independently by two reviewers (H.A. and F.A.). Seven studies met the inclusion criteria; all published between 2017 and 2022 from a single French vascular research group. The Saint-Bonnet classification achieved a categorisation rate of 98.2% across 1,033 waveforms, outperforming alternative systems. Inter-rater reliability was moderate (<i>κ</i> ≈ 0.55). Waveform grade independently correlated with maximal walking distance, and waveform-guided ankle-brachial index (ABI) selection achieved near-perfect agreement with guideline standards (<i>κ</i> up to 1.00). Automated neural network classification reached <i>κ</i> = 0.79, approaching expert agreement. AGREE II appraisal revealed high scores for Clarity of Presentation and Scope & Purpose (97% and 83%), but low scores for Rigour of Development and Applicability (44% and 40%). AGREE-REX demonstrated high Clinical Applicability and Implementability. The Saint-Bonnet classification is a promising and practical framework for Doppler waveform interpretation, with consistent findings across the available studies. Low AGREE II scores for Rigour of Development and Applicability reflect gaps in its documented development and reporting rather than evidence against its clinical performance. However, all supporting evidence originates from a single, non-independent French research group, and the classification has not undergone external validation; broader adoption should await independent, multicentre confirmation of these findings.