JOURNAL ARTICLE

A Systematic Review of Interventions Designed to Reduce Surgical Site Infection in Patients Who Undergo Transmetatarsal Amputation.

  • Published In: Vascular & Endovascular Surgery, 2026, v. 60, n. 5. P. 411 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Jess, Rebecca; Das, Kieran; Alawattegama, Lakna Harindi; Al-Saadi, Nina; Bosanquet, David; Chetter, Ian; Fabre, Ismay; Garnham, Andrew; Gwilym, Brenig; Hitchman, Louise; Hughes, Terry; Long, Judith; Magill, Laura; Pinkney, Thomas; Popplewell, Matthew; Wall, Michael 3 of 3

Abstract

This article systematically reviews interventions aimed at reducing surgical site infection (SSI) following transmetatarsal amputation (TMA) in patients with peripheral arterial disease (PAD) or diabetes-related foot complications. The review included five studies (two randomized controlled trials and three observational) covering 378 TMAs and interventions such as prolonged post-operative antibiotics, antibiotic-impregnated beads, negative pressure wound therapy (NPWT), and skin preparation methods. Findings suggest that prolonged post-operative antibiotics and NPWT may reduce SSI incidence and promote faster wound healing, while antibiotic beads showed mixed results with higher SSI rates but reduced wound breakdown. Due to limited and heterogeneous data, the authors recommend further high-quality trials to clarify the clinical and cost-effectiveness of these interventions.

Additional Information

  • Source:Vascular & Endovascular Surgery. 2026/07, Vol. 60, Issue 5, p411
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2026
  • ISSN:1538-5744
  • DOI:10.1177/15385744261421787
  • Accession Number:193276595
  • Copyright Statement:Copyright of Vascular & Endovascular Surgery is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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