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Journal of vascular surgery

July 13, 2026 · via Europe PMC

Inframalleolar status according to the Global Limb Anatomic Staging System is associated with wound recurrence after complete wound healing in patients with chronic limb-threatening ischemia.

Yanagiuchi T, Tokuda T, Yoshioka N, +7 more, LEADers PAD investigators.

Observational StudyAbstract only — full text under license

AI summary — for doctors, generated from the abstract only

Poor inframalleolar arterial status on GLASS was the only independent predictor of wound recurrence after complete healing in CLTI patients treated endovascularly.

What was studied

Multicenter retrospective study of 478 limbs with CLTI and tissue loss that healed completely after endovascular therapy including infrapopliteal intervention (from 1,094 treated limbs), analyzed with Kaplan-Meier and Cox models.

Key findings

  • Overall wound recurrence was 18.8%, at a mean of 7.7 months.
  • Recurrence at 12 months rose stepwise by inframalleolar grade: 11.8%, 19.3%, and 29.6% in grades 0, 1 and 2.
  • Inframalleolar GLASS grade was the only independent predictor.

Clinical relevance

Distal anatomy helps identify healed patients who need closer surveillance for recurrent ulceration.

Who should care

Cardiothoracic & Vascular SurgeryGeneral SurgeryVascular Surgery

Limitations

Retrospective design from a limited period with short follow-up, and the abstract does not give adjusted hazard ratios.

Tailor foot surveillance and preventive care intensity to inframalleolar disease grade after wound healing.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

Abstract

Objective

To determine the predictors of wound recurrence after complete wound healing in patients with chronic limb-threatening ischemia (CLTI) who underwent endovascular therapy (EVT), with particular focus on infrapopliteal (IP) and inframalleolar (IM) arterial status.

Methods

This multicenter retrospective study assessed de novo limbs with CLTI and tissue loss treated with EVT including IP artery intervention from March 2021 to December 2023. Among 1094 limbs in 917 patients treated with EVT, 478 limbs that achieved complete wound healing were included in the final analysis. The Kaplan-Meier method was used to estimate the wound recurrence rate after complete wound healing. Cox proportional hazards regression models were used to assess the association between baseline characteristics, including IP and IM arterial anatomic severity, and wound recurrence.

Results

The overall wound recurrence rate was 18.8%. The mean time to wound recurrence was 7.7 ± 7.4 months. The cumulative wound recurrence rate increased stepwise according to IM grade in the Global Limb Anatomic Staging System (GLASS). The estimated wound recurrence rates at 12 months were 11.8% ± 4.2%, 19.3% ± 2.8%, and 29.6% ± 5.3% in IM grades 0, 1, and 2, respectively, with a significant difference among the groups (log-rank, P < .001). Multivariable analysis revealed that IM grade in the GLASS was the only independent predictor of wound recurrence after complete wound healing (hazard ratio, 1.65 per 1-grade increase; 95% confidence interval, 1.13-2.41; P = .009).

Conclusions

In patients with CLTI who achieved complete wound healing after EVT, IM grade in the GLASS was the only independent predictor of wound recurrence. Poor IM arterial status may be an important determinant of wound durability after complete wound healing.

DOI

10.1016/j.jvs.2026.07.005

PMID

42442642

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

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