Diagnostic Ability of the Japanese Version of the High Bleeding Risk Criteria in Patients With Lower Extremity

Tadahiro Matsumoto1, Yuichi Saito2, Yuji Ohno3

  • 1Department of Cardiology, Chibaken Saiseikai Narashino Hospital.

Insights

The Japanese high bleeding risk (J-HBR) criteria effectively stratified risks in patients with lower extremity peripheral arterial disease (LEAD) undergoing endovascular treatment (EVT). While not differentiating bleeding risk, J-HBR predicted major adverse cardiovascular and limb events (MACLE) in LEAD patients.

Area of Science:

  • Cardiovascular Medicine
  • Vascular Surgery
  • Interventional Cardiology

Background:

  • The Japanese high bleeding risk (J-HBR) criteria were developed to identify patients at high bleeding risk (HBR) post-percutaneous coronary intervention.
  • The utility of J-HBR criteria in patients with lower extremity peripheral arterial disease (LEAD) remains unestablished.

Purpose of the Study:

  • To evaluate the diagnostic ability and risk stratification capability of the J-HBR criteria in patients with LEAD undergoing endovascular treatment (EVT).

Main Methods:

  • A multicenter registry study involving 818 patients with LEAD undergoing EVT.
  • Patients were categorized based on J-HBR criteria (≥2.0 points) versus lower scores (1.0-1.5 points), with LEAD itself considered a major criterion.
  • Primary endpoints included major bleeding events and major adverse cardiovascular and limb events (MACLE).

Main Results:

  • The majority of patients (83.5%) had LEAD with additional J-HBR criteria.
  • No significant difference in major bleeding events was observed between groups.
  • Patients with LEAD and additional J-HBR criteria exhibited a higher risk of MACLE (12.4% vs. 5.9%; P=0.03).
  • Both major bleeding and MACLE risks increased progressively with more J-HBR criteria.

Conclusions:

  • The J-HBR criteria demonstrated effectiveness in stratifying ischemic and bleeding risks among patients with LEAD undergoing EVT.
  • This risk-prediction model shows potential utility for managing patients with LEAD.
Abstract

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