Limited performance questions retrospective use of quantitative flow ratio in coronary artery bypass grafting

Hannes Abfalterer1, Dominik Janker1, Lorenz Rüf1

  • 1Department of Cardiac Surgery, Medical University of Innsbruck, Innsbruck, Austria.

PubMed

Insights

Quantitative flow ratio (QFR) predicts arterial graft patency in coronary artery bypass grafting. However, retrospective QFR analysis showed low feasibility and poor diagnostic performance, limiting its clinical application.

Area of Science:

  • Cardiovascular Medicine
  • Interventional Cardiology
  • Medical Imaging Analysis

Background:

  • Arterial graft patency is crucial for long-term outcomes after coronary artery bypass grafting (CABG).
  • Hemodynamic assessment of coronary artery stenosis can impact graft survival.
  • Quantitative flow ratio (QFR) is a method to assess coronary artery stenosis hemodynamics.

Purpose of the Study:

  • To evaluate the association between QFR of native coronary target vessels and postoperative arterial graft patency.
  • To assess the feasibility and diagnostic performance of retrospective QFR analysis in patients with prior CABG.

Main Methods:

  • Retrospective analysis of 596 patients with prior CABG and at least one arterial graft.
  • Preoperative angiography used for retrospective QFR analysis of native coronary target vessels.
  • Coronary targets with QFR ≤0.80 defined as hemodynamically relevant; >0.80 as irrelevant.

Main Results:

  • Higher arterial graft patency rates observed for grafts anastomosed to coronary branches with QFR ≤0.80 (p=0.017).
  • QFR ≤0.80 was an independent predictor of arterial graft patency (HR: 0.475, p=0.015).
  • Retrospective QFR analysis had low feasibility (80.22% of target vessels not analysable) and poor diagnostic performance (AUC=0.595).

Conclusions:

  • While QFR ≤0.80 is associated with improved arterial graft patency, its retrospective application is limited by low feasibility and diagnostic performance.
  • Caution is advised when using retrospective QFR in similar datasets due to observed constraints.
Abstract

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