Literature DB >> 27517648

When should fractional flow reserve be performed to assess the significance of borderline coronary artery lesions: Derivation of a simplified scoring system.

Fadi A Matar1, Shayan Falasiri2, Charles B Glover2, Asma Khaliq2, Calvin C Leung2, Jad Mroue2, George Ebra2.   

Abstract

OBJECTIVES: To derive a simplified scoring system (SSS) that can assist in selecting patients who would benefit from the application of fractional flow reserve (FFR).
BACKGROUND: Angiographers base decisions to perform FFR on their interpretation of % diameter stenosis (DS), which is subject to variability. Recent studies have shown that the amount of myocardium at jeopardy is an important factor in determining the degree of hemodynamic compromise.
METHODS: We conducted a retrospective multivariable analysis to identify independent predictors of hemodynamic compromise in 289 patients with 317 coronary vessels undergoing FFR. A SSS was derived using the odds ratios as a weighted factor. The receiver operator characteristics curve was used to identify the optimal cutoff (≥3) to discern a functionally significant lesion (FFR≤0.8).
RESULTS: Male gender, left anterior descending artery apical wrap, disease proximal to lesion, minimal lumen diameter and % DS predicted abnormal FFR (≤0.8) and lesion location in the left circumflex predicted a normal FFR. Using a cutoff score of ≥3 on the SSS, a specificity of 90.4% (95% CI: 83.0-95.3) and a sensitivity of 38.0% (95% CI: 31.5-44.9) was generated with a positive predictive value of 89.0% (95% CI: 80.7%-94.6%) and negative predictive value of 41.6% (95% CI: 35.1%-48.3%).
CONCLUSIONS: The decision to use FFR should be based not only on the % DS but also the size of the myocardial mass jeopardized. A score of ≥3 on the SSS should prompt further investigation with a pressure wire.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Coronary angiography; Coronary artery disease; Fractional flow reserve; Percutaneous coronary intervention

Mesh:

Year:  2016        PMID: 27517648     DOI: 10.1016/j.ijcard.2016.07.171

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  2 in total

1.  Diagnostic performance of machine-learning-based computed fractional flow reserve (FFR) derived from coronary computed tomography angiography for the assessment of myocardial ischemia verified by invasive FFR.

Authors:  Xiuhua Hu; Minglei Yang; Lu Han; Yujiao Du
Journal:  Int J Cardiovasc Imaging       Date:  2018-07-30       Impact factor: 2.357

2.  Clinical prediction models of fractional flow reserve: an exploration of the current evidence and appraisal of model performance.

Authors:  Wenjie Zuo; Rui Zhang; Mingming Yang; Zhenjun Ji; Yanru He; Yamin Su; Yangyang Qu; Zaixiao Tao; Genshan Ma
Journal:  Quant Imaging Med Surg       Date:  2021-06
  2 in total

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