Quantitative flow ratio and fractional flow reserve mismatch – clinical and biochemical predictors of measurement discrepancy

Martyna Zaleska; Lukasz Koltowski; Jakub Maksym; Aleksandra Chabior; Aleksandra Pohadajło; Mateusz Soliński; Mariusz Tomaniak; Grzegorz Opolski; Janusz Kochman

doi:10.5114/aic.2019.87883

Abstract

3/2019 vol. 15

Original paper

Quantitative flow ratio and fractional flow reserve mismatch – clinical and biochemical predictors of measurement discrepancy

Martyna Zaleska ¹

,

Lukasz Koltowski ¹

,

Jakub Maksym ¹

,

Aleksandra K. Chabior ¹

,

Aleksandra Pohadajło ¹

,

Mateusz Soliński ²

,

Mariusz Tomaniak ¹

,

Grzegorz Opolski ¹

,

Janusz Kochman ¹

First Chair and Department of Cardiology, Warsaw Medical University, Warsaw, Poland
Faculty of Physics, Warsaw University of Technology, Warsaw, Poland

Adv Interv Cardiol 2019; 15, 3 (57): 301–307

DOI: https://doi.org/10.5114/aic.2019.87883

Online publish date: 2019/09/18

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AMA

Zaleska M, Koltowski L, Maksym J, et al. Quantitative flow ratio and fractional flow reserve mismatch – clinical and biochemical predictors of measurement discrepancy. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej. 2019;15(3):301-307. doi:10.5114/aic.2019.87883.

APA

Zaleska, M., Koltowski, L., Maksym, J., Chabior, A. K., Pohadajło, A., & Soliński, M. et al. (2019). Quantitative flow ratio and fractional flow reserve mismatch – clinical and biochemical predictors of measurement discrepancy. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, 15(3), 301-307. https://doi.org/10.5114/aic.2019.87883

Chicago

Zaleska, Martyna, Lukasz Koltowski, Jakub Maksym, Aleksandra K Chabior, Aleksandra Pohadajło, Mateusz Soliński, and Mariusz Tomaniak et al. 2019. "Quantitative flow ratio and fractional flow reserve mismatch – clinical and biochemical predictors of measurement discrepancy". Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej 15 (3): 301-307. doi:10.5114/aic.2019.87883.

Harvard

Zaleska, M., Koltowski, L., Maksym, J., Chabior, A., Pohadajło, A., Soliński, M., Tomaniak, M., Opolski, G., and Kochman, J. (2019). Quantitative flow ratio and fractional flow reserve mismatch – clinical and biochemical predictors of measurement discrepancy. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, 15(3), pp.301-307. https://doi.org/10.5114/aic.2019.87883

MLA

Zaleska, Martyna et al. "Quantitative flow ratio and fractional flow reserve mismatch – clinical and biochemical predictors of measurement discrepancy." Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, vol. 15, no. 3, 2019, pp. 301-307. doi:10.5114/aic.2019.87883.

Vancouver

Zaleska M, Koltowski L, Maksym J, Chabior A, Pohadajło A, Soliński M et al. Quantitative flow ratio and fractional flow reserve mismatch – clinical and biochemical predictors of measurement discrepancy. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej. 2019;15(3):301-307. doi:10.5114/aic.2019.87883.

Introduction

Fractional flow reserve (FFR) is the gold standard for functional assessment of intermediate lesions. However, assessing a stenosis with pressure wire prolongs the procedure, increases costs and carries a risk of procedure-related adverse events. Quantitative flow ratio (QFR) is a wire-free method for detection of significant ischemia based on 3D reconstruction of angiographic images and TIMI frame count.

Aim

To evaluate the influence of laboratory and clinical variables on QFR-FFR mismatch.

Material and methods

We retrospectively computed QFR (Medis Suite XA/QAngio XA 3D/QFR, Medis/Netherlands) in suitable cases with corresponding FFR (PressureWire, Abbott, US). Uni-/multivariate analysis was performed to identify clinical and biochemical predictors of QFR-FFR mismatch.

Results

Two hundred six lesions (196 patients, 76% male, mean age: 66.4 ±10.1 years) were included. Chronic kidney disease (CKD) and insulin-treated diabetes mellitus (ITDM) were associated with significantly larger differences between QFR and FFR values (–0.062 ±0.031 vs. –0.025 ±0.068; p = 0.027 and –0.059 ±0.07 vs. –0.027 ±0.074; p = 0.039; respectively). CKD was associated with a decrease of diagnostic efficiency (AUC = 0.67, 95% CI: 0.46–0.88 vs. AUC = 0.89, 95% CI: 0.84–0.94, p = 0.05). For biochemical variables only weak Spearman correlations were identified for hemoglobin concentration (r = –0.18) and hematocrit levels (r = –0.18).