Literature DB >> 28853190

Diagnostic accuracy of instantaneous wave free-ratio in clinical practice.

Wern Yew Ding1, Satheesh Nair1, Clare Appleby1.   

Abstract

AIMS: To evaluate the correlation between iFR and FFR in real-world clinical practice. METHODS AND
RESULTS: Retrospective, single-centre study of 229 consecutive pressure-wire studies (np  = 158). Real-time iFR and FFR measurements were performed for angiographically borderline stenoses. Functionally significant stenoses were defined as iFR <0.86 or FFR ≤0.80. An iFR between 0.86 and 0.93 was considered within the grey zone (Hybrid approach). Median iFR and FFR (IQR) were 0.92 (0.87-0.95) and 0.83 (0.76-0.89), respectively. Pearson's correlation coefficient was 0.75 (P < 0.001). Bland-Altman plot showed a mean difference between iFR and FFR that remained consistent throughout the range of values. The optimal iFR cutoff was 0.91-sensitivity 80%, specificity 82% with ROC area under curve of 89%. Using the Hybrid iFR-FFR strategy, we demonstrated high accuracy of iFR results-sensitivity 95%, specificity 96%, PPV 95%, and NPV 96%. In addition, this method would have avoided adenosine in 56% of patients. Mean follow-up period was 17.2 (±3.4) months. All-cause mortality was 3.2% (np  = 5) and repeat intervention was required in six lesions (2.6%).
CONCLUSIONS: This study demonstrates that iFR is a valuable adjunct to FFR using the Hybrid iFR-FFR strategy in a real-world population. The use of adenosine may be avoided in about half the cases.
© 2017, Wiley Periodicals, Inc.

Entities:  

Keywords:  fractional flow reserve; functional testing; instantaneous wave-free ratio; pressure wire studies

Mesh:

Year:  2017        PMID: 28853190     DOI: 10.1111/joic.12422

Source DB:  PubMed          Journal:  J Interv Cardiol        ISSN: 0896-4327            Impact factor:   2.279


  2 in total

1.  Meta-Analysis of Diagnostic Performance of Instantaneous Wave-Free Ratio versus Quantitative Flow Ratio for Detecting the Functional Significance of Coronary Stenosis.

Authors:  Wenjie Zuo; Mingming Yang; Yifan Chen; Aiming Xie; Lijuan Chen; Genshan Ma
Journal:  Biomed Res Int       Date:  2019-04-18       Impact factor: 3.411

2.  Additional Value of Machine-Learning Computed Tomographic Angiography-Based Fractional Flow Reserve Compared to Standard Computed Tomographic Angiography.

Authors:  Dirk Lossnitzer; Leonard Chandra; Marlon Rutsch; Tobias Becher; Daniel Overhoff; Sonja Janssen; Christel Weiss; Martin Borggrefe; Ibrahim Akin; Stefan Pfleger; Stefan Baumann
Journal:  J Clin Med       Date:  2020-03-03       Impact factor: 4.241

  2 in total

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