Improved Diagnosis through Diastolic Hyperemia-Free Ratio (DFR) over Fractional Flow Reserve (FFR) in Intermediate Coronary Lesions.
CARDIOLOGY AND CARDIOVASCULAR MEDICINE 2023;
7:108-116. [PMID:
37554658 PMCID:
PMC10409495]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/10/2023]
Abstract
OBJECTIVES
To compare the fractional flow reserve (FFR) and diastolic hyperemia-free ratio (DFR) measurements in a population with intermediate coronary artery stenosis and improve the diagnosis.
BACKGROUND
Visual assessment of coronary artery stenosis severity, particularly in intermediate lesions, is prone to errors in decision-making. FFR provides a reliable assessment of functional severity in these cases but requires hyperemia induction by adenosine, which has side effects and increased cost. DFR is a novel hyperemia-independent index, which could be used as an alternative to adenosine-based hyperemia induction.
METHODS AND RESULTS
Between September 2019 to March 2020, 25 patients with 38 intermediate coronary stenotic lesions were included in the study. All patients underwent assessment of whole cycle Pd/Pa (ratio of distal coronary pressure to proximal aortic pressure), DFR and FFR. Mean whole cycle Pd/Pa, DFR and FFR were 0.93±0.06, 0.88±0.09, and 0.85±0.08, respectively. A significant positive correlation between DFR and FFR [r = 0.74; p<0.001] was observed. Receiver operating characteristic analysis showed an area under the curve of 0.90. DFR-only strategy with a treatment cut-off of ≤0.89 showed a diagnostic agreement with the FFR-only strategy in 74% of lesions, with a sensitivity of 54%, specificity of 82%, a positive predictive value of 60%, and a negative predictive value of 79%.
CONCLUSIONS
Real-time DFR measurements show a clinically reliable correlation with FFR. Hence, using DFR is likely to avoid adenosine administration as well as reduce the cost and procedural time. Further studies with a larger sample size would be ideal to evaluate specific cut-off values and endpoints.
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