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Panminerva Med 2021 June;63(2):206-13

DOI: 10.23736/S0031-0808.20.04202-0

Copyright © 2020 EDIZIONI MINERVA MEDICA

language: English

A novel algorithm for the computation of the diastolic pressure ratio in the invasive assessment of the functional significance of coronary artery disease

Francesco VERSACI 1, Micaela CONTE 2, Marcel VAN’T VEER 3, Sébastien LALANCETTE 4, Keith OLDROYD 5, Simone CALCAGNO 1, Giuseppe BIONDI ZOCCAI 6, 7

1 Department of Cardiology, Santa Maria Goretti Hospital, Latina, Italy; 2 Department of Cardiology, Clinic Saint Jean, Brussels, Belgium; 3 Catharina Hospital, Eindhoven, the Netherlands; 4 Opsens Medical, Québec, ON, Canada; 5 West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Glasgow, UK; 6 Department of Medical-Surgical Sciences and Biotechnologies, Sapienza University, Latina, Italy; 7 Mediterranea Cardiocentro, Naples, Italy



BACKGROUND: Invasive functional assessment is a mainstay in the management of patients with coronary artery disease (CAD), but there is uncertainty on the comparative accuracy of diagnostic indices of functional significance. We aimed to validate the diagnostic performance of a novel non-hyperemic diastolic pressure ratio (dPR).
METHODS: We performed a retrospective analysis including two separate registries (VERIFY 2, Latina, Italy) of patients in whom functional indices were measured for lesions with angiographically moderate severity. On top of fractional flow reserve, distal coronary pressure (Pd)/aortic pressure (Pa) ratio, instantaneous wave-free ratio (iFR) and diastolic pressure ratio (dPR) were computed using a novel dedicated algorithm over 4 consecutive beats. Agreement/discrepancy between indexes was appraised Bland-Altman analysis, area under the receiver operating characteristic curve (AUC), and unsupervised machine learning.
RESULTS: A total of 525 lesions from 479 patients were included. The novel dPR was highly correlated with iFR (R2=0.99, P<0.001), with a mean difference of -0.004±0.014. The diagnostic performance of dPR (best cutoff value: ≤0.89) against iFR was as follows: accuracy =96%; sensitivity =94%; specificity =97%; positive-predictive value =94%; and negative-predictive value =96%. Additionally, AUC to predict iFR≤0.89 was 0.99, which was significantly higher than that of Pd/Pa (0.97, P<0.001). In the iFR range of 0.85-0.93 (“grey zone”), the diagnostic performance was well maintained (accuracy =91%; sensitivity =87%; specificity =93%; and AUC=0.96). Results were supported also by unsupervised learning analysis.
CONCLUSIONS: This multicenter registry suggests this novel dPR algorithm provides results that are numerically equivalent to iFR. Pending further studies, physicians may consider using this novel dPR algorithm to gauge the functional significance of a coronary lesion.


KEY WORDS: Coronary artery disease; Fractional flow reserve, myocardial; Algorithms

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