Validation of virtual fractional flow reserve pullback curves.

PCI angina angiography‐derived fractional flow reserve coronary artery disease fractional flow reserve

Journal

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
ISSN: 1522-726X
Titre abrégé: Catheter Cardiovasc Interv
Pays: United States
ID NLM: 100884139

Informations de publication

Date de publication:
29 Sep 2024
Historique:
revised: 25 08 2024
received: 06 03 2024
accepted: 02 09 2024
medline: 29 9 2024
pubmed: 29 9 2024
entrez: 29 9 2024
Statut: aheadofprint

Résumé

Angiography-derived fractional flow reserve (virtual FFR) has shown excellent diagnostic performance compared with wire-based FFR. However, virtual FFR pullback curves have not been validated yet. To validate the accuracy of virtual FFR pullback curves compared to wire-based FFR pullbacks and to assess their clinical utility using patient-reported outcomes. Pooled analysis of two prospective studies, including patients with hemodynamically significant (FFR ≤ 0.80) coronary artery disease (CAD). Virtual and wire-based FFR pullbacks were compared to assess the accuracy of virtual pullbacks to characterize CAD as focal or diffuse. Pullbacks were analyzed visually and quantitatively using the pullback pressure gradient (PPG). Patients underwent PCI, and the Seattle Angina Questionnaire (SAQ) was administered at 3-month follow-up. A total of 298 patients (300 vessels) with both virtual and wire-based pullbacks who underwent PCI were included in the analysis. The mean age was 61.8 ± 8.8, and 15% were female. The agreement on the visual adjudication of the CAD pattern was fair (Cohen's Kappa: 0.31, 95% confidence interval: 0.18-0.45). The mean PPG were 0.65 ± 0.18 from virtual pullbacks and 0.65 ± 0.13 from wire-based pullbacks (r = 0.68, mean difference 0, limits of agreement -0.27 to 0.28). At follow-up, patients with high virtual PPG (>0.67) had higher SAQ angina frequency scores (i.e., less angina) than those with low virtual PPG (SAQ scores 92.0 ± 14.3 vs. 85.5 ± 23.1, p = 0.022). Virtual FFR pullback curves showed moderate agreement with wire-based FFR pullbacks. Nonetheless, patients with focal disease based on virtual PPG reported greater improvement in angina after PCI.

Sections du résumé

BACKGROUND BACKGROUND
Angiography-derived fractional flow reserve (virtual FFR) has shown excellent diagnostic performance compared with wire-based FFR. However, virtual FFR pullback curves have not been validated yet.
OBJECTIVES OBJECTIVE
To validate the accuracy of virtual FFR pullback curves compared to wire-based FFR pullbacks and to assess their clinical utility using patient-reported outcomes.
METHODS METHODS
Pooled analysis of two prospective studies, including patients with hemodynamically significant (FFR ≤ 0.80) coronary artery disease (CAD). Virtual and wire-based FFR pullbacks were compared to assess the accuracy of virtual pullbacks to characterize CAD as focal or diffuse. Pullbacks were analyzed visually and quantitatively using the pullback pressure gradient (PPG). Patients underwent PCI, and the Seattle Angina Questionnaire (SAQ) was administered at 3-month follow-up.
RESULTS RESULTS
A total of 298 patients (300 vessels) with both virtual and wire-based pullbacks who underwent PCI were included in the analysis. The mean age was 61.8 ± 8.8, and 15% were female. The agreement on the visual adjudication of the CAD pattern was fair (Cohen's Kappa: 0.31, 95% confidence interval: 0.18-0.45). The mean PPG were 0.65 ± 0.18 from virtual pullbacks and 0.65 ± 0.13 from wire-based pullbacks (r = 0.68, mean difference 0, limits of agreement -0.27 to 0.28). At follow-up, patients with high virtual PPG (>0.67) had higher SAQ angina frequency scores (i.e., less angina) than those with low virtual PPG (SAQ scores 92.0 ± 14.3 vs. 85.5 ± 23.1, p = 0.022).
CONCLUSION CONCLUSIONS
Virtual FFR pullback curves showed moderate agreement with wire-based FFR pullbacks. Nonetheless, patients with focal disease based on virtual PPG reported greater improvement in angina after PCI.

Identifiants

pubmed: 39342486
doi: 10.1002/ccd.31222
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024 Wiley Periodicals LLC.

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Auteurs

Ruiko Seki (R)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.

Damien Collison (D)

Department of cardiology, Golden Jubilee National Hospital, Glasgow, UK.
School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, UK.

Kazumasa Ikeda (K)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.

Jeroen Sonck (J)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.

Daniel Munhoz (D)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Department of Advanced Biomedical Sciences, University Federico II, Naples, Italy.

Dario Tino Bertolone (DT)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Department of Advanced Biomedical Sciences, University Federico II, Naples, Italy.

Brian Ko (B)

Monash Cardiovascular Research Centre, Monash University and Monash Heart, Monash Health, Clayton, Victoria, Australia.

Michael Maeng (M)

Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark.
Department of Clinical Medicine, Health, Aarhus University, Aarhus, Denmark.

Hiromasa Otake (H)

Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe, Japan.

Bon-Kon Koo (BK)

Department of Internal Medicine and Cardiovascular Center, Seoul National University Hospital, Seoul, South Korea.

Tatyana Storozhenko (T)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
L.T. Malaya Therapy National Institute NAMSU, Kharkiv, Ukraine.

Frederic Bouisset (F)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Department of Cardiology, Toulouse Rangueil University Hospital, Toulouse, France.

Marta Belmonte (M)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Department of Advanced Biomedical Sciences, University Federico II, Naples, Italy.

Attilio Leone (A)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Department of Advanced Biomedical Sciences, University Federico II, Naples, Italy.

Monika Shumkova (M)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.

Tom J Ford (TJ)

Department of cardiology, Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, Australia.

Thabo Mahendiran (T)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Department of Cardiology, University Hospital of Lausanne, Lausanne, Switzerland.

Colin Berry (C)

Department of cardiology, Golden Jubilee National Hospital, Glasgow, UK.
School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, UK.

Bernard De Bruyne (B)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Department of Cardiology, University Hospital of Lausanne, Lausanne, Switzerland.

Keith Oldroyd (K)

School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, UK.

Koshiro Sakai (K)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Division of Cardiology, Department of Medicine, Showa University School of Medicine, Tokyo, Japan.
Department of Cardiology, St Francis Hospital and Heart Center, Roslyn, New York, USA.

Takuya Mizukami (T)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Division of Clinical Pharmacology, Department of Pharmacology, Showa University, Tokyo, Japan.

Carlos Collet (C)

Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.

Classifications MeSH