Rationale and design of the pullback pressure gradient (PPG) global registry
Copyright © 2023 Elsevier Inc. All rights reserved..
INTRODUCTION: Diffuse disease has been identified as one of the main reasons leading to low post-PCI fractional flow reserve (FFR) and residual angina after PCI. Coronary pressure pullbacks allow for the evaluation of hemodynamic coronary artery disease (CAD) patterns. The pullback pressure gradient (PPG) is a novel metric that quantifies the distribution and magnitude of pressure losses along the coronary artery in a focal-to-diffuse continuum.
AIM: The primary objective is to determine the predictive capacity of the PPG for post-PCI FFR.
METHODS: This prospective, large-scale, controlled, investigator-initiated, multicenter study is enrolling patients with at least 1 lesion in a major epicardial vessel with a distal FFR ≤ 0.80 intended to be treated by PCI. The study will include 982 subjects. A standardized physiological assessment will be performed pre-PCI, including the online calculation of PPG from FFR pullbacks performed manually. PPG quantifies the CAD pattern by combining several parameters from the FFR pullback curve. Post-PCI physiology will be recorded using a standardized protocol with FFR pullbacks. We hypothesize that PPG will predict optimal PCI results (post-PCI FFR ≥ 0.88) with an area under the ROC curve (AUC) ≥ 0.80. Secondary objectives include patient-reported and clinical outcomes in patients with focal vs. diffuse CAD defined by the PPG. Clinical follow-up will be collected for up to 36 months, and an independent clinical event committee will adjudicate events.
RESULTS: Recruitment is ongoing and is expected to be completed in the second half of 2023.
CONCLUSION: This international, large-scale, prospective study with pre-specified powered hypotheses will determine the ability of the preprocedural PPG index to predict optimal revascularization assessed by post-PCI FFR. In addition, it will evaluate the impact of PPG on treatment decisions and the predictive performance of PPG for angina relief and clinical outcomes.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:265 |
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| Enthalten in: |
American heart journal - 265(2023) vom: 25. Nov., Seite 170-179 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Munhoz, Daniel [VerfasserIn] |
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| Anmerkungen: |
Date Revised 12.10.2023 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.1016/j.ahj.2023.07.016 |
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| 100 | 1 | |a Munhoz, Daniel |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Rationale and design of the pullback pressure gradient (PPG) global registry |
| 264 | 1 | |c 2023 | |
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| 500 | |a Date Revised 12.10.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status Publisher | ||
| 520 | |a Copyright © 2023 Elsevier Inc. All rights reserved. | ||
| 520 | |a INTRODUCTION: Diffuse disease has been identified as one of the main reasons leading to low post-PCI fractional flow reserve (FFR) and residual angina after PCI. Coronary pressure pullbacks allow for the evaluation of hemodynamic coronary artery disease (CAD) patterns. The pullback pressure gradient (PPG) is a novel metric that quantifies the distribution and magnitude of pressure losses along the coronary artery in a focal-to-diffuse continuum | ||
| 520 | |a AIM: The primary objective is to determine the predictive capacity of the PPG for post-PCI FFR | ||
| 520 | |a METHODS: This prospective, large-scale, controlled, investigator-initiated, multicenter study is enrolling patients with at least 1 lesion in a major epicardial vessel with a distal FFR ≤ 0.80 intended to be treated by PCI. The study will include 982 subjects. A standardized physiological assessment will be performed pre-PCI, including the online calculation of PPG from FFR pullbacks performed manually. PPG quantifies the CAD pattern by combining several parameters from the FFR pullback curve. Post-PCI physiology will be recorded using a standardized protocol with FFR pullbacks. We hypothesize that PPG will predict optimal PCI results (post-PCI FFR ≥ 0.88) with an area under the ROC curve (AUC) ≥ 0.80. Secondary objectives include patient-reported and clinical outcomes in patients with focal vs. diffuse CAD defined by the PPG. Clinical follow-up will be collected for up to 36 months, and an independent clinical event committee will adjudicate events | ||
| 520 | |a RESULTS: Recruitment is ongoing and is expected to be completed in the second half of 2023 | ||
| 520 | |a CONCLUSION: This international, large-scale, prospective study with pre-specified powered hypotheses will determine the ability of the preprocedural PPG index to predict optimal revascularization assessed by post-PCI FFR. In addition, it will evaluate the impact of PPG on treatment decisions and the predictive performance of PPG for angina relief and clinical outcomes | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a Collet, Carlos |e verfasserin |4 aut | |
| 700 | 1 | |a Mizukami, Takuya |e verfasserin |4 aut | |
| 700 | 1 | |a Yong, Andy |e verfasserin |4 aut | |
| 700 | 1 | |a Leone, Antonio Maria |e verfasserin |4 aut | |
| 700 | 1 | |a Eftekhari, Ashkan |e verfasserin |4 aut | |
| 700 | 1 | |a Ko, Brian |e verfasserin |4 aut | |
| 700 | 1 | |a da Costa, Bruno R |e verfasserin |4 aut | |
| 700 | 1 | |a Berry, Colin |e verfasserin |4 aut | |
| 700 | 1 | |a Collison, Damien |e verfasserin |4 aut | |
| 700 | 1 | |a Perera, Divaka |e verfasserin |4 aut | |
| 700 | 1 | |a Christiansen, Evald Høj |e verfasserin |4 aut | |
| 700 | 1 | |a Rivero, Fernando |e verfasserin |4 aut | |
| 700 | 1 | |a Zimmermann, Frederik M |e verfasserin |4 aut | |
| 700 | 1 | |a Ando, Hirohiko |e verfasserin |4 aut | |
| 700 | 1 | |a Matsuo, Hitoshi |e verfasserin |4 aut | |
| 700 | 1 | |a Nakayama, Masafumi |e verfasserin |4 aut | |
| 700 | 1 | |a Escaned, Javier |e verfasserin |4 aut | |
| 700 | 1 | |a Sonck, Jeroen |e verfasserin |4 aut | |
| 700 | 1 | |a Sakai, Koshiro |e verfasserin |4 aut | |
| 700 | 1 | |a Adjedj, Julien |e verfasserin |4 aut | |
| 700 | 1 | |a Desta, Liyew |e verfasserin |4 aut | |
| 700 | 1 | |a van Nunen, Lokien X |e verfasserin |4 aut | |
| 700 | 1 | |a West, Nick E J |e verfasserin |4 aut | |
| 700 | 1 | |a Fournier, Stephane |e verfasserin |4 aut | |
| 700 | 1 | |a Storozhenko, Tatyana |e verfasserin |4 aut | |
| 700 | 1 | |a Amano, Tetsuya |e verfasserin |4 aut | |
| 700 | 1 | |a Engstrøm, Thomas |e verfasserin |4 aut | |
| 700 | 1 | |a Johnson, Thomas |e verfasserin |4 aut | |
| 700 | 1 | |a Shinke, Toshiro |e verfasserin |4 aut | |
| 700 | 1 | |a Biscaglia, Simone |e verfasserin |4 aut | |
| 700 | 1 | |a Fearon, William F |e verfasserin |4 aut | |
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| 700 | 1 | |a De Bruyne, Bernard |e verfasserin |4 aut | |
| 700 | 1 | |a Johnson, Nils P |e verfasserin |4 aut | |
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