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Trans-lesional fractional flow reserve gradient as derived from coronary CT improves patient management: ADVANCE registry(☆)

BACKGROUND: The role of change in fractional flow reserve derived from CT (FFR(CT)) across coronary stenoses (ΔFFR(CT)) in guiding downstream testing in patients with stable coronary artery disease (CAD) is unknown. OBJECTIVES: To investigate the incremental value of ΔFFR(CT) in predicting early rev...

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Autores principales: Takagi, Hidenobu, Leipsic, Jonathon A., McNamara, Noah, Martin, Isabella, Fairbairn, Timothy A., Akasaka, Takashi, Nørgaard, Bjarne L., Berman, Daniel S., Chinnaiyan, Kavitha, Hurwitz-Koweek, Lynne M., Pontone, Gianluca, Kawasaki, Tomohiro, Sand, Niels Peter Rønnow, Jensen, Jesper M., Amano, Tetsuya, Poon, Michael, Øvrehus, Kristian A., Sonck, Jeroen, Rabbat, Mark G., Mullen, Sarah, De Bruyne, Bernard, Rogers, Campbell, Matsuo, Hitoshi, Bax, Jeroen J., Douglas, Pamela S., Patel, Manesh R., Nieman, Koen, Ihdayhid, Abdul Rahman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9719736/
https://www.ncbi.nlm.nih.gov/pubmed/34518113
http://dx.doi.org/10.1016/j.jcct.2021.08.003
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author Takagi, Hidenobu
Leipsic, Jonathon A.
McNamara, Noah
Martin, Isabella
Fairbairn, Timothy A.
Akasaka, Takashi
Nørgaard, Bjarne L.
Berman, Daniel S.
Chinnaiyan, Kavitha
Hurwitz-Koweek, Lynne M.
Pontone, Gianluca
Kawasaki, Tomohiro
Sand, Niels Peter Rønnow
Jensen, Jesper M.
Amano, Tetsuya
Poon, Michael
Øvrehus, Kristian A.
Sonck, Jeroen
Rabbat, Mark G.
Mullen, Sarah
De Bruyne, Bernard
Rogers, Campbell
Matsuo, Hitoshi
Bax, Jeroen J.
Douglas, Pamela S.
Patel, Manesh R.
Nieman, Koen
Ihdayhid, Abdul Rahman
author_facet Takagi, Hidenobu
Leipsic, Jonathon A.
McNamara, Noah
Martin, Isabella
Fairbairn, Timothy A.
Akasaka, Takashi
Nørgaard, Bjarne L.
Berman, Daniel S.
Chinnaiyan, Kavitha
Hurwitz-Koweek, Lynne M.
Pontone, Gianluca
Kawasaki, Tomohiro
Sand, Niels Peter Rønnow
Jensen, Jesper M.
Amano, Tetsuya
Poon, Michael
Øvrehus, Kristian A.
Sonck, Jeroen
Rabbat, Mark G.
Mullen, Sarah
De Bruyne, Bernard
Rogers, Campbell
Matsuo, Hitoshi
Bax, Jeroen J.
Douglas, Pamela S.
Patel, Manesh R.
Nieman, Koen
Ihdayhid, Abdul Rahman
author_sort Takagi, Hidenobu
collection PubMed
description BACKGROUND: The role of change in fractional flow reserve derived from CT (FFR(CT)) across coronary stenoses (ΔFFR(CT)) in guiding downstream testing in patients with stable coronary artery disease (CAD) is unknown. OBJECTIVES: To investigate the incremental value of ΔFFR(CT) in predicting early revascularization and improving efficiency of catheter laboratory utilization. MATERIALS: Patients with CAD on coronary CT angiography (CCTA) were enrolled in an international multicenter registry. Stenosis severity was assessed as per CAD-Reporting and Data System (CAD-RADS), and lesion-specific FFR(CT) was measured 2 cm distal to stenosis. ΔFFR(CT) was manually measured as the difference of FFR(CT) across visible stenosis. RESULTS: Of 4730 patients (66 ± 10 years; 34% female), 42.7% underwent ICA and 24.7% underwent early revascularization. ΔFFR(CT) remained an independent predictor for early revascularization (odds ratio per 0.05 increase [95% confidence interval], 1.31 [1.26–1.35]; p < 0.001) after adjusting for risk factors, stenosis features, and lesion-specific FFR(CT). Among the 3 models (model 1: risk factors + stenosis type and location + CAD-RADS; model 2: model 1 + FFR(CT); model 3: model 2 + ΔFFR(CT)), model 3 improved discrimination compared to model 2 (area under the curve, 0.87 [0.86–0.88] vs 0.85 [0.84–0.86]; p < 0.001), with the greatest incremental value for FFR(CT) 0.71–0.80. ΔFFR(CT) of 0.13 was the optimal cut-off as determined by the Youden index. In patients with CAD-RADS ≥3 and lesion-specific FFR(CT) ≤0.8, a diagnostic strategy incorporating ΔFFR(CT) >0.13, would potentially reduce ICA by 32.2% (1638–1110, p < 0.001) and improve the revascularization to ICA ratio from 65.2% to 73.1%. CONCLUSIONS: ΔFFR(CT) improves the discrimination of patients who underwent early revascularization compared to a standard diagnostic strategy of CCTA with FFR(CT), particularly for those with FFR(CT) 0.71–0.80. ΔFFR(CT) has the potential to aid decision-making for ICA referral and improve efficiency of catheter laboratory utilization.
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spelling pubmed-97197362022-12-04 Trans-lesional fractional flow reserve gradient as derived from coronary CT improves patient management: ADVANCE registry(☆) Takagi, Hidenobu Leipsic, Jonathon A. McNamara, Noah Martin, Isabella Fairbairn, Timothy A. Akasaka, Takashi Nørgaard, Bjarne L. Berman, Daniel S. Chinnaiyan, Kavitha Hurwitz-Koweek, Lynne M. Pontone, Gianluca Kawasaki, Tomohiro Sand, Niels Peter Rønnow Jensen, Jesper M. Amano, Tetsuya Poon, Michael Øvrehus, Kristian A. Sonck, Jeroen Rabbat, Mark G. Mullen, Sarah De Bruyne, Bernard Rogers, Campbell Matsuo, Hitoshi Bax, Jeroen J. Douglas, Pamela S. Patel, Manesh R. Nieman, Koen Ihdayhid, Abdul Rahman J Cardiovasc Comput Tomogr Article BACKGROUND: The role of change in fractional flow reserve derived from CT (FFR(CT)) across coronary stenoses (ΔFFR(CT)) in guiding downstream testing in patients with stable coronary artery disease (CAD) is unknown. OBJECTIVES: To investigate the incremental value of ΔFFR(CT) in predicting early revascularization and improving efficiency of catheter laboratory utilization. MATERIALS: Patients with CAD on coronary CT angiography (CCTA) were enrolled in an international multicenter registry. Stenosis severity was assessed as per CAD-Reporting and Data System (CAD-RADS), and lesion-specific FFR(CT) was measured 2 cm distal to stenosis. ΔFFR(CT) was manually measured as the difference of FFR(CT) across visible stenosis. RESULTS: Of 4730 patients (66 ± 10 years; 34% female), 42.7% underwent ICA and 24.7% underwent early revascularization. ΔFFR(CT) remained an independent predictor for early revascularization (odds ratio per 0.05 increase [95% confidence interval], 1.31 [1.26–1.35]; p < 0.001) after adjusting for risk factors, stenosis features, and lesion-specific FFR(CT). Among the 3 models (model 1: risk factors + stenosis type and location + CAD-RADS; model 2: model 1 + FFR(CT); model 3: model 2 + ΔFFR(CT)), model 3 improved discrimination compared to model 2 (area under the curve, 0.87 [0.86–0.88] vs 0.85 [0.84–0.86]; p < 0.001), with the greatest incremental value for FFR(CT) 0.71–0.80. ΔFFR(CT) of 0.13 was the optimal cut-off as determined by the Youden index. In patients with CAD-RADS ≥3 and lesion-specific FFR(CT) ≤0.8, a diagnostic strategy incorporating ΔFFR(CT) >0.13, would potentially reduce ICA by 32.2% (1638–1110, p < 0.001) and improve the revascularization to ICA ratio from 65.2% to 73.1%. CONCLUSIONS: ΔFFR(CT) improves the discrimination of patients who underwent early revascularization compared to a standard diagnostic strategy of CCTA with FFR(CT), particularly for those with FFR(CT) 0.71–0.80. ΔFFR(CT) has the potential to aid decision-making for ICA referral and improve efficiency of catheter laboratory utilization. 2022 2021-09-02 /pmc/articles/PMC9719736/ /pubmed/34518113 http://dx.doi.org/10.1016/j.jcct.2021.08.003 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Takagi, Hidenobu
Leipsic, Jonathon A.
McNamara, Noah
Martin, Isabella
Fairbairn, Timothy A.
Akasaka, Takashi
Nørgaard, Bjarne L.
Berman, Daniel S.
Chinnaiyan, Kavitha
Hurwitz-Koweek, Lynne M.
Pontone, Gianluca
Kawasaki, Tomohiro
Sand, Niels Peter Rønnow
Jensen, Jesper M.
Amano, Tetsuya
Poon, Michael
Øvrehus, Kristian A.
Sonck, Jeroen
Rabbat, Mark G.
Mullen, Sarah
De Bruyne, Bernard
Rogers, Campbell
Matsuo, Hitoshi
Bax, Jeroen J.
Douglas, Pamela S.
Patel, Manesh R.
Nieman, Koen
Ihdayhid, Abdul Rahman
Trans-lesional fractional flow reserve gradient as derived from coronary CT improves patient management: ADVANCE registry(☆)
title Trans-lesional fractional flow reserve gradient as derived from coronary CT improves patient management: ADVANCE registry(☆)
title_full Trans-lesional fractional flow reserve gradient as derived from coronary CT improves patient management: ADVANCE registry(☆)
title_fullStr Trans-lesional fractional flow reserve gradient as derived from coronary CT improves patient management: ADVANCE registry(☆)
title_full_unstemmed Trans-lesional fractional flow reserve gradient as derived from coronary CT improves patient management: ADVANCE registry(☆)
title_short Trans-lesional fractional flow reserve gradient as derived from coronary CT improves patient management: ADVANCE registry(☆)
title_sort trans-lesional fractional flow reserve gradient as derived from coronary ct improves patient management: advance registry(☆)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9719736/
https://www.ncbi.nlm.nih.gov/pubmed/34518113
http://dx.doi.org/10.1016/j.jcct.2021.08.003
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