Cargando…
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
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 |
_version_ | 1784843391063818240 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9719736 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT takagihidenobu translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT leipsicjonathona translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT mcnamaranoah translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT martinisabella translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT fairbairntimothya translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT akasakatakashi translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT nørgaardbjarnel translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT bermandaniels translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT chinnaiyankavitha translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT hurwitzkoweeklynnem translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT pontonegianluca translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT kawasakitomohiro translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT sandnielspeterrønnow translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT jensenjesperm translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT amanotetsuya translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT poonmichael translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT øvrehuskristiana translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT sonckjeroen translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT rabbatmarkg translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT mullensarah translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT debruynebernard translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT rogerscampbell translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT matsuohitoshi translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT baxjeroenj translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT douglaspamelas translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT patelmaneshr translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT niemankoen translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry AT ihdayhidabdulrahman translesionalfractionalflowreservegradientasderivedfromcoronaryctimprovespatientmanagementadvanceregistry |