Sex differences in machine learning computed tomography-derived fractional flow reserve
Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFR CT ) can assess the hemodynamic significance of coronary artery stenoses. We aimed to assess sex differences in the association of ML-FFR CT and incident cardiovascular outcomes. We studied a ret...
Saved in:
Published in | Scientific reports Vol. 12; no. 1; p. 13861 |
---|---|
Main Authors | , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
16.08.2022
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFR
CT
) can assess the hemodynamic significance of coronary artery stenoses. We aimed to assess sex differences in the association of ML-FFR
CT
and incident cardiovascular outcomes. We studied a retrospective cohort of consecutive patients who underwent clinically indicated CCTA and single photon emission computed tomography (SPECT). Obstructive stenosis was defined as ≥ 70% stenosis severity in non-left main vessels or ≥ 50% in the left main coronary. ML-FFR
CT
was computed using a machine learning algorithm with significant stenosis defined as ML-FFR
CT
< 0.8. The primary outcome was a composite of death or non-fatal myocardial infarction (D/MI). Our study population consisted of 471 patients with mean (SD) age 65 (13) years, 53% men, and multiple comorbidities (78% hypertension, 66% diabetes, 81% dyslipidemia). Compared to men, women were less likely to have obstructive stenosis by CCTA (9% vs. 18%; p = 0.006), less multivessel CAD (4% vs. 6%; p = 0.25), lower prevalence of ML-FFR
CT
< 0.8 (39% vs. 44%; p = 0.23) and higher median (IQR) ML-FFR
CT
(0.76 (0.53–0.86) vs. 0.71 (0.47–0.84); p = 0.047). In multivariable adjusted models, there was no significant association between ML-FFR
CT
< 0.8 and D/MI [Hazard Ratio 0.82, 95% confidence interval (0.30, 2.20); p = 0.25 for interaction with sex.]. In a high-risk cohort of symptomatic patients who underwent CCTA and SPECT testing, ML-FFR
CT
was higher in women than men. There was no significant association between ML-FFR
CT
and incident mortality or MI and no evidence that the prognostic value of ML-FFR
CT
differs by sex. |
---|---|
AbstractList | Abstract Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFRCT) can assess the hemodynamic significance of coronary artery stenoses. We aimed to assess sex differences in the association of ML-FFRCT and incident cardiovascular outcomes. We studied a retrospective cohort of consecutive patients who underwent clinically indicated CCTA and single photon emission computed tomography (SPECT). Obstructive stenosis was defined as ≥ 70% stenosis severity in non-left main vessels or ≥ 50% in the left main coronary. ML-FFRCT was computed using a machine learning algorithm with significant stenosis defined as ML-FFRCT < 0.8. The primary outcome was a composite of death or non-fatal myocardial infarction (D/MI). Our study population consisted of 471 patients with mean (SD) age 65 (13) years, 53% men, and multiple comorbidities (78% hypertension, 66% diabetes, 81% dyslipidemia). Compared to men, women were less likely to have obstructive stenosis by CCTA (9% vs. 18%; p = 0.006), less multivessel CAD (4% vs. 6%; p = 0.25), lower prevalence of ML-FFRCT < 0.8 (39% vs. 44%; p = 0.23) and higher median (IQR) ML-FFRCT (0.76 (0.53–0.86) vs. 0.71 (0.47–0.84); p = 0.047). In multivariable adjusted models, there was no significant association between ML-FFRCT < 0.8 and D/MI [Hazard Ratio 0.82, 95% confidence interval (0.30, 2.20); p = 0.25 for interaction with sex.]. In a high-risk cohort of symptomatic patients who underwent CCTA and SPECT testing, ML-FFRCT was higher in women than men. There was no significant association between ML-FFRCT and incident mortality or MI and no evidence that the prognostic value of ML-FFRCT differs by sex. Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFR CT ) can assess the hemodynamic significance of coronary artery stenoses. We aimed to assess sex differences in the association of ML-FFR CT and incident cardiovascular outcomes. We studied a retrospective cohort of consecutive patients who underwent clinically indicated CCTA and single photon emission computed tomography (SPECT). Obstructive stenosis was defined as ≥ 70% stenosis severity in non-left main vessels or ≥ 50% in the left main coronary. ML-FFR CT was computed using a machine learning algorithm with significant stenosis defined as ML-FFR CT < 0.8. The primary outcome was a composite of death or non-fatal myocardial infarction (D/MI). Our study population consisted of 471 patients with mean (SD) age 65 (13) years, 53% men, and multiple comorbidities (78% hypertension, 66% diabetes, 81% dyslipidemia). Compared to men, women were less likely to have obstructive stenosis by CCTA (9% vs. 18%; p = 0.006), less multivessel CAD (4% vs. 6%; p = 0.25), lower prevalence of ML-FFR CT < 0.8 (39% vs. 44%; p = 0.23) and higher median (IQR) ML-FFR CT (0.76 (0.53–0.86) vs. 0.71 (0.47–0.84); p = 0.047). In multivariable adjusted models, there was no significant association between ML-FFR CT < 0.8 and D/MI [Hazard Ratio 0.82, 95% confidence interval (0.30, 2.20); p = 0.25 for interaction with sex.]. In a high-risk cohort of symptomatic patients who underwent CCTA and SPECT testing, ML-FFR CT was higher in women than men. There was no significant association between ML-FFR CT and incident mortality or MI and no evidence that the prognostic value of ML-FFR CT differs by sex. Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFRCT) can assess the hemodynamic significance of coronary artery stenoses. We aimed to assess sex differences in the association of ML-FFRCT and incident cardiovascular outcomes. We studied a retrospective cohort of consecutive patients who underwent clinically indicated CCTA and single photon emission computed tomography (SPECT). Obstructive stenosis was defined as ≥ 70% stenosis severity in non-left main vessels or ≥ 50% in the left main coronary. ML-FFRCT was computed using a machine learning algorithm with significant stenosis defined as ML-FFRCT < 0.8. The primary outcome was a composite of death or non-fatal myocardial infarction (D/MI). Our study population consisted of 471 patients with mean (SD) age 65 (13) years, 53% men, and multiple comorbidities (78% hypertension, 66% diabetes, 81% dyslipidemia). Compared to men, women were less likely to have obstructive stenosis by CCTA (9% vs. 18%; p = 0.006), less multivessel CAD (4% vs. 6%; p = 0.25), lower prevalence of ML-FFRCT < 0.8 (39% vs. 44%; p = 0.23) and higher median (IQR) ML-FFRCT (0.76 (0.53–0.86) vs. 0.71 (0.47–0.84); p = 0.047). In multivariable adjusted models, there was no significant association between ML-FFRCT < 0.8 and D/MI [Hazard Ratio 0.82, 95% confidence interval (0.30, 2.20); p = 0.25 for interaction with sex.]. In a high-risk cohort of symptomatic patients who underwent CCTA and SPECT testing, ML-FFRCT was higher in women than men. There was no significant association between ML-FFRCT and incident mortality or MI and no evidence that the prognostic value of ML-FFRCT differs by sex. Abstract Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFR CT ) can assess the hemodynamic significance of coronary artery stenoses. We aimed to assess sex differences in the association of ML-FFR CT and incident cardiovascular outcomes. We studied a retrospective cohort of consecutive patients who underwent clinically indicated CCTA and single photon emission computed tomography (SPECT). Obstructive stenosis was defined as ≥ 70% stenosis severity in non-left main vessels or ≥ 50% in the left main coronary. ML-FFR CT was computed using a machine learning algorithm with significant stenosis defined as ML-FFR CT < 0.8. The primary outcome was a composite of death or non-fatal myocardial infarction (D/MI). Our study population consisted of 471 patients with mean (SD) age 65 (13) years, 53% men, and multiple comorbidities (78% hypertension, 66% diabetes, 81% dyslipidemia). Compared to men, women were less likely to have obstructive stenosis by CCTA (9% vs. 18%; p = 0.006), less multivessel CAD (4% vs. 6%; p = 0.25), lower prevalence of ML-FFR CT < 0.8 (39% vs. 44%; p = 0.23) and higher median (IQR) ML-FFR CT (0.76 (0.53–0.86) vs. 0.71 (0.47–0.84); p = 0.047). In multivariable adjusted models, there was no significant association between ML-FFR CT < 0.8 and D/MI [Hazard Ratio 0.82, 95% confidence interval (0.30, 2.20); p = 0.25 for interaction with sex.]. In a high-risk cohort of symptomatic patients who underwent CCTA and SPECT testing, ML-FFR CT was higher in women than men. There was no significant association between ML-FFR CT and incident mortality or MI and no evidence that the prognostic value of ML-FFR CT differs by sex. |
ArticleNumber | 13861 |
Author | Han, Yushui Alnabelsi, Talal Saad, Jean Michel Al Rifai, Mahmoud Al-Mallah, Mouaz H. Schwemmer, Chris Ahmed, Ahmed Ibrahim Ramirez-Giraldo, Juan C. Chang, Su Min Nabi, Faisal Cocker, Myra Mahmarian, John J. Zoghbi, William A. |
Author_xml | – sequence: 1 givenname: Mahmoud surname: Al Rifai fullname: Al Rifai, Mahmoud organization: Houston Methodist Debakey Heart & Vascular Center – sequence: 2 givenname: Ahmed Ibrahim surname: Ahmed fullname: Ahmed, Ahmed Ibrahim organization: Houston Methodist Debakey Heart & Vascular Center – sequence: 3 givenname: Yushui surname: Han fullname: Han, Yushui organization: Houston Methodist Debakey Heart & Vascular Center – sequence: 4 givenname: Jean Michel surname: Saad fullname: Saad, Jean Michel organization: Houston Methodist Debakey Heart & Vascular Center – sequence: 5 givenname: Talal surname: Alnabelsi fullname: Alnabelsi, Talal organization: University of Kentucky – sequence: 6 givenname: Faisal surname: Nabi fullname: Nabi, Faisal organization: Houston Methodist Debakey Heart & Vascular Center – sequence: 7 givenname: Su Min surname: Chang fullname: Chang, Su Min organization: Houston Methodist Debakey Heart & Vascular Center – sequence: 8 givenname: Myra surname: Cocker fullname: Cocker, Myra organization: Houston Methodist Debakey Heart & Vascular Center, Computed Tomography-Research Collaborations, Siemens Healthineers – sequence: 9 givenname: Chris surname: Schwemmer fullname: Schwemmer, Chris organization: Computed Tomography-Research & Development, Siemens Healthcare GmbH – sequence: 10 givenname: Juan C. surname: Ramirez-Giraldo fullname: Ramirez-Giraldo, Juan C. organization: Computed Tomography-Research Collaborations, Siemens Healthineers – sequence: 11 givenname: William A. surname: Zoghbi fullname: Zoghbi, William A. organization: Houston Methodist Debakey Heart & Vascular Center – sequence: 12 givenname: John J. surname: Mahmarian fullname: Mahmarian, John J. organization: Houston Methodist Debakey Heart & Vascular Center – sequence: 13 givenname: Mouaz H. surname: Al-Mallah fullname: Al-Mallah, Mouaz H. email: mal-mallah@houstonmethodist.org organization: Houston Methodist Debakey Heart & Vascular Center |
BookMark | eNp9kk1v1DAQhi1UREvpH-AUiQuXFH_G9gUJVUArVeIAiKPl2OOsV4m92NmF_nvSTQWUA77YGj_zaDR6n6OTlBMg9JLgS4KZelM5EVq1mNKWSCVFq5-gM4q5aCmj9OSv9ym6qHWLlyOo5kQ_Q6dMaMmxEGfo22f42fgYAhRIDmoTUzNZt4kJmhFsSTENjcvTbj-Db-Y85aHY3eau9VDiYSmFYt0cc7JjE8b8oylQoRzgBXoa7Fjh4uE-R18_vP9ydd3efvp4c_XutnWCyLn13DKpGdU4dJhjyTqKFUgucY87Rrq-D4KGXujeW06pD4wGzZUH68AHT9g5ulm9Ptut2ZU42XJnso3mWMhlMLbM0Y1gFOs955I7Bp4TRS3hsqdCBKs6rYNaXG9X127fT-AdpLnY8ZH08U-KGzPkg9FMEan1Inj9ICj5-x7qbKZYHYyjTZD31VCJGSeSSL6gr_5Bt3lfli0eKSqJ4EIsFF0pV3KtBcLvYQg29zEwawzMEgNzjIG5n4KtTXWB0wDlj_o_Xb8A6cq2Fg |
CitedBy_id | crossref_primary_10_1186_s12933_023_01751_5 crossref_primary_10_1161_JAHA_123_029330 crossref_primary_10_3390_jpm13020223 |
Cites_doi | 10.1016/j.jcmg.2016.11.024 10.1016/j.jcct.2017.09.009 10.1016/j.jacc.2020.03.060 10.1016/j.jcct.2015.01.008 10.1038/nrcardio.2016.89 10.1093/ehjci/jew148 10.1016/j.jcmg.2019.03.003 10.1016/S0140-6736(19)30315-0 10.1016/j.jacc.2011.06.066 10.1001/2012.jama.11274 10.1016/j.jacc.2013.11.043 10.1056/NEJMoa1805971 10.1093/eurheartj/ehv444 10.1016/j.jcmg.2020.07.008 10.1038/s41598-018-29910-9 10.1016/S0735-1097(21)02625-5 10.1093/ehjci/jeaa270 10.1016/j.jacc.2018.08.1038 10.1016/j.jcmg.2018.05.004 10.1161/CIRCULATIONAHA.111.029660 10.1136/bmjgh-2016-000080 10.1016/j.atherosclerosis.2015.04.802 10.1016/j.jcct.2016.10.002 10.1001/jamacardio.2020.3409 10.1016/j.jacc.2011.06.079 10.1161/CIRCIMAGING.117.007217 10.1056/NEJMoa1205361 10.1056/NEJMoa1415516 10.1016/j.jcmg.2016.01.004 10.1093/eurheartj/ehy530 |
ContentType | Journal Article |
Copyright | The Author(s) 2022 The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
Copyright_xml | – notice: The Author(s) 2022 – notice: The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
DBID | C6C AAYXX CITATION 3V. 7X7 7XB 88A 88E 88I 8FE 8FH 8FI 8FJ 8FK ABUWG AFKRA AZQEC BBNVY BENPR BHPHI CCPQU DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. LK8 M0S M1P M2P M7P PIMPY PQEST PQQKQ PQUKI PRINS Q9U 7X8 5PM DOA |
DOI | 10.1038/s41598-022-17875-9 |
DatabaseName | Springer Nature OA Free Journals CrossRef ProQuest Central (Corporate) Health & Medical Collection ProQuest Central (purchase pre-March 2016) Biology Database (Alumni Edition) Medical Database (Alumni Edition) Science Database (Alumni Edition) ProQuest SciTech Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni Edition) ProQuest Central ProQuest Central Essentials Biological Science Collection ProQuest Central Natural Science Collection ProQuest One Community College ProQuest Central Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) ProQuest Biological Science Collection Health & Medical Collection (Alumni Edition) Medical Database Science Database Biological Science Database Publicly Available Content Database ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic MEDLINE - Academic PubMed Central (Full Participant titles) Directory of Open Access Journals |
DatabaseTitle | CrossRef Publicly Available Content Database ProQuest Central Student ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Natural Science Collection ProQuest Central China ProQuest Biology Journals (Alumni Edition) ProQuest Central Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Biological Science Collection ProQuest Medical Library (Alumni) ProQuest Science Journals (Alumni Edition) ProQuest Biological Science Collection ProQuest Central Basic ProQuest Science Journals ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest Central (Alumni) MEDLINE - Academic |
DatabaseTitleList | Publicly Available Content Database CrossRef |
Database_xml | – sequence: 1 dbid: C6C name: Springer Nature OA Free Journals url: http://www.springeropen.com/ sourceTypes: Publisher – sequence: 2 dbid: DOA name: Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 3 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Biology |
EISSN | 2045-2322 |
EndPage | 13861 |
ExternalDocumentID | oai_doaj_org_article_83bd4474c3ed4182a147b255fa8699f8 10_1038_s41598_022_17875_9 |
GroupedDBID | 0R~ 3V. 4.4 53G 5VS 7X7 88A 88E 88I 8FE 8FH 8FI 8FJ AAFWJ AAJSJ AAKDD ABDBF ABUWG ACGFS ACSMW ADBBV ADRAZ AENEX AFKRA AJTQC ALIPV ALMA_UNASSIGNED_HOLDINGS AOIJS AZQEC BAWUL BBNVY BCNDV BENPR BHPHI BPHCQ BVXVI C6C CCPQU DIK DWQXO EBD EBLON EBS ESX FYUFA GNUQQ GROUPED_DOAJ GX1 HCIFZ HH5 HMCUK HYE KQ8 LK8 M0L M1P M2P M48 M7P M~E NAO OK1 PIMPY PQQKQ PROAC PSQYO RIG RNT RNTTT RPM SNYQT UKHRP AAYXX AFPKN CITATION 7XB 8FK K9. PQEST PQUKI PRINS Q9U 7X8 AFGXO 5PM |
ID | FETCH-LOGICAL-c517t-d4a3793290f6040736208e7470b06316bbf52fb59bda422df32f948deacedfd13 |
IEDL.DBID | RPM |
ISSN | 2045-2322 |
IngestDate | Tue Oct 22 15:09:24 EDT 2024 Tue Sep 17 21:21:54 EDT 2024 Fri Aug 16 09:46:57 EDT 2024 Thu Oct 10 22:50:16 EDT 2024 Fri Aug 23 02:47:45 EDT 2024 Fri Oct 11 20:45:09 EDT 2024 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 1 |
Language | English |
License | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c517t-d4a3793290f6040736208e7470b06316bbf52fb59bda422df32f948deacedfd13 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
OpenAccessLink | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9381799/ |
PMID | 35974055 |
PQID | 2702715455 |
PQPubID | 2041939 |
PageCount | 1 |
ParticipantIDs | doaj_primary_oai_doaj_org_article_83bd4474c3ed4182a147b255fa8699f8 pubmedcentral_primary_oai_pubmedcentral_nih_gov_9381799 proquest_miscellaneous_2703417174 proquest_journals_2702715455 crossref_primary_10_1038_s41598_022_17875_9 springer_journals_10_1038_s41598_022_17875_9 |
PublicationCentury | 2000 |
PublicationDate | 2022-08-16 |
PublicationDateYYYYMMDD | 2022-08-16 |
PublicationDate_xml | – month: 08 year: 2022 text: 2022-08-16 day: 16 |
PublicationDecade | 2020 |
PublicationPlace | London |
PublicationPlace_xml | – name: London |
PublicationTitle | Scientific reports |
PublicationTitleAbbrev | Sci Rep |
PublicationYear | 2022 |
Publisher | Nature Publishing Group UK Nature Publishing Group Nature Portfolio |
Publisher_xml | – name: Nature Publishing Group UK – name: Nature Publishing Group – name: Nature Portfolio |
References | de Knegt (CR26) 2020; 22 Cho (CR1) 2020; 75 Arbab-Zadeh (CR7) 2012; 59 Packard, Li, Budoff, Karlsberg (CR10) 2017; 18 Stuijfzand (CR27) 2020; 5 Douglas (CR24) 2015; 372 Lu (CR31) 2017; 10 Shaw (CR22) 2011; 124 Newby (CR23) 2018; 379 Pagidipati, Peterson (CR3) 2016; 13 Thygesen (CR15) 2018; 72 Kueh (CR17) 2017; 11 Nørgaard (CR30) 2014; 63 Min (CR19) 2012; 308 De Bruyne (CR25) 2012; 367 Agasthi (CR12) 2018; 8 Fairbairn (CR13) 2020; 13 Coenen (CR18) 2018; 11 Abbara (CR16) 2016; 10 Danad (CR8) 2017; 38 Ahmed (CR14) 2021; 77 Peters, Woodward, Jha, Kennedy, Norton (CR4) 2016; 1 Koo (CR20) 2011; 58 Sand (CR21) 2018; 11 Baldassarre (CR5) 2016; 9 Thompson (CR11) 2015; 9 Mehran, Vogel, Ortega, Cooney, Horton (CR2) 2019; 393 Patel (CR28) 2020; 13 Crea, Battipaglia, Andreotti (CR6) 2015; 241 Fairbairn (CR29) 2018; 39 Douglas (CR9) 2015; 36 AG Thompson (17875_CR11) 2015; 9 BL Nørgaard (17875_CR30) 2014; 63 NPR Sand (17875_CR21) 2018; 11 A Arbab-Zadeh (17875_CR7) 2012; 59 JK Min (17875_CR19) 2012; 308 LA Baldassarre (17875_CR5) 2016; 9 WJ Stuijfzand (17875_CR27) 2020; 5 NJ Pagidipati (17875_CR3) 2016; 13 B Koo (17875_CR20) 2011; 58 MR Patel (17875_CR28) 2020; 13 AI Ahmed (17875_CR14) 2021; 77 TA Fairbairn (17875_CR29) 2018; 39 SAE Peters (17875_CR4) 2016; 1 MT Lu (17875_CR31) 2017; 10 TA Fairbairn (17875_CR13) 2020; 13 LJ Shaw (17875_CR22) 2011; 124 PS Douglas (17875_CR24) 2015; 372 F Crea (17875_CR6) 2015; 241 I Danad (17875_CR8) 2017; 38 PS Douglas (17875_CR9) 2015; 36 K Thygesen (17875_CR15) 2018; 72 SH Kueh (17875_CR17) 2017; 11 DE Newby (17875_CR23) 2018; 379 MC de Knegt (17875_CR26) 2020; 22 A Coenen (17875_CR18) 2018; 11 R Mehran (17875_CR2) 2019; 393 S Abbara (17875_CR16) 2016; 10 P Agasthi (17875_CR12) 2018; 8 RRS Packard (17875_CR10) 2017; 18 B De Bruyne (17875_CR25) 2012; 367 L Cho (17875_CR1) 2020; 75 |
References_xml | – volume: 10 start-page: 1350 year: 2017 end-page: 1358 ident: CR31 article-title: Noninvasive FFR derived from coronary CT angiography: Management and outcomes in the PROMISE trial publication-title: JACC Cardiovasc. Imaging. doi: 10.1016/j.jcmg.2016.11.024 contributor: fullname: Lu – volume: 11 start-page: 462 year: 2017 end-page: 467 ident: CR17 article-title: Fractional flow reserve derived from coronary computed tomography angiography reclassification rate using value distal to lesion compared to lowest value publication-title: J. Cardiovasc. Comput. Tomogr. doi: 10.1016/j.jcct.2017.09.009 contributor: fullname: Kueh – volume: 75 start-page: 2602 year: 2020 end-page: 2618 ident: CR1 article-title: Summary of updated recommendations for primary prevention of cardiovascular disease in women: JACC state-of-the-art review publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2020.03.060 contributor: fullname: Cho – volume: 9 start-page: 120 year: 2015 end-page: 128 ident: CR11 article-title: Diagnostic accuracy and discrimination of ischemia by fractional flow reserve CT using a clinical use rule: Results from the determination of fractional flow reserve by anatomic computed tomographic angiography study publication-title: J. Cardiovasc. Comput. Tomogr. doi: 10.1016/j.jcct.2015.01.008 contributor: fullname: Thompson – volume: 13 start-page: 471 year: 2016 end-page: 480 ident: CR3 article-title: Acute coronary syndromes in women and men publication-title: Nat. Rev. Cardiol. doi: 10.1038/nrcardio.2016.89 contributor: fullname: Peterson – volume: 18 start-page: 145 year: 2017 end-page: 152 ident: CR10 article-title: Fractional flow reserve by computerized tomography and subsequent coronary revascularization publication-title: Eur. Heart J. Cardiovasc. Imaging doi: 10.1093/ehjci/jew148 contributor: fullname: Karlsberg – volume: 13 start-page: 97 year: 2020 end-page: 105 ident: CR28 article-title: 1-Year impact on medical practice and clinical outcomes of FFRCT: The ADVANCE registry publication-title: JACC Cardiovasc. Imaging doi: 10.1016/j.jcmg.2019.03.003 contributor: fullname: Patel – volume: 393 start-page: 967 year: 2019 end-page: 968 ident: CR2 article-title: The Lancet Commission on women and cardiovascular disease: Time for a shift in women's health publication-title: Lancet doi: 10.1016/S0140-6736(19)30315-0 contributor: fullname: Horton – volume: 58 start-page: 1989 year: 2011 end-page: 1997 ident: CR20 article-title: Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2011.06.066 contributor: fullname: Koo – volume: 308 start-page: 1237 year: 2012 end-page: 1245 ident: CR19 article-title: Diagnostic accuracy of fractional flow reserve from anatomic CT angiography publication-title: JAMA doi: 10.1001/2012.jama.11274 contributor: fullname: Min – volume: 63 start-page: 1145 year: 2014 end-page: 1155 ident: CR30 article-title: Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: The NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps) publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2013.11.043 contributor: fullname: Nørgaard – volume: 379 start-page: 924 year: 2018 end-page: 933 ident: CR23 article-title: Coronary CT angiography and 5-year risk of myocardial infarction publication-title: N. Engl. J. Med. doi: 10.1056/NEJMoa1805971 contributor: fullname: Newby – volume: 36 start-page: 3359 year: 2015 end-page: 3367 ident: CR9 article-title: Clinical outcomes of fractional flow reserve by computed tomographic angiography-guided diagnostic strategies vs. usual care in patients with suspected coronary artery disease: The prospective longitudinal trial of FFR(CT): Outcome and resource impacts study publication-title: Eur. Heart J. doi: 10.1093/eurheartj/ehv444 contributor: fullname: Douglas – volume: 13 start-page: 2576 year: 2020 end-page: 2587 ident: CR13 article-title: Sex differences in coronary computed tomography angiography-derived fractional flow reserve: Lessons from ADVANCE publication-title: JACC Cardiovasc. Imaging. doi: 10.1016/j.jcmg.2020.07.008 contributor: fullname: Fairbairn – volume: 8 start-page: 11535 year: 2018 ident: CR12 article-title: Comparison of computed tomography derived fractional flow reserve to invasive fractional flow reserve in diagnosis of functional coronary stenosis: A meta-analysis publication-title: Sci. Rep. doi: 10.1038/s41598-018-29910-9 contributor: fullname: Agasthi – volume: 77 start-page: 1267 year: 2021 ident: CR14 article-title: Prognostic value of computed tomography derived fractional flow reserve comparison with myocardial perfusion imaging publication-title: J. Am. Coll. Cardiol. doi: 10.1016/S0735-1097(21)02625-5 contributor: fullname: Ahmed – volume: 22 start-page: jeaa270 year: 2020 ident: CR26 article-title: Stress myocardial perfusion with qualitative magnetic resonance and quantitative dynamic computed tomography: Comparison of diagnostic performance and incremental value over coronary computed tomography angiography publication-title: Eur. Heart J. Cardiovasc. Imaging doi: 10.1093/ehjci/jeaa270 contributor: fullname: de Knegt – volume: 72 start-page: 2231 year: 2018 end-page: 2264 ident: CR15 article-title: Fourth Universal Definition of Myocardial Infarction (2018) publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2018.08.1038 contributor: fullname: Thygesen – volume: 11 start-page: 1640 year: 2018 end-page: 1650 ident: CR21 article-title: Prospective comparison of FFR derived from coronary CT angiography with SPECT perfusion imaging in stable coronary artery disease: The ReASSESS study publication-title: JACC Cardiovasc. Imaging. doi: 10.1016/j.jcmg.2018.05.004 contributor: fullname: Sand – volume: 124 start-page: 1239 year: 2011 end-page: 1249 ident: CR22 article-title: Comparative effectiveness of exercise electrocardiography with or without myocardial perfusion single photon emission computed tomography in women with suspected coronary artery disease: Results from the What Is the Optimal Method for Ischemia Evaluation in Women (WOMEN) trial publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.111.029660 contributor: fullname: Shaw – volume: 1 year: 2016 ident: CR4 article-title: Women's health: A new global agenda publication-title: BMJ Glob. Health doi: 10.1136/bmjgh-2016-000080 contributor: fullname: Norton – volume: 241 start-page: 157 year: 2015 end-page: 168 ident: CR6 article-title: Sex differences in mechanisms, presentation and management of ischaemic heart disease publication-title: Atherosclerosis doi: 10.1016/j.atherosclerosis.2015.04.802 contributor: fullname: Andreotti – volume: 38 start-page: 991 year: 2017 end-page: 998 ident: CR8 article-title: Diagnostic performance of cardiac imaging methods to diagnose ischaemia-causing coronary artery disease when directly compared with fractional flow reserve as a reference standard: A meta-analysis publication-title: Eur. Heart J. contributor: fullname: Danad – volume: 10 start-page: 435 year: 2016 end-page: 449 ident: CR16 article-title: SCCT guidelines for the performance and acquisition of coronary computed tomographic angiography: A report of the society of Cardiovascular Computed Tomography Guidelines Committee: Endorsed by the North American Society for Cardiovascular Imaging (NASCI) publication-title: J. Cardiovasc. Comput. Tomogr. doi: 10.1016/j.jcct.2016.10.002 contributor: fullname: Abbara – volume: 5 start-page: 1338 year: 2020 end-page: 1348 ident: CR27 article-title: Stress myocardial perfusion imaging vs coronary computed tomographic angiography for diagnosis of invasive vessel-specific coronary physiology: Predictive modeling results from the computed tomographic evaluation of atherosclerotic determinants of myocardial ischemia (CREDENCE) trial publication-title: JAMA Cardiol. doi: 10.1001/jamacardio.2020.3409 contributor: fullname: Stuijfzand – volume: 59 start-page: 379 year: 2012 end-page: 387 ident: CR7 article-title: Diagnostic accuracy of computed tomography coronary angiography according to pre-test probability of coronary artery disease and severity of coronary arterial calcification. The CORE-64 (Coronary Artery Evaluation Using 64-Row Multidetector Computed Tomography Angiography) International Multicenter Study publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2011.06.079 contributor: fullname: Arbab-Zadeh – volume: 11 year: 2018 ident: CR18 article-title: Diagnostic accuracy of a machine-learning approach to coronary computed tomographic angiography-based fractional flow reserve: Result from the MACHINE consortium publication-title: Circ. Cardiovasc. Imaging doi: 10.1161/CIRCIMAGING.117.007217 contributor: fullname: Coenen – volume: 367 start-page: 991 year: 2012 end-page: 1001 ident: CR25 article-title: Fractional flow reserve-guided PCI versus medical therapy in stable coronary disease publication-title: N. Engl. J. Med. doi: 10.1056/NEJMoa1205361 contributor: fullname: De Bruyne – volume: 372 start-page: 1291 year: 2015 end-page: 1300 ident: CR24 article-title: Outcomes of anatomical versus functional testing for coronary artery disease publication-title: N. Engl. J. Med. doi: 10.1056/NEJMoa1415516 contributor: fullname: Douglas – volume: 9 start-page: 421 year: 2016 end-page: 435 ident: CR5 article-title: Noninvasive imaging to evaluate women with stable ischemic heart disease publication-title: JACC Cardiovasc. Imaging doi: 10.1016/j.jcmg.2016.01.004 contributor: fullname: Baldassarre – volume: 39 start-page: 3701 year: 2018 end-page: 3711 ident: CR29 article-title: Real-world clinical utility and impact on clinical decision-making of coronary computed tomography angiography-derived fractional flow reserve: Lessons from the ADVANCE Registry publication-title: Eur. Heart J. doi: 10.1093/eurheartj/ehy530 contributor: fullname: Fairbairn – volume: 379 start-page: 924 year: 2018 ident: 17875_CR23 publication-title: N. Engl. J. Med. doi: 10.1056/NEJMoa1805971 contributor: fullname: DE Newby – volume: 372 start-page: 1291 year: 2015 ident: 17875_CR24 publication-title: N. Engl. J. Med. doi: 10.1056/NEJMoa1415516 contributor: fullname: PS Douglas – volume: 367 start-page: 991 year: 2012 ident: 17875_CR25 publication-title: N. Engl. J. Med. doi: 10.1056/NEJMoa1205361 contributor: fullname: B De Bruyne – volume: 241 start-page: 157 year: 2015 ident: 17875_CR6 publication-title: Atherosclerosis doi: 10.1016/j.atherosclerosis.2015.04.802 contributor: fullname: F Crea – volume: 13 start-page: 97 year: 2020 ident: 17875_CR28 publication-title: JACC Cardiovasc. Imaging doi: 10.1016/j.jcmg.2019.03.003 contributor: fullname: MR Patel – volume: 8 start-page: 11535 year: 2018 ident: 17875_CR12 publication-title: Sci. Rep. doi: 10.1038/s41598-018-29910-9 contributor: fullname: P Agasthi – volume: 77 start-page: 1267 year: 2021 ident: 17875_CR14 publication-title: J. Am. Coll. Cardiol. doi: 10.1016/S0735-1097(21)02625-5 contributor: fullname: AI Ahmed – volume: 10 start-page: 435 year: 2016 ident: 17875_CR16 publication-title: J. Cardiovasc. Comput. Tomogr. doi: 10.1016/j.jcct.2016.10.002 contributor: fullname: S Abbara – volume: 393 start-page: 967 year: 2019 ident: 17875_CR2 publication-title: Lancet doi: 10.1016/S0140-6736(19)30315-0 contributor: fullname: R Mehran – volume: 18 start-page: 145 year: 2017 ident: 17875_CR10 publication-title: Eur. Heart J. Cardiovasc. Imaging doi: 10.1093/ehjci/jew148 contributor: fullname: RRS Packard – volume: 11 start-page: 462 year: 2017 ident: 17875_CR17 publication-title: J. Cardiovasc. Comput. Tomogr. doi: 10.1016/j.jcct.2017.09.009 contributor: fullname: SH Kueh – volume: 39 start-page: 3701 year: 2018 ident: 17875_CR29 publication-title: Eur. Heart J. doi: 10.1093/eurheartj/ehy530 contributor: fullname: TA Fairbairn – volume: 5 start-page: 1338 year: 2020 ident: 17875_CR27 publication-title: JAMA Cardiol. doi: 10.1001/jamacardio.2020.3409 contributor: fullname: WJ Stuijfzand – volume: 1 year: 2016 ident: 17875_CR4 publication-title: BMJ Glob. Health doi: 10.1136/bmjgh-2016-000080 contributor: fullname: SAE Peters – volume: 36 start-page: 3359 year: 2015 ident: 17875_CR9 publication-title: Eur. Heart J. doi: 10.1093/eurheartj/ehv444 contributor: fullname: PS Douglas – volume: 124 start-page: 1239 year: 2011 ident: 17875_CR22 publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.111.029660 contributor: fullname: LJ Shaw – volume: 63 start-page: 1145 year: 2014 ident: 17875_CR30 publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2013.11.043 contributor: fullname: BL Nørgaard – volume: 38 start-page: 991 year: 2017 ident: 17875_CR8 publication-title: Eur. Heart J. contributor: fullname: I Danad – volume: 9 start-page: 421 year: 2016 ident: 17875_CR5 publication-title: JACC Cardiovasc. Imaging doi: 10.1016/j.jcmg.2016.01.004 contributor: fullname: LA Baldassarre – volume: 22 start-page: jeaa270 year: 2020 ident: 17875_CR26 publication-title: Eur. Heart J. Cardiovasc. Imaging doi: 10.1093/ehjci/jeaa270 contributor: fullname: MC de Knegt – volume: 11 year: 2018 ident: 17875_CR18 publication-title: Circ. Cardiovasc. Imaging doi: 10.1161/CIRCIMAGING.117.007217 contributor: fullname: A Coenen – volume: 308 start-page: 1237 year: 2012 ident: 17875_CR19 publication-title: JAMA doi: 10.1001/2012.jama.11274 contributor: fullname: JK Min – volume: 11 start-page: 1640 year: 2018 ident: 17875_CR21 publication-title: JACC Cardiovasc. Imaging. doi: 10.1016/j.jcmg.2018.05.004 contributor: fullname: NPR Sand – volume: 72 start-page: 2231 year: 2018 ident: 17875_CR15 publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2018.08.1038 contributor: fullname: K Thygesen – volume: 10 start-page: 1350 year: 2017 ident: 17875_CR31 publication-title: JACC Cardiovasc. Imaging. doi: 10.1016/j.jcmg.2016.11.024 contributor: fullname: MT Lu – volume: 13 start-page: 471 year: 2016 ident: 17875_CR3 publication-title: Nat. Rev. Cardiol. doi: 10.1038/nrcardio.2016.89 contributor: fullname: NJ Pagidipati – volume: 58 start-page: 1989 year: 2011 ident: 17875_CR20 publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2011.06.066 contributor: fullname: B Koo – volume: 9 start-page: 120 year: 2015 ident: 17875_CR11 publication-title: J. Cardiovasc. Comput. Tomogr. doi: 10.1016/j.jcct.2015.01.008 contributor: fullname: AG Thompson – volume: 75 start-page: 2602 year: 2020 ident: 17875_CR1 publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2020.03.060 contributor: fullname: L Cho – volume: 59 start-page: 379 year: 2012 ident: 17875_CR7 publication-title: J. Am. Coll. Cardiol. doi: 10.1016/j.jacc.2011.06.079 contributor: fullname: A Arbab-Zadeh – volume: 13 start-page: 2576 year: 2020 ident: 17875_CR13 publication-title: JACC Cardiovasc. Imaging. doi: 10.1016/j.jcmg.2020.07.008 contributor: fullname: TA Fairbairn |
SSID | ssj0000529419 |
Score | 2.433017 |
Snippet | Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFR
CT
) can assess the hemodynamic significance of... Abstract Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFR CT ) can assess the hemodynamic significance... Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFRCT) can assess the hemodynamic significance of coronary... Abstract Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFRCT) can assess the hemodynamic significance of... |
SourceID | doaj pubmedcentral proquest crossref springer |
SourceType | Open Website Open Access Repository Aggregation Database Publisher |
StartPage | 13861 |
SubjectTerms | 692/4019/592/75 692/4019/592/75/593/15/1939 Angiography Comorbidity Computed tomography Coronary artery Diabetes mellitus Dyslipidemia Gender differences Humanities and Social Sciences Hypertension Learning algorithms Machine learning multidisciplinary Myocardial infarction Population studies Science Science (multidisciplinary) Sex differences Single photon emission computed tomography Stenosis Tomography |
SummonAdditionalLinks | – databaseName: Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3PaxUxEA6lIPQiViuuVlnBW126yWSTzVHFUnropRZ7C8kmowW7T15fq_3vnST7ardQvHhNFpLMj50Zku8bxt5phGGQAZvBOypQwEPjlDRNUADAVTvokNk-j9XhqTw6687utPpKb8IKPXAR3H4PPkip5QAxSEqGHZfaUx6MrlfGYIH58u5OMVVYvYWR3EwomRb6_UuKVAlNRrUXJyPtGjOLRJmwf5Zl3n8jee-iNMefgyfs8ZQ41h_KhrfZRhyfskelleTNM_b1JP6u191OyPfr87G-yA8lYz11hvhWD6WFQ6hXi4uJqroJZILXNITLAnGgNfDH4ledYEnL67jDTg8-f_l02ExNE5qh43rVBOmAfE6YFhU5qKYA1faRiobWUzbClffYCfSd8cFJIQKCQCP7QD_gGDBweM42x8UYXyQ4d4-gNQrvQGrg3rXKOwRUwuHQY8X21gK0Pws3hs132tDbIm5L4rZZ3NZU7GOS8e2Xidc6D5C27aRt-y9tV2x3rSE7OdulTZA6nVLBrmJvb6fJTdLdhxvj4ip_Q_GaaldZMT3T7GxD85nx_Hsm3DaJxtDQCd6vbeDv4g8f-OX_OPArtiWSzSYSXrXLNlfLq_ia0qCVf5Mt_g_aRAUO priority: 102 providerName: Directory of Open Access Journals – databaseName: ProQuest Central dbid: BENPR link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1baxUxEA7aIvgi9Yarrazgm4ZuNtlcnqQtLcWHImqxbyHXWrC79ZzTqv_eSTZ7yhb0NQkkmcwlk8l8g9BbEalzzEfsrAEHhVqKDWcKe04pJbxxwme0zxN-fMo-nnVn5cFtWb5VTjoxK2o_uPRGvpvypkSy992Hq584VY1K0dVSQuM-2mwJS2Hazf3Dk0-f168sKY7FiCrZMg2Vu0uwWCmrDHwwAszaYTWzSBm4f3bbvPtX8k7ANNuhoy30qFwg673xxB-je6F_gh6MJSX_PEXfvoTf9VT1BHRAfdHXl_nDZKhLhYjz2o2lHHy9Gi4LZDX2wIo30BQXY6oDzBF_DL_qlJ60uAnP0OnR4deDY1yKJ2DXEbHCnhkKsteqJnIQVAGGqpEBnIfGwq2EcGtj10bbKesNa1sfaRsVkx4UcfDRE_ocbfRDH16ktG4ZqRCxtYYyQYk1Dbcm0shbE52MFXo3EVBfjRgZOse2qdQjuTWQW2dya1Wh_UTj9ciEb50bhsW5LuKiJbWeMcEcDZ6BC2QIExa8n2gkVyrKCm1PJ6SL0C31LYtU6M26G8QlxUBMH4brPAbsNviwrEJidrKzBc17-ovvGXhbJThDBTt4P_HA7eT_3vDL_6_1FXrYJm5MMLt8G22sFtdhBy46K_u6cPNfB-7-YQ priority: 102 providerName: ProQuest – databaseName: Scholars Portal Open Access Journals dbid: M48 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Jb9YwELVKKyQuVdlEuqAgcYNAYjteDggVRFVVggt8ojfLjj2lUpvQ9Ov27xk7SVGqcuBqO3I8nvHMkz1vCHktgTUN91A0ziJAYY4VVnBdeMEYq0TZSJ_YPr-J_QU_OKwPV8hU7mgU4Pm90C7Wk1r0J--uz24-osF_GFLG1ftzdEIxUQxhVYX6Vxf6AVmjnPGo8V_HcH_g-qaaV3rMnbn_05l_SjT-s9jz7svJO9enySvtbZD1MZzMd4f9f0xWQvuEPBwKTN48JT-_h-t8qoGCJ0J-3Oan6flkyMd6EUd5MxR28PmyOx0JrAuPinmJTdAPiQ84B5x0V3lMVuovwzOy2Pvy4_N-MZZSKJq6ksvCc8vQEqkuQaDZSnRbpQoIJUqHMUolnIOagqu185ZT6oFR0Fx5PJaDB1-x52S17drwIiZ5K2BSAnWWcckqZ0vhLDAQ1EKjICNvJgGa3wNjhkk33UyZQdwGxW2SuI3OyKco49uRke06NXT9kRmNxyjmPOeSNyx4joDIVlw6xEJgldAaVEa2px0ykwaZmGgnY4BYZ-TVbTcaT7wRsW3oLtIY9OKIaHlG5GxnZz8072mPfyUabh3JDTWu4O2kA38n__eCN_9v-BZ5RKN2RhJesU1Wl_1F2MEwaOleJt3-AystBKY priority: 102 providerName: Scholars Portal – databaseName: Springer Nature OA Free Journals dbid: C6C link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT9wwELbKVkhcEC2tGqBVKvVGI5KM48eRrkCIA5d2VW6WHXtapJJFy0Lh3zN2slsFtYdeYyeO55GZyXi-YeyTRGhb7rFonaUABRwUVnBdeAEAlShb6RPa54U4m_Hzy-ZygMmJtTCj_D2oo1syMLEIjEKmimSrKfQGe9nQQ6IET8V0_T8lZqx4pYe6mL_fOrI9CaJ_5Fc-PxX5LDWaLM7pDtseXMX8uOftK_YidK_ZZt888nGXff8aHvJVfxPS9vyqy6_T0ciQD70gfuRt37TB58v59QBOXXgSunu6hIu-qIHWwF_z33ksRFrchzdsdnrybXpWDG0Sirap5LLw3AJpWa1LFKSSkkxSqQKFCaUj_6MSzmFTo2u085bXtUeoUXPl6ZMbPPoK3rJJN-_Cu1jArRCkxNpZ4BIqZ0vhLAKK2mKrMGOHKwKamx4Nw6QsNijTk9sQuU0it9EZ-xJpvJ4ZkazTBWKwGRTDKHCec8lbCJ5TsGMrLh3FOWiV0BpVxg5WHDKDet2aWEQno_PXZOzjepgUI2Y7bBfmd2kOWWiKVnnG5Iizoxcaj3RXPxPEto7AhZp28HklA38W__eG9_5v-j7bqqN0RoBdccAmy8VdeE8uztJ9SLL9BIuE9gw priority: 102 providerName: Springer Nature |
Title | Sex differences in machine learning computed tomography-derived fractional flow reserve |
URI | https://link.springer.com/article/10.1038/s41598-022-17875-9 https://www.proquest.com/docview/2702715455 https://search.proquest.com/docview/2703417174 https://pubmed.ncbi.nlm.nih.gov/PMC9381799 https://doaj.org/article/83bd4474c3ed4182a147b255fa8699f8 |
Volume | 12 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3da9RAEF_aiuCL-InRekTwTdNLMpv9eLRHSxFailq8t2U_60EvKddr1f_e2U1SewVffAlkd2E3szM7M9mZ3xDyngewlrpQWKPRQQEDhWZUFo4BQMVKy11C-zxhR2f087yZb5FmzIVJQfvWLPbai-Veu_iRYisvl3Y6xolNT49nMsLKSTndJtsc4I6L3gN615JWckiQKUFMr1BJxUQydLsq5M-miFChEC3pMmb43dFHCbZ_w9a8Hyl577o0aaHDJ-TxYD7mn_plPiVbvn1GHvYFJX8_J9-_-l_5WPMET4B80ebLFC7p86E-xHlu-0IOLl93ywGwunDIiDfYFFZ9ogPOES66n3lMTlrd-Bfk7PDg2-yoGEonFLap-LpwVANKXi3LwFBMOaqpUnh0HUqDNknFjAlNHUwjjdO0rl2AOkgqHB7D3gVXwUuy03atfxWTukUAzkNtNFAOldElMzpAYLUOVoSMfBgJqC57hAyVbrZBqJ7yCimvEuWVzMh-pPHtyIhunRq61bka9lgJMI5STi14R9EB0hXlBn2foAWTMoiM7I47pAaRu1IxsY5Hg7DJyLvbbhSWeAOiW99dpzGotdGDpRnhGzu7saDNHuTCBLs9cF1GPo488Hfyf3_w6_-e6A15VEeejfi7bJfsrFfX_i1aQGszQb6f8wl5sH9wcvoF32ZsNkl_E_B5TMUkScQfLVcLXA |
link.rule.ids | 230,315,733,786,790,870,891,2115,12083,21416,24346,27955,27956,31752,31753,33777,33778,41153,42222,43343,43838,51609,53825,53827,74100,74657 |
linkProvider | National Library of Medicine |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3NbxUhECdaY_Ri6ldcbXVNvCnp7g4Ly8lYY_PU2ottfDcCC7RN7G5977Xa_96BZV-zTfQKJMAwHwzD_IaQN8JD2zLraWs0OihggGrOJLUcAEpetMJGtM8DPjtiX-b1PD24LdO3ylEnRkVt-za8ke-EvCkR7H39_vwXDVWjQnQ1ldC4Te4wABb4XMzF-o0lRLFYKVOuTAHNzhLtVcgpQw-sRFatqZzYowjbP7lr3vwpeSNcGq3Q3iZ5kK6P-YfhvB-SW657RO4OBSWvHpMf392ffKx5ghogP-3ys_hd0uWpPsRx3g6FHGy-6s8SYDW1yIiX2OQXQ6IDzuF_9r_zkJy0uHRPyNHep8OPM5pKJ9C2LsWKWqYBJa-ShecopgLNVNE4dB0Kg3eSkhvj68qbWhqrWVVZD5WXrLGohp31toSnZKPrO_csJHU3HoTwldHABJRGF9xoD55X2reNz8jbkYDqfEDIUDGyDY0ayK2Q3CqSW8mM7AYar0cGdOvY0C-OVRIW1YCxjAnWgrMMHSBdMmHQ9_G64VL6JiNb4wmpJHJLdc0gGXm97kZhCREQ3bn-Io5Bq40eLMuImJzsZEHTnu70JMJuywBmKHEH70YeuJ783xt-_v-1viL3Zoff9tX-54OvL8j9KnBmANzlW2Rjtbhw23jlWZmXka__AtJD_-g |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfR1da9UwNOhE8UXmF1Y3reCbhts2adI8iZte5gdD0OF9C0mTMweunffeTf33nqTpHR3oaxJIcnI-c74IeSGBtS13QFtr0EBhllEjuKJOMMZKUbTSxWqfh-LgiH9Y1IsU_7RKYZUjT4yM2vVt-COfhbwpGeR9PYMUFvH57fz12U8aOkgFT2tqp3Gd3EApWYQ2DnIhN_8twaPFS5XyZgrWzFYou0J-GVpjJaJtTdVENsUS_hO982rU5BXXaZRI821yJ6mS-Zvh7e-Sa767R24OzSX_3Cffvvjf-dj_BLlBftLlpzF00uepV8Rx3g5NHVy-7k9T8WrqECkvcAiWQ9ID7gE_-l95SFRaXvgH5Gj-7uv-AU1tFGhbl3JNHTcMqbBSBQgkWYkiq2g8mhGFRf2kFNZCXYGtlXWGV5UDVoHijUOW7B24kj0kW13f-UchwbsBJiVU1jAuWWlNIawBBqIy0DaQkZcjAPXZUC1DRy83a_QAbo3g1hHcWmVkL8B4szJUuo4D_fJYJ8LRDbOOc8lb5h1HY8iUXFq0g8A0QiloMrIzvpBO5LfSl8iSkeebaSSc4A0xne_P4xqU4GjN8ozIyctODjSd6U6-xxLcKhQ2VHiDVyMOXG7-7ws__v9Zn5FbiNL60_vDj0_I7SogZqi9K3bI1np57ndR-1nbpxGt_wKsWgQj |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Sex+differences+in+machine+learning+computed+tomography-derived+fractional+flow+reserve&rft.jtitle=Scientific+reports&rft.au=Al+Rifai%2C+Mahmoud&rft.au=Ahmed%2C+Ahmed+Ibrahim&rft.au=Han%2C+Yushui&rft.au=Saad%2C+Jean+Michel&rft.date=2022-08-16&rft.pub=Nature+Publishing+Group+UK&rft.eissn=2045-2322&rft.volume=12&rft.issue=1&rft_id=info:doi/10.1038%2Fs41598-022-17875-9&rft.externalDocID=10_1038_s41598_022_17875_9 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2045-2322&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2045-2322&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2045-2322&client=summon |