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Sex differences in machine learning computed tomography-derived fractional flow reserve
- Source :
- Scientific Reports, Vol 12, Iss 1, Pp 1-9 (2022)
- Publication Year :
- 2022
- Publisher :
- Nature Portfolio, 2022.
-
Abstract
- 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
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 12
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Scientific Reports
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.83bd4474c3ed4182a147b255fa8699f8
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41598-022-17875-9