Valvular & structural heart disease
Deep Learning-Based 3D Computed Tomography (CT) Body Composition Is Associated With Mortality in Patients Undergoing Transcatheter Aortic Valve Replacement
Authors' conclusion
Automated 3-dimensional CT-derived body composition measures provide independent prognostic information and improve risk stratification for mortality after transcatheter aortic valve replacement. Low subcutaneous adipose tissue volume and higher adipose tissue attenuation identify patients at increased risk, whereas higher skeletal muscle volume and attenuation are associated with lower mortality.
Study context
- Population
- Patients undergoing transcatheter aortic valve replacement with preprocedural CT imaging, 2014–2023
- Participants
- 915 patients
- Exposure
- Automated CT-derived body composition measures added to demographics and cardiometabolic risk factors for association with mortality
Methodological detailsconsecutive patients
- Consecutive patients
Main finding
As reported in the abstract
Mortality · median follow-up of 22 months (interquartile range, 14-36)
Died
160
17.5%
Observational data: associations, not effects.
Further findings
| Outcome | Harrell C | P value |
|---|---|---|
| Discrimination for mortality (Harrell C) | 0.66 versus 0.71 | P < 0.001 |
Body composition and mortality (restricted cubic spline analyses)
- Lower subcutaneous adipose tissue volume and higher adipose tissue attenuation associated with increased mortality
- Higher skeletal muscle volume and attenuation associated with improved survival
Original publication
Deep Learning-Based 3D CT Body Composition Is Associated With Mortality in Patients Undergoing Transcatheter Aortic Valve Replacement. Circ Cardiovasc Imaging. Published 20 October 2026. doi:10.
Summarised from the published abstract; every number is checked against it