Heart failure & cardiomyopathies
Sarcopenia Assessment Using Fully Automated Deep Learning Predicts Cardiac Allograft Survival in Heart Transplant Recipients
Main finding · Cardiac allograft survival (sarcopenia at T11)Result — go to the resultHazard ratio 3.86 95% CI 1.35–11.0Authors' conclusion
Fully automated quantification of radiographic sarcopenia using pretransplant chest computed tomography successfully predicts cardiac allograft survival.
Study context
- Population
- Adult heart transplant recipients, January 2013–December 2022
- Participants
- 164 recipients
- Exposure
- Radiographic sarcopenia at T11 vs no sarcopenia
- Outcome
- Cardiac allograft survival
Main finding
Cardiac allograft survival (sarcopenia at T11)
Hazard ratio
3.86
95% CI 1.35–11.0
P = 0.01
By group
Sarcopenia
- 1 year
- 90%
- 3 years
- 83%
No sarcopenia
- 1 year
- 98%
- 3 years
- 97%
1 year
Sarcopenia90%
No sarcopenia98%
3 years
Sarcopenia83%
No sarcopenia97%
Sarcopeniavs No sarcopenia
HR 3.86 (95% CI 1.35–11.0); P = 0.01
As reported in the abstract
Observational data: associations, not effects.
Further findings
Hospital length of stay
P = 0.046
| Outcome | P value |
|---|---|
| Skeletal muscle index by sexWomen vs Men | P < 0.001 |
- Skeletal muscle index by sex: Women mean 28.3 (SD 7.6) cm²/m²
- Skeletal muscle index by sex: Men mean 33.1 (SD 8.1) cm²/m²
Original publication
Sarcopenia Assessment Using Fully Automated Deep Learning Predicts Cardiac Allograft Survival in Heart Transplant Recipients. Circ Heart Fail. Published 20 August 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →