Deep learning–derived abdominal adiposity phenotypes and 28-day mortality in sepsis
Authors' conclusion
Greater SAT CSA and a higher VAT/SAT ratio showed opposing adjusted associations with 28-day mortality.
Study context
- Population
- Adults with sepsis with abdominal computed tomography (CT); adiposity measured at L3-L4
- Participants
- 1,107 adults
- Exposure
- Abdominal adipose tissue measures per 1-SD increase
- Outcome
- 28-day mortality
- Follow-up
- 28 days
Methodological detailssingle-centre, automated CT analysis (pretrained nnU-Net-based segmentation)
- Single-centre
- Automated CT analysis (pretrained nnU-Net-based segmentation)
Main finding
As reported in the abstract
Died within 28 days during index hospitalization
300
27.1%
Observational data: associations, not effects.
Further findings
28-day mortality by BMI category (exploratory BMI-stratified analyses)
- Greater SAT CSA among underweight patients: adjusted HR 0.37; 95% CI 0.16-0.83
- Higher visceral adipose tissue (VAT)/SAT ratio among patients with obesity: adjusted HR 1.48; 95% CI 1.18-1.85
- Interactions with BMI category not significant: P for interaction = 0.145 (SAT CSA) and 0.127 (VAT/SAT ratio)
- Exploratory
28-day mortality by psoas muscle measures
- Only higher low-attenuation muscle proportion remained associated after adjustment: adjusted HR 1.14; 95% CI 1.01-1.28; P = 0.033
Original publication
Deep learning–derived abdominal adiposity phenotypes and 28-day mortality in sepsis. Int J Obes (Lond). Published 19 September 2026. doi:10.
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