Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Malamutmann, E; Roehrborn, F; Vershinina, K; Koitka, S; Jaradat, D; Schmitz, SM; Haubold, J; Neumann, UP; Nensa, F; Oezcelik, A.
AI-based body composition score predicts survival after liver transplantation.
Langenbecks Arch Surg. 2025; 410(1): 307
Doi: 10.1007/s00423-025-03885-4
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- Co-Autor*innen der Med Uni Graz
- Jaradat Derar
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- Abstract:
- PURPOSE: Body composition has a significant role to predict survival in patients with malignant disease. This study evaluates the importance of body composition for predicting short- and long-term survival after liver transplantation. Additionally, the sex specific differences will be evaluated. METHODS: Body composition, of all patients who underwent liver transplantation between January 2011 and December 2023 with computed tomography prior liver transplantation, was assessed fully automated with AI based technique. Pre-, intra- and postoperative data were retrospectively reported. Uni- and multivariate regression analyses was performed to identify independent prognostic factors for survival. The statistical analyses was performed separately for male and female with comparison of the both groups. RESULTS: There were 346 patients (60.1%male, 39.9%female) with median age of 52.2 years (SD 10.8) included to the study. The univariate and multivariate cox regression analyses have identified the ratio of the subcutaneous fat volume to muscle volume as well as the ratio of the visceral fat volume to muscle volume as significant prognostic parameter for the overall survival. The separate analyses of the two groups show that these factors predict survival in male and female. However, visceral fat and also the ratio of FVM is significantly higher in male. CONCLUSION: Based on the results of our study we can conclude that the ratio of visceral fat volume to muscle volume (FVM-ratio) has an essential impact on overall survival after liver transplantation in male and female patients. The fully automated AI based assessment is fast, accurate and investigator independent.
- Find related publications in this database (using NLM MeSH Indexing)
- Humans - administration & dosage
- Liver Transplantation - mortality
- Male - administration & dosage
- Female - administration & dosage
- Middle Aged - administration & dosage
- Body Composition - administration & dosage
- Retrospective Studies - administration & dosage
- Adult - administration & dosage
- Prognosis - administration & dosage
- Tomography, X-Ray Computed - administration & dosage
- Survival Rate - administration & dosage
- Aged - administration & dosage
- Sex Factors - administration & dosage
- Predictive Value of Tests - administration & dosage