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Donor-Recipient Body Surface Area Mismatch and the Outcome of Liver Transplantation in the UK.

Ioannis D KostakisDimitri Aristotle RaptisBrian R DavidsonSatheesh IypeDavid NasrallaCharles ImberDinesh SharmaTheodora PissanouJoerg Matthias Pollok
Published in: Progress in transplantation (Aliso Viejo, Calif.) (2022)
Introduction: Too small or too big liver grafts for recipient's size has detrimental effects on transplant outcomes. Research Questions: The purpose was to correlate donor-recipient body surface area (BSA) ratio or BSA index (BSAi) with recipient survival, graft survival, hepatic artery or portal vein, or vena cava thrombosis. High and low BSAi cut-off points were determined. Design: There were 11,245 adult recipients of first deceased donor whole liver-only grafts performed in the UK from January 2000 until June 2020. The transplants were grouped according to the BSAi and compared to complications, graft and recipient survival. Results: The BSAi ranged from 0.491 to 1.691 with a median of 0.988. The BSAi > 1.3 was associated with a higher rate of portal vein thrombosis within the first 3 months (5.5%). This risk was higher than size-matched transplants (OR: 2.878, 95% CI: 1.292-6.409, P = 0.01). Overall graft survival was worse in transplants with BSAi ≤ 0.85 (HR: 1.254, 95% CI: 1.051-1.497, P = 0.012) or BSAi > 1.4 (HR: 3.704, 95% CI: 2.029-6.762, P < 0.001) than those with intermediate values. The graft survival rates were reduced by 2% for cases with BSAi ≤ 0.85 but were decreased by 20% for cases with BSAi > 1.4. These findings were confirmed by bootstrap internal validation. No statistically significant differences were detected for hepatic artery thrombosis, occlusion of hepatic veins/inferior vena cava or recipient survival. Conclusions: Donor-recipient size mismatch affects the rates of portal vein thrombosis within the first 3 months and overall graft survival in deceased-donor liver transplants.
Keyphrases
  • inferior vena cava
  • pulmonary embolism
  • vena cava
  • free survival
  • metabolic syndrome
  • adipose tissue
  • machine learning
  • deep learning
  • kidney transplantation
  • insulin resistance
  • skeletal muscle
  • big data
  • childhood cancer