SPLENIC ARTERY SYNDROME AFTER LIVER TRANSPLANTATION – PREDICTIVE FACTORS: EXPERIENCE OF A CENTER

• Autor(a) principal: L., Domingues
• Data de Publicação: 2021
• Outros Autores: Diogo, D., Donato, P., Pereira da Silva, F., Martins, R., Oliveira, P., Tralhão, G., Furtado, E.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.34635/rpc.896

Splenic artery syndrome (SAS) is described as a decrease in hepatic artery (HA) flow associated with increased flow in the splenic artery (SA). The present study aim was to identify predictive factors of SAS. A retrospective study was conducted in 70 patients, undergoing liver transplantation (LT) between 03/2010 until 08/2016. The case group (n=27) corresponded to the patients who developed SAS and the control group (n=43) to the patients who didn’t develop. The donor, recipient and graft variables were collected. Significant differences were observed in relation to spleen volume 1137,4±512,9) cm3 vs 523,9±258,1cm3, spleen volume/ liver volume ratio 0,9±0,3 vs 0,4±0,2, difference in caliber between SA and HA 2,1±1,6mm vs 0,8±1,5mm, and the ratio between spleen volume and body mass index (BMI) of the recipient 47,9±24,5 vs 18,9±8,8 between the case and control group respectively. In case group the mean difference between pre-embolization and post-embolization resistive index (RI) was 0.2±0.1, which demonstrates a significant improvement after embolization of the SA (p<0.001, CI: 95% 0.11-0.25). In logistic regression, the retained variable was only the spleen volume (p<0.05), and the cut-off point was 1023.9 cm3. It’s possible to conclude that spleen volume is a risk factor for SAS. It’s also important to note that significant differences between groups were evident in relation to the ratio spleen volume/liver volume and difference in caliber between SA and HA in the pre-LT. In this sense, it’s relevant in future studies to develop a prospective methodological design in order to analyze the predictive value of these variables.