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Risk index for early infections following living donor liver transplantation

INTRODUCTION: Post-operative infections in patients undergoing living donor liver transplantation (LDLT) are a major cause of morbidity and mortality. This study aims to develop a practical and efficient prognostic index for early identification and possible prediction of post-transplant infections...

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Detalles Bibliográficos
Autores principales: Elkholy, Shaimaa, Mansour, Doaa Ahmed, El-Hamid, SamahAbd, Al-Jarhi, Ula M., El-Nahaas, Saeed M., Mogawer, Sherif
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Termedia Publishing House 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6524199/
https://www.ncbi.nlm.nih.gov/pubmed/31110531
http://dx.doi.org/10.5114/aoms.2019.84736
Descripción
Sumario:INTRODUCTION: Post-operative infections in patients undergoing living donor liver transplantation (LDLT) are a major cause of morbidity and mortality. This study aims to develop a practical and efficient prognostic index for early identification and possible prediction of post-transplant infections using risk factors identified by multivariate analysis. MATERIAL AND METHODS: One hundred patients with post-hepatitic cirrhosis, HCV positive, genotype 4, Child B/C or MELD score 13-25 undergoing LDLT were included. All potential predictors of infection were analyzed by backward logistic regression. Cut-off values were obtained from ROC curve analysis. Significant predictors were combined into a risk index, which was further tested and compared by ROC curve analysis. RESULTS: Post-operative infection was associated with a significantly higher mortality (50.7% vs. 33.3%). Total leucocyte count, total bilirubin, early biliary complications, fever and C-reactive protein were found to be independent predictors of early infectious complications after LDLT. The risk index predicted infection with the highest sensitivity and specificity as compared with each predictor on its own (AUC = 0.91, 95% CI: 0.830–0.955, p < 0.0001). CONCLUSIONS: The use of a combined risk index for early diagnosis of post-operative infections can efficiently identify high risk patients.