Abstracts of the 2023 Annual Meeting of the ALEH
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Introduction and ObjectivesLiver transplantation is the only curative procedure for liver cirrhosis, where pharmacotherapeutic factors are crucial to avoid complications. Transplant rejection is an adverse event that endangers the transplanted organ and the patient's life. Objective: To determine the clinical, pharmacotherapeutic, and morbid factors associated with rejection and mortality in patients during the first year after orthotopic liver transplantation.
Patients / Materials and MethodsRetrospective cohort study in patients who underwent liver transplantation at the Clinical Hospital of the University of Chile from August 2019 to August 2022, with at least one year of post-transplant follow-up. The days until rejection (confirmed by biopsy) and death were recorded to perform a survival analysis using Cox Proportional Hazards Regression. The effect magnitude of each associated factor was evaluated using Hazard Ratio (HR) and its 95% Confidence Interval (95% CI).
Results and DiscussionDuring the study period, 63 patients underwent transplantation; 60% (38) were men, and the median age was 60 (IQR 52-63) years. The incidence of rejection was 43% (27), of which 11 (17%) were biopsy-confirmed, and 6% (4) of the patients died during the first year.
Risk factors for biopsy-confirmed rejection included using analgesics before transplantation (HR: 8.7, 95% CI: 2.2 – 34.5) and the average prednisone dose in the first month (HR: 1.1, 95% CI: 1.02 – 1.18). Protective factors included age (HR: 0.96, 95% CI: 0.92 – 0.99), average tacrolimus dose (HR: 0.5, 95% CI: 0.38 – 0.71), and average mycophenolate dose (HR: 0.998, 95% CI: 0.996 – 0.999).
Regarding mortality, the risk factor identified was the occurrence of re-transplantation (HR: 11.3, 95% CI: 1.16 – 109.3).
ConclusionsHigher doses of tacrolimus and mycophenolate were associated with a lower risk of rejection, while higher doses of prednisone were associated with a higher risk of the event. Considering the factors that can predict the event would help optimize therapy and improve clinical outcomes.