The AKI Prediction Score: a new prediction model for acute kidney injury after liver transplantation.
HPB (Oxford)
; 21(12): 1707-1717, 2019 12.
Article
en En
| MEDLINE
| ID: mdl-31153834
ABSTRACT
BACKGROUND:
Acute kidney injury (AKI) is a frequent complication after liver transplantation. Although numerous risk factors for AKI have been identified, their cumulative impact remains unclear. Our aim was therefore to design a new model to predict post-transplant AKI.METHODS:
Risk analysis was performed in patients undergoing liver transplantation in two centres (n = 1230). A model to predict severe AKI was calculated, based on weight of donor and recipient risk factors in a multivariable regression analysis according to the Framingham risk-scheme.RESULTS:
Overall, 34% developed severe AKI, including 18% requiring postoperative renal replacement therapy (RRT). Five factors were identified as strongest predictors donor and recipient BMI, DCD grafts, FFP requirements, and recipient warm ischemia time, leading to a range of 0-25 score points with an AUC of 0.70. Three risk classes were identified low, intermediate and high-risk. Severe AKI was less frequently observed if recipients with an intermediate or high-risk were treated with a renal-sparing immunosuppression regimen (29 vs. 45%; p = 0.007).CONCLUSION:
The AKI Prediction Score is a new instrument to identify recipients at risk for severe post-transplant AKI. This score is readily available at end of the transplant procedure, as a tool to timely decide on the use of kidney-sparing immunosuppression and early RRT.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Trasplante de Hígado
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Medición de Riesgo
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Lesión Renal Aguda
Tipo de estudio:
Diagnostic_studies
/
Etiology_studies
/
Prognostic_studies
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Risk_factors_studies
Límite:
Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
HPB (Oxford)
Asunto de la revista:
GASTROENTEROLOGIA
Año:
2019
Tipo del documento:
Article
País de afiliación:
Países Bajos