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Post-operative acute renal failure is a severe post-operative complication and is associated with high mortality. The enhanced prediction score, including pre-as well as intra-operative predictors accurately predicted ARF following hepatic surgery. This prediction score allows early identification of patients at high risk of ARF and may support decision-making for protective kidney treatment.
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To enhance and validate an already pre-existing score accurately predicting post-operative acute renal failure (ARF) after hepatic surgery
We will enhance a pre-existing score predicting ARF based on pre-operative as well as intra-operative predictors.
Development process: we will identify the strongest predictors of ARF in a multivariable logistic regression model followed by a stepwise backward logistic regression analysis and bootstrapping.
Validation process: we will perform an internal validation by calibrating the prediction model as well as by k-fold cross validation (c statistics) and bootstrapping. Additionally, we will calculate the discrimination by the area under the curve (AUC).
Decision curve analysis: Furthermore we will perform a decision curve analysis to evaluate the clinical consequences of both prediction scores whether a patient with increased ARF risk would post-operative benefit of a treatment on the ICU.
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549 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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