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ABSTRACT: Introduction
Existing laboratory markers and clinical scoring systems have shown suboptimal accuracies for early prediction of persistent organ failure (POF) in acute pancreatitis (AP). We used information theory and machine learning to select the best-performing panel of circulating cytokines for predicting POF early in the disease course and performed verification of the cytokine panel's prognostic accuracy in an independent AP cohort.Methods
The derivation cohort included 60 subjects with AP with early serum samples collected between 2007 and 2010. Twenty-five cytokines associated with an acute inflammatory response were ranked by computing the mutual information between their levels and the outcome of POF; 5 high-ranking cytokines were selected. These cytokines were sub
SUBMITTER: Langmead C
PROVIDER: S-EPMC8104185 | biostudies-literature | 2021 May
REPOSITORIES: biostudies-literature