Prediction of Multiple Organ Failure Complicated by Moderately Severe or Severe Acute Pancreatitis Based on Machine Learning: A Multicenter Cohort Study.

ABSTRACT:

Background

Multiple organ failure (MOF) may lead to an increased mortality rate of moderately severe (MSAP) or severe acute pancreatitis (SAP). This study is aimed to use machine learning to predict the risk of MOF in the course of disease.

Methods

Clinical and laboratory features with significant differences between patients with and without MOF were screened out by univariate analysis. Prediction models were developed for selected features through six machine learning methods. The models were internally validated with a five-fold cross-validation, and a series of optimal feature subsets were generated in corresponding models. A test set was used to evaluate the predictive performance of the six models.

Results

305 (68%) of 455 patients with MSAP or SAP developed MOF

SUBMITTER: Xu F 

PROVIDER: S-EPMC8112913 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature