An interactive nomogram to predict healthcare-associated infections in ICU patients: A multicenter study in GuiZhou Province, China.

ABSTRACT:

Objective

To develop and validate an interactive nomogram to predict healthcare-associated infections (HCAIs) in the intensive care unit (ICU).

Methods

A multicenter retrospective study was conducted to review 2017 data from six hospitals in Guizhou Province, China. A total of 1,782 ICU inpatients were divided into either a training set (n = 1,189) or a validation set (n = 593). The patients' demographic characteristics, basic clinical features from the previous admission, and their need for bacterial culture during the current admission were extracted from electronic medical records of the hospitals to predict HCAI. Univariate and multivariable analyses were used to identify independent risk factors of HCAI in the training set. The multivariable model's performance was eval

SUBMITTER: Zhang M 

PROVIDER: S-EPMC6629073 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature