Prediction of central venous catheter-associated deep venous thrombosis in pediatric critical care settings.

ABSTRACT:

Background

An increase in the incidence of central venous catheter (CVC)-associated deep venous thrombosis (CADVT) has been reported in pediatric patients over the past decade. At the same time, current screening guidelines for venous thromboembolism risk have low sensitivity for CADVT in hospitalized children. This study utilized a multimodal deep learning model to predict CADVT before it occurs.

Methods

Children who were admitted to intensive care units (ICUs) between December 2015 and December 2018 and with CVC placement at least 3 days were included. The variables analyzed included demographic characteristics, clinical conditions, laboratory test results, vital signs and medications. A multimodal deep learning (MMDL) model that can handle temporal data using long short-t

SUBMITTER: Li H 

PROVIDER: S-EPMC8627017 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature