Prognostic nomogram for 30-day mortality of deep vein thrombosis patients in intensive care unit.

ABSTRACT:

Background

We aimed to use the Medical Information Mart for Intensive Care III database to build a nomogram to identify 30-day mortality risk of deep vein thrombosis (DVT) patients in intensive care unit (ICU).

Methods

Stepwise logistic regression and logistic regression with least absolute shrinkage and selection operator (LASSO) were used to fit two prediction models. Bootstrap method was used to perform internal validation.

Results

We obtained baseline data of 535 DVT patients, 91 (17%) of whom died within 30 days. The discriminations of two new models were better than traditional scores. Compared with simplified acute physiology score II (SAPSII), the predictive abilities of two new models were improved (Net reclassification improvement [NRI] > 0; Integrated discr

SUBMITTER: Shen R 

PROVIDER: S-EPMC7788873 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature