A risk nomogram for predicting prolonged intensive care unit stays in patients with chronic obstructive pulmonary disease.

ABSTRACT:

Background

Providing intensive care is increasingly expensive, and the aim of this study was to construct a risk column line graph (nomograms)for prolonged length of stay (LOS) in the intensive care unit (ICU) for patients with chronic obstructive pulmonary disease (COPD).

Methods

This study included 4,940 patients, and the data set was randomly divided into training (n = 3,458) and validation (n = 1,482) sets at a 7:3 ratio. First, least absolute shrinkage and selection operator (LASSO) regression analysis was used to optimize variable selection by running a tenfold k-cyclic coordinate descent. Second, a prediction model was constructed using multifactorial logistic regression analysis. Third, the model was validated using receiver operating characteristic (RO

SUBMITTER: Cheng H 

PROVIDER: S-EPMC10359115 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature