Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture.

ABSTRACT:

Background

Skull fracture can lead to significant morbidity and mortality, yet the development of effective predictive tools has remained a challenge. This study aimed to establish and validate a nomogram to evaluate the 28-day mortality risk among patients with skull fracture.

Materials and methods

Data extracted from the Medical Information Mart for Intensive Care (MIMIC) database were utilized as the training set, while data from the eICU Collaborative Research Database were employed as the external validation set. This nomogram was developed using univariate Cox regression, best subset regression (BSR), and the least absolute shrinkage and selection operator (LASSO) methods. Subsequently, backward stepwise multivariable Cox regression was employed to refine predictor sel

SUBMITTER: Tang J 

PROVIDER: S-EPMC10811263 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature