Methodological development study: Dynamic mask attention graph neural network for mechanical ventilation in elderly intensive care unit patients.

ABSTRACT:

Objective

With the intensifying global population aging, the demand for mechanical ventilation in geriatric patients is rising. Given their complex physiological traits and sparse intensive care unit (ICU) data, accurate intubation prediction is difficult. Premature intubation may raise the risk of hypoxic organ damage, whereas delayed intubation can lead to increased ventilator-associated mortality. Therefore, developing precise intubation prediction models is vital for elderly ICU patients.

Methods

This study retrospectively analyzed data from ICU patients aged over 65 years in the MIMIC-IV and eICU databases. The intubation prediction task was formulated using a sliding window with a strict temporal data split to avoid data leakage. We propose a dynamic mask attention gra

SUBMITTER: Xie Y 

PROVIDER: S-EPMC12317266 | biostudies-literature | 2025 Jan-Dec

REPOSITORIES: biostudies-literature