Comprehensive risk factor-based nomogram for predicting one-year mortality in patients with sepsis-associated encephalopathy.

ABSTRACT: Sepsis-associated encephalopathy (SAE) is a frequent and severe complication in septic patients, characterized by diffuse brain dysfunction resulting from systemic inflammation. Accurate prediction of long-term mortality in these patients is critical for improving clinical outcomes and guiding treatment strategies. We conducted a retrospective cohort study using the MIMIC IV database to identify adult patients diagnosed with SAE. Patients were randomly divided into a training set (70%) and a validation set (30%). Least absolute shrinkage and selection operator regression and multivariate logistic regression were employed to identify significant predictors of 1-year mortality, which were then used to develop a prognostic nomogram. The model's discrimination, calibration, and clinical utilit

SUBMITTER: Jin G 

PROVIDER: S-EPMC11473772 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature