A nomogram for predicting ICU mortality of sepsis associated encephalopathy: a retrospective cohort study based on MIMIC-IV and eICU-CRD.

ABSTRACT:

Background

Sepsis-associated encephalopathy (SAE) is a fatal complication of sepsis, with a high mortality rate worldwide. This study aimed to reduce mortality and improve the quality of life of patients with SAEs by developing a practical nomogram to predict the risk factors associated with ICU mortality.

Method

The MIMIC database was used as the training set to build the model, and the eICU-CRD served as the validation set for external verification. LASSO regression analysis was conducted to identify predictive variables and develop the nomogram model. Receiver Operating Characteristic (ROC) curves were generated to assess the model's discriminative ability. Model calibration was assessed using calibration curves and the Hosmer-Lemeshow goodness-of-fit tests. Clinical deci

SUBMITTER: Hu X 

PROVIDER: S-EPMC12534946 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature