A predictive model for sepsis risk in patients with non-traumatic cerebral hemorrhage based on the MIMIC-IV database.

ABSTRACT: Patients with non-traumatic cerebral hemorrhage admitted to the intensive care unit (ICU) are known to be at high risk for developing sepsis. However, limited research exists to quantify this risk. Therefore, this study aimed to develop a reliable predictive model to assess the risk of sepsis in ICU patients with non-traumatic cerebral hemorrhage. We extracted data on patients admitted to the ICU with non-traumatic cerebral hemorrhage from the Medical Information Mart for Intensive Care IV (MIMIC IV) database. Afterward, the patients were then randomized in a 7:3 ratio into a training set (N = 1,365) and a validation set (N = 585). Least Absolute Shrinkage and Selection Operator (LASSO) regression and stepwise logistic regression were employed to screen variables within the training set. T

SUBMITTER: Wu X 

PROVIDER: S-EPMC12241317 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature