Association between ePWV and delirium risk in icu sepsis patients: a retrospective analysis based on the MIMIC database and development of a predictive model.

BACKGROUND: Sepsis, frequently complicated by delirium with poor prognosis, is common in the Intensive Care Unit (ICU). Estimated Pulse Wave Velocity (ePWV), a non-invasive arterial stiffness marker, remains unexplored regarding delirium risk in ICU sepsis patients. This study investigated ePWV's association with sepsis-linked delirium and developed a predictive model. METHODS: This retrospective cohort study utilized MIMIC-IV 3.1 data. ICU patients with sepsis meeting the Sepsis-3.0 criteria were randomly allocated in a 7:3 to the training and validation cohorts.The exposure was ePWV derived using age and blood pressure. The outcome was delirium, defined by the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Features were selected via Boruta and LASSO.Associations were examined using Cox models, Kaplan-Meier curves, restricted cubic splines, and subgroup analyses. Five machine learning models were evaluated. RESULTS: Among 24,889 patients (delirium incidence 44.4%), Kaplan-Meier analysis showed significant differences in delirium risk across ePWV levels (p < 0.0001). Cox regression indicated ePWV was positively associated with delirium (HR = 1.018, 95% CI: 1.008‒1.027), with the highest quartile showing 19% elevated risk versus the lowest (HR = 1.193). RCS analysis revealed a nonlinear relationship (p = 0.019). Subgroup analyses were significant except for cerebral infarction. K-Nearest Neighbor performed best with AUC = 0.736 in validation. SHAP analysis demonstrated respiratory failure, ARFand ACEI as key features. CONCLUSION: ePWV was independently associated with delirium risk in ICU sepsis patients. The machine learning model demonstrated good discriminative ability, facilitating early identification of high-risk patients.