Construction and Validation of a Risk Assessment Model for Sepsis-Associated Acute Lung Injury in Patients with Sepsis in the Intensive Care Unit.

PURPOSE

Sepsis-Associated Acute Lung Injury (SALI) represents a severe complication in sepsis patients, leading to poor clinical outcomes and increased mortality. This study aimed to develop and validate a reliable nomogram for early prediction of SALI in adult critically ill patients, addressing the critical need for timely risk stratification and intervention.

METHODS

A retrospective cohort study was conducted involving 345 intensive care unit (ICU) sepsis patients from the First People's Hospital of Huzhou. Patients were randomly divided into training (n = 241) and validation (n = 104) cohorts. Multivariate logistic regression and LASSO regression were employed to identify independent risk factors and construct a predictive nomogram.

RESULTS

Four independent risk factors were identified: PaCO2, PaO2, serum uric acid (SUA), and SOFA score. The developed nomogram demonstrated excellent discriminative performance, with area under the receiver operating characteristic curve (AUC) of 0.916 in the training cohort and 0.931 in the validation cohort. Calibration curves, decision curve, and SHapley Additive exPlanations (SHAP) analysis confirmed the model's robust predictive performance and clinical utility.

CONCLUSIONS

The novel nomogram provides a practical, visualized risk assessment tool for early SALI recognition, potentially improving patient outcomes through enhanced understanding and timely interventions in critically ill patients.