Abstract
ObjectiveThe aims of this study were to develop and validate a prediction model for severe disturbance of consciousness (SDOC) occurring within 30 days of intensive care unit (ICU) admission in patients with non-traumatic intracranial hemorrhage (NTICH), and to compare and validate the predictive value of anion gap (AG), serum albumin, and albumin-corrected anion gap (ACAG) for SDOC in this population.MethodsThis study is a retrospective cohort study. It included a total of 873 patients with NTICH from the Medical Information Mart for Intensive Care (MIMIC-IV) database. These patients were randomly allocated in a 7:3 ratio to a training cohort (n = 611) and a validation cohort (n = 262). Variables selected from the Least Absolute Shrinkage and Selection Operator (LASSO) regression were subsequently entered into a multivariable logistic regression analysis, with those demonstrating a P-value< 0.05 incorporated into the final model to develop a dynamic nomogram. The discriminative ability of the model was evaluated by receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Model performance was assessed using calibration curves and the Hosmer-Lemeshow goodness-of-fit test (HL test). Furthermore, decision curve analysis (DCA) was employed to evaluate the net clinical benefit of the model.ResultsWe developed a 14-variable prediction model for the occurrence of SDOC within 30 days of NTICH patients' ICU admission. The prediction model demonstrated satisfactory discriminative ability in the validation cohort, with an AUC of 0.870. Notably, ACAG showed superior predictive performance compared to AG and serum albumin alone. The constructed nomogram exhibited good calibration performance. DCA further confirmed the clinical utility of this predictive model.ConclusionsThis study developed a prediction model for estimating the risk of SDOC within 30 days of admission in patients with NTICH. Furthermore, ACAG demonstrated significant importance in patients who developed SDOC.