Acute-phase serum metabolomics signatures for predicting post-stroke cognitive impairment after ischemic stroke: a prospective cohort study.

BACKGROUND: Post-stroke cognitive impairment (PSCI) is a common long-term complication of acute ischemic stroke often accompanied by metabolic disorder, yet early metabolomic predictors remain poorly characterized. This study aimed to identify acute-phase serum metabolomic signatures associated with PSCI and develop a prediction model for early PSCI risk stratification. METHODS: In this prospective study, 130 acute ischemic stroke patients were enrolled. Serum samples collected within 24 h of stroke onset were subjected to untargeted metabolomic profiling. Cognitive status was assessed at 3 months after stroke. KEGG pathway and MECNA analyses were performed to assess pathway-level and metabolite-metabolite correlation patterns. Bootstrap-LASSO stability selection and logistic regression were used to develop a prediction model, which was evaluated by stratified 10-fold cross-validation. Calibration curves and decision curve analysis assessed model performance. RESULTS: A total of 51 candidate differential metabolites were identified between PSCI and Non-PSCI patients, involving purine/caffeine-related metabolism, bile acid metabolism, lipid and fatty acid metabolism, and amino acid-related metabolism. MECNA identified 15,120 differential metabolite-metabolite correlation pairs, suggesting distinct acute-phase serum correlation patterns in patients who later developed PSCI. Six metabolites were retained in the final model: 6-Hydroxymellein, 21-Deoxycortisol, Inosine, 2-Hydroxy-3-methylbutyric acid, Isoleucyl-Arginine, and Propylparaben. The metabolite-only model achieved an AUC of 0.774 (95% CI, 0.690-0.853), showing higher discrimination than the core clinical-only model and the combined clinical-metabolomic model. CONCLUSIONS: Acute-phase serum metabolomic profiling identified multi-domain metabolic features associated with PSCI. The internally validated six-metabolite model showed moderate performance for early PSCI risk stratification.