Abstract Number: Esoc2026a868 Obesity- And Dyslipidemia-Related Indices as Predictors of Post-Stroke Depression: A Multicenter Observational Study

Abstract Background and aims This study evaluated the predictive value of selected obesity- and dyslipidemia-related indices for post-stroke depression in ischemic stroke patients and identified the most reliable indicator for early screening. Methods This observational study was conducted from July 2023 to May 2025 at Al-Azhar University Hospitals and Cairo Fatemia Hospital, enrolling 460 ischemic stroke patients. Anthropometric and metabolic indices—including BMI, WC, WHtR, VAI, BRI, LAP, CVAI, TyG index, and TyG-related parameters—were assessed. Post-stroke depression was diagnosed using standardized clinical tools. Associations with PSD were analyzed using multivariable logistic regression, and predictive performance with optimal cutoff values was evaluated by ROC curve analysis. Results Post-stroke depression was identified in 158 patients (34.3%). After adjustment for demographic and clinical confounders, several obesity- and lipid-related indices were independently associated with PSD (p 0.05). CVAI, LAP, TyG index, and WHtR showed the strongest associations with PSD. ROC curve analysis demonstrated that CVAI had the highest predictive accuracy (AUC = 0.70, 95% CI: 0.65–0.75), followed by LAP (AUC = 0.67) and TyG index (AUC = 0.65). A CVAI cutoff value of ≥127 yielded optimal sensitivity and specificity for PSD prediction. Increasing levels of adiposity- and dyslipidemia-related indices were associated with a progressively higher risk of PSD. Conclusions Obesity- and dyslipidemia-related indices are significantly associated with post-stroke depression. CVAI emerged as the most effective predictor of PSD in ischemic stroke patients. These easily obtainable indices may be useful as screening tools for early identification of patients at risk of PSD, allowing prompt psychological evaluation and management. Conflict of interest Nothing to disclose