Remnant cholesterol inflammatory index, calculated from residual cholesterol to C-reactive protein ratio, and stroke outcomes: a retrospective study using the National institutes of health stroke scale and modified Rankin scale - Yanmei Yu; Yiming Zhang; Chunyan Zhu; Tingting Duan; Zichen Rao (Lipids in Health and Disease)
Abstract Background Globally, acute ischemic stroke (AIS) persists as a significant driver of both mortality and prolonged disability. Reliable biomarkers for predicting stroke outcomes must be identified to improve clinical decision-making. Residual cholesterol (RC) and RC inflammatory index (RCII) have been proposed as potential biomarkers, although their precise prognostic significance in stroke remains unclear. This research sought to examine the predictive value of RCII and RC in estimating extent of neurological impairment, assessed using the National Institutes of Health Stroke Scale (NIHSS), and functional recovery, evaluated using the three-month modified Rankin Scale (mRS), among individuals diagnosed with AIS. Methods The study enrolled 775 individuals diagnosed with AIS. RC and RCII were derived and subsequently grouped into quartiles for analysis. The associations between RCII, RC, NIHSS, and the three-month mRS were investigated using multivariable logistic regression analysis. Subpopulation analysis, inflection point analysis, generalized additive models (GAM), and receiver operating curve (ROC) analyses were utilized to evaluate the ability of these biomarkers to predict outcomes and to identify their optimal cutoff points. Results RCII demonstrated a significant relationship with unfavorable functional prognosis, with participants belonging to the top quartile of RCII levels having almost double the risk of poor outcomes compared to those in the lowest quartile. (odds ratio [OR] = 1.98, 95% confidence interval [CI]; 1.20–3.26, P = 0.0071). RC showed no significant association with the NIHSS or three-month mRS (P > 0.05). ROC analysis demonstrated that the RCII exhibited moderate discriminatory power in predicting poor three-month outcomes (AUC = 0.641, 95% CI; 0.595–0.688), whereas RC demonstrated modest predictive performance (AUC = 0.519, 95% CI; 0.475–0.564, P = 0.0018). GAM analysis revealed a J-shaped relationship for RCII, with optimal thresholds of 2.47 for NIHSS and 0.45 for three-month mRS, indicating significant associations above these cutoffs. The subgroup analysis showed stronger associations for RCII in men, smokers, and individuals with hypertension, but no significant associations were found for RC in any subgroup. Conclusion The RCII serves as an independent predictor of unfavorable three-month prognoses among individuals diagnosed with AIS. As a composite biomarker combining lipid and inflammatory factors, the RCII can enhance early risk stratification and guide personalized prognostic prediction in Acute stroke management.