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. 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. 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. 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.

Objective: To investigate the association between the Systemic Immune-Inflammation Index (SII) and the severity of acute ischemic stroke (AIS), as measured by the National Institutes of Health Stroke Scale (NIHSS), and to explore its potential as a predictive marker for clinical outcomes.Methods: We used the data of 1723 AIS patients in the Stroke Center of Quzhou People’s Hospital from September 2016 to September 2022 for a cross-sectional study. SII was calculated as platelet count × neutrophil count divided by lymphocyte count. Stroke severity was classified as mild (NIHSS < 8) or severe (NIHSS ≥ 8). Multivariable logistic regression and subgroup analyses were performed to evaluate the relationship between SII levels and NIHSS scores, adjusting for confounders such as age, sex, and comorbidities. Nonlinear associations and threshold effects were further assessed using smooth curve fitting.Results: Elevated SII levels were independently associated with higher stroke severity (OR: 1.04, 95% CI: 1.01–1.07). A nonlinear relationship was identified, with a critical range of SII/100 values (2.4–7.8) demonstrating the strongest correlation with NIHSS scores. Patients in the highest SII quartile (Q4) exhibited a 3.46-fold increase in odds of severe stroke compared to those in the lowest quartile (Q1) (p < 0.001). Subgroup analyses confirmed the robustness of these findings across diverse demographic and clinical profiles.Conclusion: SII is a robust biomarker for predicting stroke severity in AIS patients. The observed nonlinear relationship highlights its potential utility in identifying critical inflammatory thresholds for risk stratification and personalized therapeutic interventions.

Acute ischemic stroke (AIS) prognosis is significantly influenced by early neurological deterioration (END). Emerging evidence suggests that thyroid function, particularly free triiodothyronine (FT3) levels and the FT3/FT4 ratio, may play a crucial role in END occurrence. This study aimed to investigate the association between thyroid function parameters and END. This study included a total of 1767 AIS patients. Multivariable regression analysis was conducted to assess the associations between FT3, the FT3/FT4 ratio, and other thyroid function parameters with END. Subgroup analyses were performed to explore the potential moderating effects of age, smoking status, and sex on these relationships. The predictive performance of the models was evaluated using receiver operating characteristic (ROC) curves. The FT3 levels (3.66 vs. 4.03 pmol/L, P < 0.001) and the FT3/FT4 ratio (0.28 vs. 0.30, P < 0.001) were significantly lower in the END group compared to the non-END group. Multivariable regression analysis identified a higher FT3/FT4 ratio as an independent protective factor against END (OR = 1.20, 95 % CI: 1.07-1.35, P = 0.0014). Subgroup analyses demonstrated that this protective effect was more pronounced inpatients older than 70 years, and non-smokers. Furthermore, the predictive model incorporating thyroid function parameters demonstrated certain predictive advantages over the CRP-based model (AUC = 0.688 vs. 0.624, P = 0.0036), suggesting its potential utility in predicting early neurological deterioration in AIS patients. Lower FT3 levels and a reduced FT3/FT4 ratio are significantly associated with a higher risk of END. The FT3/FT4 ratio may serve as a valuable biomarker for risk stratification in AIS patients, underscoring the potential role of thyroid function in stroke management.

Objective To evaluate the association between the stress hyperglycaemia ratio (SHR) and baseline stroke severity in patients with acute ischaemic stroke (AIS) and to investigate whether the relationship is non-linear. Design Retrospective cohort study. Setting A tertiary hospital in Zhejiang Province, China. Participants 1479 consecutive AIS patients admitted within 24 hours of symptom onset between 2016 and 2022. Primary and secondary outcome measures SHR was calculated as fasting plasma glucose (mmol/L) divided by glycated haemoglobin (HbA1c, %). Stroke severity was assessed by the NIH Stroke Scale (NIHSS) and categorised as mild (NIHSS ≤5) or moderate to severe (NIHSS >5). Associations between SHR and stroke severity were examined using multivariable logistic regression, generalised additive models and threshold effect analysis. Results Patients with more severe strokes had significantly higher SHR values (median 0.99 vs 0.94; p<0.001). After full adjustment, higher SHR remained independently associated with increased odds of moderate-to-severe stroke (OR=2.90; 95% CI: 1.60 to 5.26; p=0.0004). SHR in the highest quartile (Q4) was linked to a greater risk compared with the lowest quartile (Q1) (OR=1.90; 95% CI: 1.31 to 2.76; p=0.0008). Non-linear analysis revealed a threshold at SHR=1.3, with sharply increased risk below this point (OR=6.11; 95% CI: 2.64 to 14.15; p<0.0001). Subgroup findings were consistent, with a significant interaction across TOAST subtypes (P for interaction=0.0042). Conclusions SHR is independently associated with greater stroke severity at admission. Values below 1.3 may reflect heightened metabolic stress and could help inform early risk stratification in AIS management, but their discriminative power is limited and should be interpreted in conjunction with other clinical indicators.

Background: Lipid-related parameters have been linked to vascular risk, yet their association with post-stroke functional recovery remains uncertain. We aimed to examine whether lipoprotein imbalance is associated with 3-month functional outcome after acute ischemic stroke. Methods: In this retrospective cohort study, 748 patients with acute ischemic stroke were included. Poor functional outcome was defined as modified Rankin Scale (mRS) > 2 at 3 months. Fourteen lipid-related parameters were analyzed. Multivariable logistic regression, generalized additive models, two-piecewise regression, and subgroup analyses were performed with adjustment for age, sex, smoking, hypertension, diabetes, atrial fibrillation (AF), Trial of Org 10,172 in Acute Stroke Treatment (TOAST) classification, and baseline National Institutes of Health Stroke Scale (NIHSS) score. Results: LDL-related measures were independently associated with poor functional outcome. Specifically, each unit increase in lbLDL-C/HDL-C (OR 1.86, 95% CI 1.32–2.63, p < 0.001) and TC/HDL-C (OR 1.27, 95% CI 1.02–1.57, p = 0.031) was linked to higher risk of poor functional outcome. Compared with the lowest quartile, patients in the highest quartile of lbLDL-C/HDL-C (OR 3.10, 95% CI 1.60–6.01, p < 0.001) and LDL-C/HDL-C (OR 2.85, 95% CI 1.43–5.67, p = 0.003) showed the strongest associations. Most LDL-related indices including NHHR, TC, and lbLDL-C showed positive associations (all p < 0.05), whereas TG and TG/HDL-C displayed decreasing trends. Exploratory smooth-curve and threshold analyses suggested non-linear patterns for HDL-C and remnant cholesterol, although remnant cholesterol was not independently associated with functional outcome in the primary adjusted analyses. AF significantly modified the associations of lipid ratios with outcome, with stronger associations observed among patients without AF. Conclusion: Lipoprotein imbalance, reflected by LDL-related ratios, was associated with 3-month functional outcome after ischemic stroke. The observed non-linear patterns and interaction with AF suggest heterogeneity in lipid-outcome associations after ischemic stroke. These exploratory findings require further validation in independent cohorts.