Abstract
Abstract Objective The Cholesterol, High-density lipoprotein, and Glucose (CHG) index is a novel biomarker related to glucose metabolism and exhibits a significant statistical association with insulin resistance levels. Compared to the Triglyceride-Glucose (TyG) index, the CHG index demonstrates higher sensitivity and specificity in evaluating glucose and lipid metabolism. Currently, no studies have explored the relationship between the CHG index and short-term prognosis in patients with acute ischemic stroke. Therefore, this study aims to investigate the association between the CHG index and short-term prognosis in acute ischemic stroke patients and to integrate the CHG index with clinical prediction assessment systems to improve predictive efficiency. Methods This study is a single-center observational study. The study enrolled 1728 acute ischemic stroke patients aged 18 years or older and conducted a 3-month short-term follow-up. The CHG index was calculated upon hospital admission and categorized into quartiles (Q1–Q4) from lowest to highest. Logistic regression models, restricted cubic spline analysis, and subgroup analysis were employed to explore the association between the CHG index and short-term prognosis, as well as potential nonlinear relationships. Mediation effects were further examined using various statistical methods. After establishing the relationship, the CHG index was incorporated as a predictive variable into a nomogram model. The predictive performance and clinical applicability of the new nomogram were evaluated using calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Continuous variables were compared using independent t-tests or Mann–Whitney U tests, while categorical variables were presented as counts and percentages and compared using chi-square tests. Results The CHG index showed a nonlinear positive correlation with the risk of poor short-term prognosis in acute ischemic stroke patients (P for overall 0.05). Multivariate logistic analysis revealed that the highest CHG quartile (Q4) had the greatest risk of poor short-term prognosis and mortality compared to the lowest quartile (Q1) (OR = 2.020, 95% CI 1.354–3.014, P = 0.001; OR = 6.953, 95% CI 2.730–17.713, P = 0.001). The risk of poor prognosis increased progressively with higher CHG levels (OR = 1.838, 95% CI 1.321–2.558, P = 0.001; OR = 4.642, 95% CI 2.134–10.099, P = 0.001). Subgroup analysis indicated an interaction between Sex and short-term mortality risk (P for interaction = 0.044). The nomogram model incorporating the CHG index demonstrated excellent clinical utility (AUC for poor short-term prognosis = 0.707; AUC for short-term mortality = 0.855) and improved calibration and decision-making benefits. Conclusion This study found that the CHG index exhibits a nonlinear positive correlation with poor short-term prognosis and a linear positive correlation with short-term mortality in acute ischemic stroke patients. The CHG-integrated risk prediction model demonstrates superior clinical applicability, suggesting that the CHG index could serve as a novel biomarker for assessing short-term prognosis in acute ischemic stroke patients.