The Diagnostic Value of sdLDL-C for Acute Coronary Syndrome with Coexisting Hypertension and Carotid Atherosclerosis in Northeast China

Background: Current cardiovascular risk assessment relies heavily on conventional lipid parameters, which inadequately capture residual risk for acute coronary syndrome (ACS). Small dense low-density lipoprotein cholesterol (sdLDL-C) exhibits heightened atherogenicity due to its unique physicochemical properties, yet its diagnostic utility for ACS in high-risk populations with multiple comorbidities remains undefined. Furthermore, population-specific evidence, particularly from Northeast China where cardiovascular disease prevalence is high, is limited. Methods: This retrospective study enrolled 456 ACS patients and 100 healthy controls. Patients were stratified by hypertension (HT) grade and carotid intima-media thickness (CIMT). Receiver operating characteristic (ROC) analysis was performed to evaluate diagnostic efficacy and determine optimal cut-off values. An independent validation cohort (4 groups, n=100 each) was used to calculate positive predictive value (PPV) and negative predictive value (NPV). Results: < 0.001], showing an increasing trend with disease burden and peaking in the ACS with HT and abnormal CIMT group (ACS+HT+ACIMT). Multivariate logistic regression revealed the strongest association between sdLDL-C and the ACS+HT+ACIMT group, odds ratio (OR)=119.341. ROC analysis demonstrated the highest diagnostic efficacy for this group (area under the curve (AUC)=0.903), with an optimal cut-off of 0.621 mmol/L (sensitivity 88.70%, specificity 83.00%). In the validation cohort, the ACS+HT+ACIMT group achieved PPV of 89.36% and NPV of 84.91%, with narrower confidence intervals, indicating improved predictive accuracy. Conclusion: sdLDL-C exhibits significant diagnostic value in ACS patients, with efficacy increasing alongside disease burden, particularly in high-risk populations with HT and carotid atherosclerosis. The phenotype-specific cut-off (0.621 mmol/L) may serve as an effective risk stratification tool.