Why the study?
Conventional lipid parameters inadequately capture residual ACS risk, leaving the diagnostic utility of sdLDL-C undefined in high-risk populations with multiple comorbidities, particularly in Northeast China.
Does sdLDL-C measurement improve diagnostic risk stratification for acute coronary syndrome in patients with coexisting hypertension and carotid atherosclerosis?
Does sdLDL-C measurement improve diagnostic risk stratification for acute coronary syndrome in patients with coexisting hypertension and carotid atherosclerosis?
sdLDL-C serves as a highly effective diagnostic biomarker for risk stratification in ACS, with its predictive value increasing alongside the burden of comorbidities like hypertension and carotid atherosclerosis.
May improve ACS diagnostic stratification in hypertension with carotid atherosclerosis; extends biomarker evidence but should not yet change practice.[[1]](https://www.dovepress.
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: sdLDL-C levels were significantly higher in ACS patients vs. controls [0.78 vs. 0.42 mmol/L, p < 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.
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Li et al. (2026) studied this question.
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