Objective: High-density lipoprotein (HDL) consists of diverse subfractions, each with unique roles in cardiovascular health and disease. This study aimed to evaluate the clinical utility of HDL2b quantification via microfluidic chip electrophoresis (MCE) for acute coronary syndrome (ACS) as prediction and compare its diagnostic performance with conventional lipid parameters. Methods: This retrospective study analyzed 230 participants (126 ACS patients vs. 104 age/sex-matched controls) from Gaozhou People's Hospital (2020-2021). HDL subfractions were quantified using the MICEP-30 MCE system. Univariable logistic regression and receiver operating characteristic (ROC) analyses were performed to assess associations and diagnostic accuracy. Results: The analysis revealed significantly lower HDL2b concentrations in ACS patients compared to controls (median: 248.30 vs. 399.68 μmol/L, p<0.001), with no significant difference in HDL3 (p=0.839). Logistic regression identified HDL2b as the strongest independent predictor of ACS (OR: 0.988 per μmol/L increase, 95% CI: 0.985-0.992, p<0.001), outperforming traditional HDL-C (OR: 0.007) and triglycerides (OR: 1.999). ROC analysis demonstrated HDL2b's superior diagnostic accuracy (AUC: 0.822, 81.0% sensitivity/70.2% specificity at 333.165 μmol/L cutoff), surpassing HDL-C (AUC: 0.810) and other lipid parameters (TG AUC: 0.606, LDL-C AUC: 0.606), while HDL3 showed no discriminative capacity (AUC: 0.508). These findings position HDL2b quantified by microfluidic electrophoresis as a clinically superior biomarker for ACS prediction. Conclusions: HDL2b quantification via MCE emerges as a rapid, precise diagnostic tool for ACS prediction, demonstrating significant advantages over traditional lipid parameters. This technology enables clinically actionable HDL subfraction profiling, with the potential to significantly improve cardiovascular risk stratification paradigms.
Deng et al. (Tue,) studied this question.