Why the study?
The association between lipid ratios and intracranial atherosclerotic stenosis in a Chinese population was not well defined.
Are lipid ratios associated with intracranial atherosclerotic stenosis in patients with ischemic stroke?
Are lipid ratios associated with intracranial atherosclerotic stenosis in patients with ischemic stroke?
Lipid ratios, particularly apo B/apo A-I, are significantly associated with intracranial atherosclerotic stenosis in patients with ischemic stroke and may serve as useful discriminators for ICAS risk.
Background: We wished to investigate the association of lipid ratios with intracranial atherosclerotic stenosis (ICAS) in a Chinese population. Methods: We included 658 consecutive patients with ischemic stroke in our cross-sectional study. Intracranial and extracranial arteries were evaluated for atherosclerotic stenosis using digital subtraction angiography or computed tomography angiography. Lipid ratios [total cholesterol (TC)/high-density lipoprotein-cholesterol (HDL-C), triglycerides (TG)/HDL-C, low-density lipoprotein-cholesterol (LDL-C)/HDL-C, non-high-density lipoprotein-cholesterol (non-HDL-C)/HDL-C, remnant cholesterol (RC)/HDL-C, apolipoprotein B (apo B)/apolipoprotein A-I (apo A-I), and apo B/HDL-C] were calculated. Results : Ratios of TC/HDL-C, LDL-C/HDL-C, RC/HDL-C, non-HDL-C/HDL-C, apo B/HDL-C and apo B/apo A-I were associated significantly with ICAS but not with extracranial atherosclerotic stenosis after adjustment for confounding factors. Analyses of receiver operating characteristic (ROC) curves revealed the apo B/apo A-I ratio have the highest area under the ROC curve (AUC) value for a lipid level alone and for lipid ratios (AUC = 0.588). Lipid ratios had higher AUC values than those for a lipid level alone for identifying ICAS. Conclusion : The ratios of TC/HDL-C, LDL-C/HDL-C, RC/HDL-C, non-HDL-C/HDL-C apo B/HDL-C and apo B/apo A-I were related significantly to ICAS risk. Compared with the other variables tested, the apo B/apo A-I ratio appeared to be better discriminator for identifying ICAS risk.
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Yang et al. (2020) studied this question.
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