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The role of the small-dense LDL-C/large-buoyant LDL-C ratio as an independent risk factor in patients with type 2 diabetes mellitus and metabolic syndrome

Par : Contributeur(s) : Type de matériel : TexteTexteLangue : français Détails de publication : 2024. Ressources en ligne : Abrégé : Background Dyslipidemia plays a key role in metabolic syndrome (MS), intricately linked to type 2 diabetes mellitus (T2DM). Objective This study aimed to investigate the differences in low-density lipoprotein cholesterol (LDL-C) subfraction levels between T2DM and T2DM with MS, and identify the risk factors associated with the disease. Methods A total of 246 individuals diagnosed with T2DM (including 144 T2DM patients with MS) and 147 healthy subjects were recruited. All participants underwent a comprehensive clinical evaluation. Lipoprotein subfraction analysis was performed using the Lipoprint LDL system. Results Multivariate logistic regression analysis revealed that several lipid markers, including triglyceride (TG), LDL-C, large-buoyant LDL-C (lbLDL-C), small-dense LDL-C (sdLDL-C), LDLC2-5, and the sdLDL-C/lbLDL-C ratio, were identified as independent risk factors for T2DM. Additionally, TG, sdLDL-C, LDLC-4, LDLC-5, and the sdLDL-C/lbLDL-C ratio were found to be independent risk factors for T2DM with MS. Furthermore, the results of the receiver operating characteristic (ROC) curves demonstrated that sdLDL-C, LDLC-4, LDLC-3, and the sdLDL-C/lbLDL-C ratio exhibited excellent predictive performance for the risk of T2DM (AUC > 0.9). Conclusion The sdLDL-C/lbLDL-C ratio emerges as a shared independent risk factor for T2DM and MS complications. Furthermore, the sdLDL-C/lbLDL-C ratio, along with LDL-4 and LDL-3, exhibits noteworthy predictive capabilities for T2DM.
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Background Dyslipidemia plays a key role in metabolic syndrome (MS), intricately linked to type 2 diabetes mellitus (T2DM). Objective This study aimed to investigate the differences in low-density lipoprotein cholesterol (LDL-C) subfraction levels between T2DM and T2DM with MS, and identify the risk factors associated with the disease. Methods A total of 246 individuals diagnosed with T2DM (including 144 T2DM patients with MS) and 147 healthy subjects were recruited. All participants underwent a comprehensive clinical evaluation. Lipoprotein subfraction analysis was performed using the Lipoprint LDL system. Results Multivariate logistic regression analysis revealed that several lipid markers, including triglyceride (TG), LDL-C, large-buoyant LDL-C (lbLDL-C), small-dense LDL-C (sdLDL-C), LDLC2-5, and the sdLDL-C/lbLDL-C ratio, were identified as independent risk factors for T2DM. Additionally, TG, sdLDL-C, LDLC-4, LDLC-5, and the sdLDL-C/lbLDL-C ratio were found to be independent risk factors for T2DM with MS. Furthermore, the results of the receiver operating characteristic (ROC) curves demonstrated that sdLDL-C, LDLC-4, LDLC-3, and the sdLDL-C/lbLDL-C ratio exhibited excellent predictive performance for the risk of T2DM (AUC > 0.9). Conclusion The sdLDL-C/lbLDL-C ratio emerges as a shared independent risk factor for T2DM and MS complications. Furthermore, the sdLDL-C/lbLDL-C ratio, along with LDL-4 and LDL-3, exhibits noteworthy predictive capabilities for T2DM.

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