Publications by authors named "Aibibanmu Aizezi"

Background: Coronary heart disease (CHD) remains a leading cause of mortality globally. The prognostic value of myeloperoxidase (MPO) and the triglyceride-glucose (TyG) index in predicting adverse cardiovascular events among individuals with CHD remains uncertain. This study aimed to investigate the predictive value of MPO in combination with the TyG index for major adverse cardiovascular events (MACE) in patients with CHD.

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Proprotein convertase subtilisin/kexin type 9 (PCSK9) polymorphisms exhibit ethnic-specific associations with cardiovascular risk. However, their prognostic value for major adverse cardiovascular and cerebrovascular events (MACCE) in Asian populations remains undefined. This prospective cohort study enrolled 1969 patients (mean age 54.

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Objects: Our aim was to identify changes in the metabolome in dilated cardiomyopathy (DCM) as well as to construct a metabolic diagnostic model for DCM.

Methods: We utilized non-targeted metabolomics with a cross-sectional cohort of age- and sex-matched DCM patients and controls. Metabolomics data were analyzed using orthogonal partial least squares-discriminant analysis (OPLS-DA) and pathway analysis.

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Article Synopsis
  • The study investigates the impact of genetic variations in the Dab2 gene on the risk of developing type 2 diabetes mellitus (T2DM) in the Uygur and Han populations in Xinjiang, China.
  • A total of 2,157 individuals were analyzed, revealing significant associations between specific SNPs (rs2255280 and rs2855512) of the Dab2 gene and T2DM in the Uygur population, while no such associations were found in the Han population.
  • The results indicate that individuals with certain genotypes of rs2255280 and rs2855512 have higher odds of developing T2DM, alongside altered plasma glucose and HbA1c levels in the Uygur group.
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Background: VT (Ventricular Thrombus) is a serious complication of dilated cardiomyopathy (DCM). Our goal is to develop a nomogram for personalized prediction of incident VT in DCM patients.

Methods: 1267 patients (52.

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Article Synopsis
  • Researchers aimed to create a nomogram to predict the risk of unplanned ICU admissions in patients with dilated cardiomyopathy (DCM) based on individual clinical factors.
  • The study analyzed 2,214 patients from a specific hospital, using various statistical methods to develop and validate the prediction model, which included factors like emergency admission and heart rate.
  • The final nomogram successfully predicted unplanned ICU admissions, with strong performance metrics, potentially aiding doctors in identifying high-risk DCM patients for better care management.
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