Analysis of the Relationship Between Glycated Hemoglobin and Echocardiographic Parameters in Patients Without Diabetes: A Retrospective Study

<b>Background:</b> Glycated hemoglobin (HbA1c) is a parameter commonly used in clinical practice to assess glycemic control in patients with diagnosed diabetes. Hyperglycemia is a strong risk factor for developing cardiovascular (CV) disease. Although there is some evidence that this parameter could also help assess CV health in patients without known carbohydrate metabolism disorders, this is not entirely clear. The purpose of this study was to investigate the relationship between HbA1c and selected echocardiographic parameters in patients without diabetes. <b>Methods:</b> This study was a retrospective analysis of data from 59 patients (females: 72.88%) with a mean age of 54.82 ± 17.34 years without any features of acute illness or exacerbation of chronic diseases hospitalized in the Department of Internal Medicine, Angiology and Physical Medicine of the Medical University of Silesia in Katowice (Poland) in the period between June 2022 and May 2024. Only individuals with HbA1c levels and who have undergone transthoracic echocardiography were included in the analysis. Spearman's rank correlation test was used for statistical analysis, and a multivariate analysis model was then constructed (adjusted for age, sex, body mass index, low-density lipoprotein cholesterol, systolic blood pressure, hypertension, and smoking). <b>Results:</b> In univariate analysis, HbA1c was found to be significantly correlated with selected parameters relating to left ventricular dimensions and mass, left atrial dimensions, right ventricular systolic function, mitral inflow profile parameters, and tissue Doppler echocardiography. Multivariate analysis did not confirm a significant association between HbA1c and the assessed echocardiographic parameters. <b>Conclusions</b>: Although HbA1c significantly correlates with some echocardiographic parameters, the observed relationships are entirely explained by confounding variables.