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. 2022 Jan 18:9:100317.
doi: 10.1016/j.ajpc.2022.100317. eCollection 2022 Mar.

HbA1c, Coronary atheroma progression and cardiovascular outcomes

Affiliations

HbA1c, Coronary atheroma progression and cardiovascular outcomes

Iryna Dykun et al. Am J Prev Cardiol. .

Abstract

Background and aims: We tested the hypothesis that on-treatment HbA1c levels independently associate with coronary atheroma progression and major adverse cardiovascular events (MACE: death, myocardial infarction, cerebrovascular accident, coronary revascularization, or hospitalization for unstable angina) rates.

Methods: We performed a post-hoc pooled analysis of data from seven prospective, randomized trials involving serial coronary intravascular ultrasonography (IVUS). The percent atheroma volume (PAV) was calculated as the proportion of the entire vessel wall occupied by atherosclerotic plaque. Using multivariable mixed modeling, we determined the association of on-treatment HbA1c with annualized change in PAV. Cox proportional hazard models were used to assess the association of HbA1c with incidence of MACE.

Results: Among 3,312 patients (mean age 58.6±9years, 28.4%women) average on-treatment HbA1c was 6.2±1.1%. Overall, there was no net significant annualized change in PAV (0.12±0.19%, p = 0.52). In a fully adjusted multivariable analysis (following adjustment of age, sex, body mass index, systolic blood pressure, smoking, low- and high-density lipoprotein cholesterol, triglyceride levels, peripheral vascular disease, trial, region, and baseline PAV), higher on-treatment HbA1c levels were independently associated with annualized changes in PAV [beta-estimate (95% confidence interval): 0.13(0.08, 0.19), p < 0.001]. On-treatment HbA1c levels were independently associated with MACE [hazard ratio (95% confidence interval): 1.13(1.04, 1.23), p = 0.005].

Conclusions: Independent of achieved cardiovascular risk factor control, greater HbA1c levels significantly associate with coronary atheroma progression rates and clinical outcomes. These results support the notion of a direct, specific effect of glycemic control upon coronary atheroma and atherosclerotic events, supporting the rationale of therapies designed to directly modulate it.

Keywords: ACS, acute coronary syndrome; AQUARIUS, Aliskiren Quantative Atherosclerosis Regression Intravascular Ultrasound Study; ASCVD, atherosclerotic cardiovascular disease; BMI, body mass index; CVD, cardiovascular disease; Coronary atheroma progression; Diabetes mellitus; GLAGOV, Global Assessment of Plaque Regression With a PCSK9 Antibody as Measured by Intravascular Ultrasound; HDL-C, high-density lipoprotein cholesterol; HbA1c; HbA1c, hemoglobin A1c; IBIS 2, The Integrated Biomarkers and Imaging Study-2; IVUS; IVUS, intravascular ultrasonography; LDL-C, lipoprotein cholesterol; MACE; MACE, major adverse cardiovascular events; NORMALISE, Norvasc for Regression of Manifest Atherosclerotic Lesions by Intravascular Sonographic Evaluation; PAV, percent atheroma volume; PERISCOPE, Pioglitazone Effect on Regression of Intravascular Sonographic Coronary Obstruction Prospective Evaluation; PVD, peripheral vascular disease; REVERSAL, Reversal of Atherosclerosis With Aggressive Lipid Lowering; SATURN, The Study of Coronary Atheroma by Intravascular Ultrasound: Effect of Rosuvastatin Versus Atorvastatin; STRADIVARIUS, Strategy to Reduce Atherosclerosis Development Involving Administration of Rimonabont – The Intravascular Ultrasound Study; TG, triglycerides; UKPDS, UK Prospective Diabetes Study; hsCRP, high-sensitivity-CRP.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
On-treatment HbA1c levels according to specific patient subgroups and odds of PAV progression vs. regression. Forest plot for the association of on-treatment HbA1c levels and progression vs. regression of PAV across differing patient subpopulations. For on-treatment risk factors, average values were used to create the subgroups. Odds ratio and 95% confidence interval per standard deviation for the on-treatment HbAc1 level was calculated using logistic regression models. Variables adjusted for in each model included baseline PAV, trial, region, age, sex, BMI, smoking, PVD, as well as average on-treatment SBP, LDL-C, HDL-C, and TG.Abbreviations: BMI = body mass index, CI = confidential interval, HbA1C = hemoglobin A1c, HDL-C = high-density lipoprotein cholesterol, LDL-C = low-density lipoprotein cholesterol, PAV = percent atheroma volume, PVD = peripheral vascular disease, SBP = systolic blood pressure, TG = Triglycerides.

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