Dataset Information

HbA1c trajectory and cardiovascular outcomes: an analysis of data from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study.

ABSTRACT:

Background

We investigated the associations between glycated hemoglobin (HbA1c) trajectories and cardiovascular outcomes using data from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study.

Methods

We used HbA1c values within the first 2 years of treatment for modeling with a latent class growth model. Groups of HbA1c trajectories were modeled separately in the standard (group 1-group 4) and intensive (group 5-group 8) treatment arms. The primary outcome in the ACCORD study was a composite of non-fatal myocardial infarction, non-fatal stroke, or death from cardiovascular causes. Effects of HbA1c trajectories on cardiovascular outcomes were analyzed using a Cox-proportional hazard model.

Results

Baseline HbA1c levels for the eight trajectories (group 1-group 8) were 7.8 ± 0.8, 8.2 ± 0.9, 9.3 ± 1.1, 9.6 ± 1.2, 7.8 ± 0.7, 10.1 ± 0.8, 8.3 ± 0.7, and 9.5 ± 1.1%, respectively. The respective values after 2 years of treatment were 7.0 ± 0.6, 7.7 ± 0.7, 8.5 ± 0.9, 10.3 ± 1.3, 6.2 ± 0.4, 6.5 ± 0.6, 7.2 ± 0.6, and 8.5 ± 1.1%. After a median follow-up of 4.8 years, group 5 and group 6 had similar outcomes compared with group 1 (reference group). In contrast, group 3, group 4, and group 8 had higher risks of the primary composite outcome compared with group 1.

Conclusion

HbA1c trajectory was associated with cardiovascular outcomes in type 2 diabetes patients with high cardiovascular risk.

SUBMITTER: Wang JS

PROVIDER: S-EPMC8239983 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAlthough recent guidelines advocate for HbA1c target individualization, a comprehensive criterion for patient categorization remains absent. This study aimed to categorize HbA1c variability levels and explore the relationship between glycemic control, cardiovascular outcomes, and mortality across different degrees of variability.MethodsAction to Control Cardiovascular Risk in Diabetes study data were used. HbA1c variability was measured using the HbA1c variability score (HVS) and standard deviation (SD). K-means and K-medians clustering were used to combine the HVS and SD.ResultsK-means clustering was the most stable algorithm with the lowest clustering similarities. In the low variability group, intensive glucose-lowering treatment significantly reduced the risk of adverse cardiovascular outcomes (HR: 0·78 [95% CI: 0·63, 0·97]) without increasing mortality risk (HR: 1·07 [0.81, 1·42]); the risk of adverse cardiovascular events (HR: 1·33 [1·14, 1·56]) and all-cause mortality (HR: 1·23 [1·01,1·51]) increased with increasing mean HbA1c. In the high variability group, treatment increased the risk of cardiovascular events (HR: 2.00 [1·54, 2·60]) and mortality (HR: 2·20 [1·66, 2·92]); a higher mean HbA1c (7·86%, [7·66%, 8·06%]) had the lowest mortality risk, when the mean HbA1c was < 7·86%, a higher mean HbA1c was associated with a lower mortality risk (HR: 0·63 [0·42, 0·95]). In the medium variability group, a mean HbA1c around 7·5% was associated with the lowest risk.ConclusionsHbA1c variability can guide glycemic control targets for patients with type 2 diabetes. For patients with low variability, the lower the HbA1c, the lower the risk. For those with medium variability, controlling HbA1c at 7·5% provides the maximum benefit. For patients with high variability, a mean HbA1c of around 7·8% presents the lowest risk of all-cause mortality, a lower HbA1c did not provide cardiovascular benefits but instead increased the mortality risk. Further studies, especially those with patients that reflect the general population with type 2 diabetes undergoing the latest therapeutic approaches, are essential to validate the conclusions of this study.