Early atrial remodeling predicts the risk of cardiovascular events in patients with metabolic syndrome: a retrospective cohort study

Front Cardiovasc Med. 2023 May 3:10:1162886. doi: 10.3389/fcvm.2023.1162886. eCollection 2023.

Abstract

Background: This study aims to assess the prevalence of atrial cardiomyopathy (ACM) in patients with new-onset metabolic syndrome (MetS) and investigate whether ACM could be a predictor of hospital admission for cardiovascular (CV) events.

Methods: Patients with MetS who were free of clinically proven atrial fibrillation and other CV diseases (CVDs) at baseline were included in the present study. The prevalence of ACM was compared between MetS patients with and without left ventricular hypertrophy (LVH). The time to first hospital admission for a CV event between subgroups was assessed using the Cox proportional hazard model.

Results: A total of 15,528 MetS patients were included in the final analysis. Overall, LVH patients accounted for 25.6% of all newly diagnosed MetS patients. ACM occurred in 52.9% of the cohort and involved 74.8% of LVH patients. Interestingly, a significant percentage of ACM patients (45.4%) experienced MetS without LVH. After 33.2 ± 20.6 months of follow-up, 7,468 (48.1%) patients had a history of readmission due to CV events. Multivariable Cox regression analysis revealed that ACM was associated with an increased risk of admission for CVDs in the MetS patients with LVH [hazard ratio (HR), 1.29; 95% confidence interval (CI), 1.142-1.458; P < 0.001]. Likewise, ACM was found to be independently associated with hospital readmission due to CVD-related events in MetS patients without LVH (HR, 1.175; 95% CI, 1.105-1.250; P < 0.001).

Conclusion: ACM is a marker of early myocardial remodeling and predicts hospitalization for CV events in patients with MetS.

Keywords: atrial myopathy; atrial remodeling; cardiovascular diseases; left ventricular hypertrophy; metabolic syndrome.

Grants and funding

This work was supported by the Chang Jiang Scholars Program (grant number T2017124), the Dalian Talents Innovation Supporting Project (2018RD09), the National Natural Science Foundation of China (grant number 81970286), the Program of Liaoning Distinguished Professor, Dalian Science Fund for Distinguished Young Scholars (grant number 2022RJ13), and the LiaoNing Revitalization Talents Program (grant number XLYC2002096).