Abstract

Background: This meta-analysis aims to clarify the effects of depression on the risk of ventricular arrhythmias. Materials and methods: A systematic search was performed in PubMed, EMBASE, Web of Science, and the Cochrane Library. Summary hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated employing random-effects models. Publication bias of the literature was evaluated using Begg’s funnel plots and Egger’s test. Results: A total of nine prospective cohort studies were included in this meta-analysis. Overall, participants with depression, as compared to those who had no depression, experienced a significantly increased risk of developing ventricular arrhythmia (combined HR, 1.33; 95% CI, 1.02 – 1.73; p = 0.037). In a subgroup analysis, a statistically-significant relation between depression and risk of ventricular arrhythmia was observed in coronary heart disease (CHD) patients and in studies with adjustment for confounding factors, with pooled HR at a 95% CI of 1.78 (1.31 – 2.42) and 1.52 (1.11 – 2.08), respectively. No publication bias was detected by Begg’s funnel plot and Egger’s test. Conclusion: This meta-analysis suggests that depression in patients was associated with increased risk of developing ventricular arrhythmias, especially in patients with CHD. Cardiologists and psychiatrists should be alert to the risk of ventricular arrhythmia in patients with depression. Moreover, the antidepressant medications (e.g., tricyclic antidepressants and selective serotonin reuptake inhibitors) that could affect heart rate variability should be used carefully.

*Yu Fu and Xiaoting Shen contributed equally to this study.

Author Details

Authors

• Yu Fu¹*
• Xiaoting Shen¹*
• Wenbin Huang²

Departments

• ¹ First Affiliated Hospital of Sun Yat-Sen University, Guangzhou and 

• ² Zhongshan Ophthalmic Center, State Key Laboratory of Ophthalmology, 
Sun Yat-Sen University, Guangzhou, China

Address

Wenbin Huang MD, PhD

Zhongshan Ophthalmic Center
State Key Laboratory of Ophthalmology
Sun Yat-Sen University Guangzhou
54S.Xianlie Road, Guangzhou, 510060 China
Email: [email protected]

Citation