학술논문

Distinct uric acid trajectories are associated with incident cardiac conduction block
Document Type
Report
Source
Arthritis Research & Therapy. February 27, 2024, Vol. 26 Issue 1
Subject
China
Language
English
ISSN
1478-6354
Abstract
Background The association of longitudinal uric acid (UA) changes with cardiac conduction block risk is unclear. We aimed to identify the trajectories of UA and explore its association with cardiac conduction block. Methods A total of 67,095 participants with a mean age of 53.12 years were included from the Kailuan cohort in Tangshan, China, who were free of cardiac conduction block and with repeated measurements of UA from 2006 to 2012. UA trajectories during 2006 to 2012 were identified by group-based trajectory modeling. Cox proportional hazard regression models were used to assess the association of UA trajectories with cardiac conduction block. Results We categorized three observed discrete trajectories of UA during 2006-2012 period: low-stable, moderate-stable, and high-stable. Over a median follow-up of 6.19 years, we identified 1405 (2.09%) incident cardiac conduction block. Compared to those in the low-stable trajectory, the adjusted hazard ratios (HRs) (95% confidence interval [CI]) of cardiac conduction block in the moderate-stable and high-stable trajectory were 1.30 (1.16-1.47) and 1.86 (1.56-2.22), and HRs of atrioventricular block were 1.39 (1.12-1.72) and 2.90 (2.19-3.83), and HRs of bundle branch blocks were 1.27 (1.10-1.47) and 1.43 (1.13-1.79). Notably, although the average UA level in the moderate-stable UA trajectory group is within the normal range, the risk of cardiac conduction block has increased. Conclusions The moderate-stable and high-stable trajectories are associated with increased risk for new-onset cardiac conduction block. Monitoring UA trajectories may assist in identifying subpopulations at higher risk for cardiac conduction block. Keywords: Uric acid, Trajectories, Cardiac conduction block, Risk factors
Author(s): Na Li[sup.1,2] , Liufu Cui[sup.2] , Rong Shu[sup.2] , Haicheng Song[sup.2] , Jierui Wang[sup.2] , Shuohua Chen[sup.3] , Gary Tse[sup.1,4] , Nan Zhang[sup.1] , Xuemei Yang[sup.5] , Wenqi Xu[sup.3] [...]