Prevalence and risk factors of prolonged corrected QT interval in general Chinese population

Abstract

Background: Corrected QT (QTc) interval has been correlated with total and CVD mortality. Although much is known about the relation between prolonged QTc interval and clinical outcome, there is no information on the prevalence and specific risk factors of QTc prolongation in general Chinese population. We evaluated the prevalence of prolonged QTc interval and its risk factors in general Chinese population, aiming to fill in the gaps in the literature and provide evidence for potential CVD risk prediction and disease burden estimate in community. Methods: A population-based survey was conducted on 11,209 participants over the age of 35 in rural areas of Liaoning Province from 2012 to 2013. Twelve-lead ECGs and automatic analysis were performed on all participants. Logistic regression adjustments were made by using the Bazett's formula to correlate specific risk factors with prolonged QTc intervals (> 440 ms) for potential confounders. Results: The overall prevalence of prolonged QTc interval was 31.6%. The prevalence increased significantly with age (24.1% among those aged 35-44 years; 28.3%, 45-54 years; 35.2%, 55-64 years; 43.4%, ≥65 years, P < 0.001). Participants with a history of CVD had a higher prevalence of QTc prolongation (40.7% vs. 30.0%). In the fully adjusted logistic regress model, older age, abdominal obesity, hypertension, diabetes, hypokalemia and any medicine used in the past two weeks were associated independently with increased risk for prolonged QTc interval (All P < 0.05). We found no significant differences between general obesity, hypocalcemia and hypomagnesemia with prolongation of QTc interval. Female sex showed opposite results after applying clinical diagnostic criteria, and high physical activity could reduce the risk of prolonged QTc interval. Conclusions: The prevalence of prolonged QTc interval was relatively high in general Chinese population and listed relevant factors, which would help identify patients at risk in pre-clinical prevention and provide evidence for estimating potential CVD burden and making management strategies in community.